Tag: tesla

  • A test mule of Tesla’s upcoming robotaxi has allegedly been spotted in Los Angeles

    A test mule of Tesla’s upcoming robotaxi has allegedly been spotted in Los Angeles

    A prototype of what appears to be Tesla’s forthcoming robotaxi has been noticed by a Reddit user who claims to work at Warner Bros. studio in Los Angeles, where the unveiling of the so-called “Cybercab” is expected to occur on October 10.

    The vivid yellow prototype shown in the attached photo seems to be a heavily disguised two-door model with headlights reminiscent of the Model 3. According to the user Boopitysmopp, who shared the image, the vehicle also features a full-width LED light strip at the back similar to the Cybertruck’s.

    The entire design resembles a life-size Matchbox car, and it could simply be a poor joke, so we’re approaching this with caution. However, considering the location, the shape of the side windows, and the car’s short wheelbase together, we have reason to believe this could be Tesla’s long-anticipated self-driving cab.

    Recently, Musk has shifted his focus from presenting Tesla solely as an all-electric vehicle manufacturer to discussing artificial intelligence and robotics, hinting for some time that Tesla EVs—both existing and new—could soon integrate into a global system of autonomous vehicles that transports people independently for the benefit of their owners.

    Consequently, the upcoming Cybercab holds significant importance for Tesla’s vocal CEO. Could it be the major breakthrough that Musk has predicted? We remain doubtful. The company’s Autopilot and Full Self-Driving (Supervised) features are still classified as Level 2 systems on SAE’s autonomy chart. Additionally, the existing legal framework does not permit fully autonomous vehicles to operate freely on the streets and highways of the United States, indicating that more work is necessary.

    That said, Tesla aims to ensure everything proceeds smoothly during next month’s event. Following a slowdown in global sales, the automaker—sorry, AI and robotics company—has been collecting mapping data from the area where the event is set to occur, according to Bloomberg and renowned Tesla hacker Green The Only.

    This strategy makes sense from a performance perspective, but it contradicts many of Musk’s statements on autonomous vehicles, as he has criticized competing automakers and robotaxi services for relying on pre-existing map data to operate their driverless cars in designated geofenced regions.

    We’ll have to wait and see what unfolds next month during the Tesla Cybercab reveal. If it parallels the Cybertruck reveal in 2019, you might want to set a reminder for at least three years from now to find out if the vehicle is ready for mainstream use.

    Recently, Tesla CEO Elon Musk appears to be losing interest in the automobile industry. He argues that the future of Tesla does not depend on selling more vehicles, but rather on advancements in artificial intelligence and robotics. A key element of that vision involves self-driving cars that can serve as “robotaxis,” which would eliminate the need for human drivers entirely.

    However, Musk seems unwilling to rely on ordinary Model 3 sedans and Model Y SUVs for his version of an Uber competitor. Tesla claims it is creating a vehicle specifically designed as a robotaxi, which Musk suggested might be named the “Cybercab” during a recent earnings call.

    This is an extraordinarily ambitious initiative, one that represents the ultimate evolution of Tesla’s long-term reliance on its Autopilot and so-called Full Self-Driving systems. It is also highly untested, depends on aggressive development of entirely new technologies, relies on uncertain consumer acceptance, faces regulatory hurdles that have yet to be established, and will require Autopilot and FSD to navigate a complicated legal landscape, including a federal criminal investigation.

    In essence, this could be Musk’s boldest and riskiest move up to this point—and it remains far from guaranteed. Nevertheless, let’s examine what we think we know so far, based on the company’s various statements and concept artwork that have surfaced.

    What do we understand about the Tesla Robotaxi?

    For at least ten years, Musk has consistently claimed that self-driving capabilities would soon arrive in Teslas. He has stated over the years that autonomous Teslas could generate considerable passive income for their owners by transporting passengers while parked. None of this has yet materialized.

    In more recent years, Tesla executives have also begun discussing the concept of a vehicle specifically designed for the purpose of being a robotaxi. This means not just a standard Tesla that can drive autonomously at times, but a vehicle engineered from the ground up with that sole aim.

    The robotaxi initiative has taken priority over more traditional—and arguably, wiser—projects at Tesla. In April, Reuters reported that Tesla had abandoned plans for an affordable mass-market vehicle, informally referred to as the Model 2, to focus entirely on the robotaxi. (Musk has suggested that this less expensive model is still a possibility, but it doesn’t appear to be a priority.)

    When Will Tesla Unveil the Robotaxi?

    In April, Musk mentioned in a post on X that Tesla would present the robotaxi on August 8. However, in July, Bloomberg stated that Tesla intended to delay the event until October. The outlet explained that Tesla teams required more time to create additional robotaxi prototypes.

    During Tesla’s Q2 2024 earnings call, CEO Elon Musk confirmed that the Robotaxi reveal would take place on October 10th.

    When Is the Robotaxi Expected to Be Released?

    Up until now, Tesla has not succeeded in achieving fully autonomous driving in its existing vehicles. It markets a feature called “Full Self-Driving,” but this system still necessitates driver oversight and is quite far from being perfect.

    Before introducing robotaxis without steering wheels, Tesla must produce reliable self-driving technology, and it’s uncertain when or if that will occur.

    In response to an investor query on Tesla’s Q2 2024 earnings call, Musk explained that the company couldn’t begin offering rides to customers until Full Self-Driving could operate without supervision. In its earnings report released on Tuesday, Tesla stated that the “timing of Robotaxi deployment is contingent on technological progress and regulatory permission.”

    The robotaxi’s unveiling this evening does not necessarily indicate that it is nearing production. Tesla unveiled the Cybertruck pickup in late 2019, but customers did not receive their trucks until five years later. The design for an upcoming supercar, the Tesla Roadster, was revealed in 2017 and is still yet to be launched.

    What Will the Robotaxi Look Like?

    Now that it has been revealed, we know precisely its appearance. However, prior to its debut, we had a general idea of what to expect. In 2022, Musk indicated that the robotaxi would forgo a steering wheel and pedals, describing its design as “futuristic.” Walter Isaacson, Musk’s biographer, noted that an early concept for the vehicle displayed a “Cybertruck futuristic feel.” This could suggest a more angular, polygonal design compared to the sleek Model 3 and Model Y.

    He provided an illustration in his book, Elon Musk, showcasing a compact, two-seat vehicle with a teardrop silhouette. In April, Musk referred to the robotaxi as the Cybercab. It remains unclear if this will be the actual name, but it would be logical given its reportedly Cybertruck-inspired styling.

    In a video shared on X, Tesla released additional teasers. The clip features what might be the robotaxi’s front bumper and white interior.

    Previously, Tesla has indicated it would construct the robotaxi using its lower-cost, next-generation vehicle framework. Recently, however, Tesla announced it is expediting new vehicle initiatives by employing a blend of its current and next-generation technologies. It remains uncertain which technology will support the robotaxi.

    How Will Tesla’s Competitor to Uber Function?

    During an earnings call, Musk described Tesla’s taxi service as a blend of Airbnb and Uber. The concept is that Tesla’s fleet will consist of both its own robotaxis and vehicles from Tesla owners who decide to participate—meaning you own the car and when you’re not using it, you can “rent” it out for robotaxi service.

    This is a promise Musk has made over the years in different forms. Back in 2019, he stated that by 2020, up to a million Model 3s on U.S. roads would be available as fully autonomous (SAE Level 5) robotaxis. As you may have noticed, that did not materialize.

    Nonetheless, Tesla is evidently heading in that direction. In its earnings report, the automaker displayed some renderings of what its Tesla ride-hailing app might resemble.

    How Does Tesla’s Robotaxi Differ from Waymo, Cruise, and Zoox?

    Waymo and Cruise, autonomous taxi services owned by Alphabet and General Motors, respectively, utilize modified versions of standard electric vehicles for their operations. Waymo employs Jaguar I-Paces, while Cruise works with Chevrolet Bolts.

    As they have developed their self-driving technology on public roadways, both companies have utilized safety drivers who can monitor and intervene if necessary. After a pedestrian accident last year, Cruise temporarily halted operations and is gradually reintroducing its vehicles with drivers present.

    Zoox, the self-driving startup owned by Amazon, is developing a taxi service utilizing specially designed pod-like vehicles that lack steering wheels. However, it is still in the experimental stage and has not yet commenced commercial operations.

    In contrast to other companies, Tesla claims it can achieve dependable self-driving capability using solely cameras. Other autonomous-driving initiatives depend on additional sensors, such as LiDAR units that employ lasers to construct a three-dimensional representation of the environment. Many experts in the field of autonomous vehicles are skeptical that Tesla’s streamlined, vision-only method will succeed.

    What Obstacles Are in the Way?

    How much time do you have? Primarily, the endeavor hinges on Tesla “solving” the challenge of fully autonomous driving, something that many experts caution could take decades rather than just a few years—if it’s ever achieved at all. Moreover, Tesla historically shuns autonomy technologies that other car manufacturers support, such as LIDAR. Instead, it is attempting to train AI through the use of cameras, sensors, and supercomputers.

    Additionally, the United States is not prepared for a large-scale robotaxi network. Although testing and pilot programs for robotaxis are underway in around ten states, no comprehensive federal regulations exist. Issues surrounding accident liability and other concerns need to be addressed first. Furthermore, as previously mentioned, Tesla’s current Full Self-Driving (FSD) and Autopilot systems have faced scrutiny due to high-profile crashes, lawsuits, state investigations, and even a Department of Justice inquiry into whether the company misled investors and consumers about its driver-assistance features.

    Why Is the Tesla Robotaxi Important?

    Tesla, along with its enthusiastic investors and optimistic Wall Street analysts, believes that autonomous driving will enable the company to generate substantial revenue over time. This belief is part of the reason why Tesla has such a high valuation.

    As of now, it is valued at $544 billion, which is roughly ten times the market capitalization of rivals like Ford and General Motors. A functioning robotaxi will be crucial if Tesla aims to meet the expectations set by its inflated stock price.

    “The Robotaxi has no plug,” Elon Musk remarked during the event last night. Is Tesla poised to make a significant move toward inductive charging?

    Well, the moment has finally arrived. Tesla unveiled its eagerly awaited Robotaxi, as well as a driverless Robovan, during last night’s presentation at the Warner Bros. Discovery studio in Burbank, California.

    The event featured the usual Elon Musk speech, interspersed with random audience questions—much like when that engaging substitute teacher comes in trying to make the best of things despite lacking all the details.

    The entire reveal offered minimal technical specifics, leaving us unaware of the battery capacity of the Cybercab, its charging speed, maximum speed, or whether it utilizes rear-wheel, front-wheel, or all-wheel drive. Instead, Musk concentrated on an “optimistic” timeframe projecting that the driverless two-door vehicle will be operational “by the end of 2027” and priced under $30,000. Nevertheless, it’s important to remember that the second-generation Tesla Roadster was introduced in 2017 but has yet to enter mass production.

    That being said, he did share one minor yet intriguing detail: the Tesla Cybercab will charge wirelessly through inductive charging, rather than through a cable. In fact, according to Musk, it does not even possess a charging port, as he briefly mentioned during the evening’s event.

    “Something we’re also doing, and it’s really about time, is inductive charging,” he stated. “So, the robotaxi has no plug. It simply goes over the inductive charger to charge. So, yeah, that’s how it should work. Thanks, everyone. I appreciate your support.”

    But this encapsulates everything we know on the subject, which isn’t much. Numerous questions remain unanswered, such as how long recharging takes, the dimensions of the inductive charger, or the cost of acquiring one. These are all pertinent inquiries, especially considering Tesla’s vision of the Cybercab, which is that individuals will have the ability to purchase one—or several—and manage a personal fleet of driverless cabs from their homes. This effectively shifts the responsibility from the company to the individual while also increasing the costs associated with operating such a fleet.

    Elon Musk stated that the Cybercab could serve as an excellent option for individuals currently driving for Uber and Lyft. In urban centers, many rideshare drivers already utilize electric vehicles, making them familiar with charging an EV and maintaining it. However, if they need to invest in three inductive chargers for a small fleet of Cybercabs, the upfront costs might exceed expectations.

    Additionally, there’s the concern regarding charging speeds. Presently, typical inductive charging solutions generally max out at around 20 kilowatts, which is significantly less than the 250 kW peak rate available at Tesla’s own Superchargers. While there are wireless charging pad prototypes that have achieved 270 kW, they are still years away from being widely available.

    So, how would this actually function? If recharging the Cybercab requires an entire night and it’s anticipated to operate throughout the day carrying passengers, it could lead to challenges. Downtime is crucial in the ride-hailing business. Unless Tesla manages to provide a wireless charging pad that is both affordable and capable of delivering sufficient power to extend range quickly, this plan may face difficulties.

    Elon Musk, the CEO of Tesla, revealed that the Robotaxi will be available for purchase prior to 2027

    Musk unveiled the sleek Robotaxi today at the Warner Bros. Hollywood studio close to Los Angeles. He entered the elegantly designed vehicle featuring butterfly doors, which lacks a steering wheel and pedals, and demonstrated its capabilities by driving it around the Warner Bros. lot.

    Musk indicated that consumers would be able to purchase the self-driving cab for less than $30,000—an objective several automakers aspire to with their standard electric vehicles to tackle affordability issues and attract a wider array of car buyers.

    This price point is notably lower than the Model 3 sedan currently on the market, which starts at over $42,000 following Tesla’s discontinuation of the base rear-wheel-drive variant due to tariffs on components sourced from China implemented last month.

    It’s significant to mention that Tesla has a history of promising inexpensive EVs that turned out to be more costly. For instance, the Cybertruck was initially expected to be priced below $50,000 but now begins at $80,000. Although it’s slated for release in 2026, Musk acknowledged that he often tends to be overly optimistic regarding timelines.

    If Tesla can maintain that under-$30,000 price, it could be transformative. However, before that, Tesla must demonstrate that its Robotaxi is safe and can legally operate on U.S. roads.

    Various AI and autonomous vehicle experts have expressed to InsideEVs that Tesla’s strategy with its self-driving cars has flaws. Tesla solely relies on cameras and AI for the Robotaxi, while competitors like Waymo employ a more comprehensive mix of sensors, including radar and LIDAR. Moreover, there are still unresolved questions surrounding the Robotaxi’s business model and its operational framework.

    We lack detailed information about the platform and how it impacts vehicle pricing, making it unclear how Tesla intends to meet that ambitious price point. However, the automaker has the ability to manufacture at scale and has experience in reducing costs.

    Tesla customers might not need to wait until 2026 to experience autonomous driving. The Model 3 and Model Y are expected to receive unsupervised self-driving capabilities in California and Texas by the end of next year, subject to regulatory approval. Eventually, the Cybertruck, Model S, and Model X are also expected to gain this functionality.

    The company has stated that the Cybercabs would be the “most affordable” and “cheapest to operate.” According to Musk, the average bus ride costs around a dollar per mile, while the Cybercab would charge 20 cents per mile. Considering taxes, it would likely be around 30-40 cents per mile.

    Musk argued that the average car owner drives only about 10 hours a week, despite there being 168 hours in total each week. Thus, he believes that autonomy will allow individuals to save both time and money. Nevertheless, this remains theoretical for now, and it will be interesting to see how it evolves over time.

    Elon Musk has introduced the long-anticipated robotaxi, known as the Cybercab, at the Warner Bros Studios in Burbank, California.

    The futuristic vehicle, which features two wing-like doors and lacks both pedals and a steering wheel, brought Musk in front of a captivated audience eager to learn more about a project he regards as pivotal to Tesla’s future direction.

    During the event titled “We, Robot,” the billionaire reiterated his belief that fully autonomous vehicles will be safer than those driven by humans and could even generate income for their owners by being rented out for rides.

    Investors have not yet shared his excitement – Tesla’s stock price dropped after the US markets opened on Friday morning.

    At 11:45 Eastern Time (16:45 BST), the value of its shares had decreased by over eight percent, trading at approximately $219.

    In contrast, stocks of ride-hailing competitors Uber and Lyft, which also have ambitions in autonomous technology, were each up by as much as 10%.

    Doubts are emerging regarding Mr. Musk’s timeline for the production of the Cybercab, projected to start “before 2027,” considering his history of missing deadlines.

    “I tend to be overly optimistic with timelines,” he humorously remarked during the event.

    He mentioned that the Cybercab – set to compete against rivals like Alphabet’s Waymo – would be priced below $30,000 (£23,000).

    However, analysts question the feasibility of that target.

    “Tesla will face significant challenges in offering a new vehicle at that price within that timeframe,” stated Paul Miller from Forrester research.

    “Without external subsidies or Tesla incurring losses on each vehicle, launching at anything close to that price in this decade doesn’t seem realistic,” he added.

    Concerns about safety were also raised.

    Mr. Musk predicted that “fully autonomous unsupervised” technology would be available in Tesla’s Model 3 and Model Y in Texas and California next year “wherever regulators grant approval.”

    However, such approval is anything but assured.

    “It involves a large piece of machinery operating at high speeds on roads, so safety concerns are paramount,” remarked Samitha Samaranayake, an engineering associate professor at Cornell University.

    Tesla’s ambitions in self-driving technology depend on cameras less expensive than radar and Lidar (light detection and ranging) sensors, which are the foundation of many competitors’ systems.

    By programming its vehicles to navigate autonomously, Tesla intends to utilize artificial intelligence (AI) informed by raw data gathered from its millions of cars.

    Yet the research community “is not convinced that Tesla’s approach provides the safety assurances we desire,” said Mr. Samaranayake.

    The cybercab initiative has faced delays, having originally been expected to launch in August.

    This summer, Mr. Musk mentioned in a post on X, formerly known as Twitter, that the delay was due to design changes he deemed important.

    Tesla also appears likely to record its first-ever annual sales decline as competitors enter the electric vehicle market, even as sales have slowed down.

    Despite this gloomy backdrop, Tuesday’s event was filled with spectacle, featuring Tesla’s humanoid robots dancing and serving drinks to attendees.

    Mr. Musk introduced another prototype for a “Robovan” capable of transporting up to 20 passengers simultaneously.

    The stylish shuttle “might become a new transportation mode that Tesla exploits in the future,” suggested Dan Ives, a managing director at Wedbush Securities, who attended the event.

    Another analyst noted that the event felt reminiscent of the past while also hinting at future directions.

    “Musk adeptly illustrated an ideal future for transportation that aims to save time and boost safety,” commented Jessica Caldwell, head of insights at Edmunds.

    However, despite the showmanship, skepticism remains about his ability to realize the vision he presented.

    “Numerous questions linger about the practical aspects of achieving this,” Caldwell added.

    The progress of robotaxis has faced challenges, as driverless vehicles operated by GM subsidiary Cruise were temporarily halted in San Francisco following an incident involving a pedestrian.

    Nonetheless, the sector keeps growing.

    Waymo announced earlier in October that it would be adding the Hyundai Ioniq 5 to its robotaxi fleet after these vehicles complete on-road testing with the company’s technology.

    Ride-hailing giant Uber also aims to incorporate more autonomous vehicles into its fleet to enhance delivery and ridesharing services for customers.

    In August, it announced a multi-year partnership with driverless car developer Cruise.

    Chinese tech firm Baidu is reportedly planning to expand its robotaxi division, Apollo Go, outside of China, where the vehicles are operational in multiple cities.

    Eight years after pledging a self-driving taxi, Elon Musk has finally introduced the new Tesla Cybercab. It is a fully autonomous vehicle lacking a steering wheel or pedals, and you can purchase one in 2026 for under £23,000 – or so says Elon Musk.

    It was revealed at Tesla’s ‘We, Robot’ event in California, alongside a new autonomous Robovan that will be able to transport up to 20 individuals or cargo across cities without a driver at the helm.

    New Tesla Cybercab set to launch in 2026 for less than £23,000

    The key highlight here is that individuals will have the opportunity to purchase a Tesla Cybercab, contrary to speculation that they would only operate as city-owned fleets. Its price will be below £23,000 ($30,000), and you’ll have the option to rent it out when you’re not using it to earn some extra income.

    Tesla’s autonomous taxi initiative extends beyond the Cybercab, as owners of Model 3s and Model Ys will also benefit from full, unsupervised self-driving in Texas and California next year. Musk asserts that these owners will similarly be able to rent their vehicles out, just like the Cybercab.

    It’s important to consider these timelines with skepticism. Elon Musk himself acknowledged that he tends to be overly optimistic regarding deadlines, having previously promised a million robotaxis on the road by 2020. He also claimed that a self-driving minibus would be available by 2019, whereas we are only now seeing the first concept.

    Naturally, there are several regulatory challenges to address before a car without pedals can gain approval for use in cities worldwide. Therefore, you should expect a wait before seeing a Cybercab navigating around London.

    What is the functioning of the Tesla Cybercab?

    You can essentially think of it as an Uber experience minus any uncomfortable conversations. You’ll be able to summon one via an app on your phone, and it will transport you to your desired location. During the ride, you can watch movies, work on your laptop, or even take a nap.

    The vehicle utilizes a set of cameras and sensors to monitor its surroundings, employing data from countless cars making millions of journeys to enhance its safety over time. This capability relies heavily on Tesla’s artificial intelligence technology rather than solely on hardware, making it cost-effective to manufacture and easy to update.

    A novel feature of the Cybercab is its inductive charging capability. There are no plugs to connect, as you’ll drive over a large wireless charging pad, similar to what you might use for your smartphone, to charge the batteries. However, this should be taken cautiously since significant work on infrastructure would be required for practical implementation. A conventional plug is more likely when the vehicle enters production.

    Interior of the new Tesla Cybercab

    What immediately stands out about the Cybercab’s interior is the absence of a steering wheel or pedals. Tesla typically designs minimalist interiors, but this takes it to an entirely different level.

    You’ll find only a large screen in the center, which can be used to watch movies, make video calls, or stream music. Compared to the Verne Robotaxi, it offers a more enclosed experience, as the Verne has a large glass area for expansive views, whereas the Cybercab is designed to create a more isolated atmosphere from the external environment.

    Design of the new Tesla Cybercab

    Given that this model comes from the same design team responsible for the unconventional Cybertruck, it’s expected to have a very futuristic appearance. And it does.

    Its side profile is unlike anything else currently on the road, featuring a smooth, almost teardrop shape that sharply contrasts with the rounder Verne Robotaxi presented by Rimac earlier this year. The gullwing doors add a distinctive touch as well.

    The car retains several design elements from the Cybertruck, but without the sharply defined angles. You’ll notice a similar full-width light bar at the front, along with a comparable bare-metal finish to the truck.

    Additionally, the rear design reflects more Cybertruck characteristics, with a robust bumper and squared-off back end, and the concealed lights embedded in the bumper also pay homage to that truck design.

    New Tesla Robovan has also been announced

    In addition to the new Cybercab, Tesla has introduced the Robovan. This futuristic minibus operates on the same concept as the Cybercab, allowing you to summon it via your smartphone, with a capacity to accommodate up to 20 passengers.

    The Robovan can also function as a cargo transport across urban areas, and its design is truly wild. Elon Musk stated that this is the design we can expect in production, and given the Cybertruck, we have every reason to believe this.

    The triple light bars positioned at both the front and rear are unlike anything we’ve seen from Tesla previously, and this van breaks new ground by having no windscreen. The interior features comfortable seats that face one another, and it’s a safe bet that there will be numerous screens to entertain all passengers during their journey.

    While the Tesla Robotaxi was the standout feature of Thursday night’s reveal event, the company led by Elon Musk elevated its vision of an autonomous future even further with the unveiling of the Robovan concept.

    Robovan or Robobus?

    “We’re going to manufacture this, and it will resemble that,” Musk told a group of exclusive invitees. The Robovan might include “van” in its name, but the massive vehicle, shaped like a toaster, appears much more akin to a bus or train car. Its art-deco style clearly evokes comparisons to classic locomotives, except the Robovan will utilize automated driving.

    Similar to the Robotaxi, the Robovan is devoid of a steering wheel or pedals. Indeed, the entire interior resembles a waiting room at a dental clinic, albeit one with inviting ambient lighting. The images that Tesla shared reveal a Robovan setup for passenger transport (Musk indicated it can hold 20 people as well as be used for carrying merchandise).

    There are several rows of seats that face each other, featuring large displays mounted on the walls at both ends of the cabin. One side of the Robovan is equipped with a sliding door, partly made of glass, and two glass panel vanes extend along either side of the roof.

    Although we now have our first look at the Tesla Robovan, our knowledge beyond visual features and some mostly ambiguous remarks from Musk is still limited. Tesla’s CEO mentioned it could be customized for either personal or commercial purposes, but there was no information on pricing.

    Importantly, a timeline for when the Robovan will enter production is not yet available, although a launch in 2027 seems plausible at the earliest, as the smaller Robotaxi isn’t expected to start production until sometime in 2026. That timeline is based on Musk’s statements, who is known for being overly optimistic about launch dates, as he acknowledged during Thursday’s event, saying, “I tend to be a little optimistic with time frames.” Naturally, Tesla must also secure regulatory approval for an unsupervised version of its Full Self-Driving (FSD) software, which will influence the future of the Robotaxi, the Robovan, and the company’s other fully autonomous vehicle initiatives.

    Despite reaching impressive expectations, the unveiling of the Cybercab fell flat due to exaggerated claims and limited self-driving capabilities.

    The recent launch of Tesla’s highly awaited Cybercab has ignited significant conversations within the auto industry, impacting much more than just electric vehicles. Initially seen as a revolutionary leap for urban transportation, hopes soared due to months of enthusiastic marketing by Tesla, painting a vision of fully autonomous vehicles transforming city life. However, the event left many feeling dissatisfied as reality did not meet the high expectations, causing a dip in Tesla’s stock price—though it has since recovered due to positive sales predictions.

    So, what went wrong? A primary factor was the immense buzz surrounding the reveal. Teaser videos, enigmatic social media updates, and ambitious assertions about advanced technology heightened the anticipation. Tesla aimed to revolutionize urban transport, presenting the Cybercab as more than merely another electric vehicle—it was meant to be the future of ride-hailing and transportation.

    When the moment finally came, hopes for a groundbreaking product were met with disillusionment. The design, rather than capturing attention with its sleek, forward-thinking look, was likened to outdated science fiction imagery. The Cybercab’s blocky design and uninspired interior appeared to lack any genuine aesthetic innovation or comfort features. Initial renders suggested elegance and ease, yet the actual reveal felt underwhelming, failing to convince anyone this was the automotive future.

    Even more disappointing was the absence of advanced autonomous technology. Fans anticipated that Tesla would fulfill its dream by launching one of the first fully self-driving, commercially viable vehicles. Instead, the Cybercab displayed features similar to those found in many high-end cars today—lane-keeping assistance and adaptive cruise control—while lacking true self-driving functionality. By not delivering on its automation promises, Tesla has set itself apart from rivals like Waymo, who are viewed as closer to achieving fully autonomous vehicles.

    This technological inadequacy was glaringly perceived in financial markets. Investors reacted adversely to the announcement, as it underscored the disparity between expected advancements and the vehicle’s genuine capabilities. While CEO Elon Musk asserted Tesla was only years away from achieving full autonomy, many people now view this timeline as overly optimistic. With regulatory approval for self-driving vehicles requiring extensive testing and proof of safety, Tesla’s goals seem even less attainable.

    Another lingering concern is the expected pricing structure of the Cybercab. With hopes for affordability, analysts were surprised by its features, which rendered the vehicle more similar to high-priced luxury items. The absence of a steering wheel or pedals raised questions about how the Cybercab’s pricing model would compete with more economical options like the forthcoming ‘Model 2’. This discrepancy presents considerable challenges, especially as the broader electric vehicle market copes with its pricing issues.

    The crucial question is: does the Cybercab truly address the needs and desires of urban markets? Critics argue it resembles more of an extravagant tech gadget than a solution to urgent urban transportation problems—such as reducing traffic congestion or offering practical, affordable alternatives for underserved city inhabitants. The reveal suggested that the Cybercab was aimed more at technology elites than at resolving real-life urban transport issues.

    In summary, the market reaction highlights the potential risks of excessively promoting products before they are ready. While the idea of electrified, self-driving urban transport vehicles is undeniably fascinating, the Cybercab reveal has made it evident just how far Tesla still has to go to achieve this goal effectively. The disconnect between public enthusiasm and product capability serves as both a cautionary tale and a learning experience for Tesla and the broader automotive sector as they navigate this dynamic and ever-evolving technological landscape.

    Elon Musk, the leader of the American electric vehicle and clean energy company Tesla, is known for making bold statements and promising innovative futures. At the recent “We, Robot” event, Musk showcased a line of electric robotaxis for the company, including the Cybercab.

    However, despite the presentation’s flashy nature, filled with futuristic designs and staged sci-fi battles, several critical points were overlooked. What other details did you miss during the presentation apart from the shiny robots and grand promises?

     

    Timeline troubles: Why the Cybercab launch is still uncertain

    Their suggestion for Musk to introduce a sub-$30,000 Cybercab devoid of a steering wheel or pedals seems promising, but the timing of its release remains unclear: Musk initially indicated that production would commence in 2026 and later revised it to before 2027, acknowledging that he had set overly ambitious targets in past years. If that’s true, it implies that Tesla has missed this target, particularly concerning its robotaxi initiative.

    Back in 2019, Musk confidently asserted that fully self-driving robotaxis would be operational by 2020. Fast forward to now, and while advancements have been made, completely unsupervised autonomous vehicles have yet to emerge. Such fluctuations in timelines erode the confidence that investors and consumers place in the Cybercab being functional when expected. Even the most dedicated of Musk’s supporters can no longer overlook the evident production issues, which threaten the credibility of his new vision.

    Regulatory challenges: What obstacles is Tesla facing in this venture?

    As Musk envisions a future with the vehicle taking full control, regulation becomes one of the major challenges for Tesla’s robotaxi aspirations. Numerous US states and various international countries have stringent legal frameworks surrounding AV technology, particularly vehicles lacking traditional components like steering wheels and pedals.

    It seems rather bold, if not impractical, for Tesla to aim for a fully driverless vehicle by 2026 and to suggest starting tests in California and Texas. These regulatory challenges were downplayed during the presentation. There was no mention of the extensive testing, safety certifications, and legal compliance that Tesla will encounter.

    Musk also omitted any discussion about investigations into Tesla’s Full Self-Driving (FSD), which has been linked to several accidents. Thus, the path to securing approvals could take significantly longer than Musk’s predicted timeline.

    Safety concerns and technology: Are they overhyping the features of the Cybercab?

    Undoubtedly, the most evident and perhaps significant concern during the Tesla presentation revolved around safety. Musk claimed that self-driving vehicles would be “10, 20, 30 times safer than humans,” referencing data from millions of miles driven by Tesla.

    However, the presentation lacked crucial details on how Tesla plans to mitigate accidents, especially in light of recent FSD concerns. What Musk presented as Tesla’s edge – utilizing artificial intelligence and cameras instead of expensive lidar – has sparked considerable debate.

    Lidar, which employs lasers to map the surroundings of the vehicle, is deemed much more reliable for fully autonomous cars. By neglecting this technology, Tesla leans on its camera-based approach, a choice many analysts consider unwise and premature.

    Additionally, Tesla’s Full Self-Driving system has encountered regulatory challenges and ongoing complaints. Some accidents, including fatal incidents, have been attributed to the autopilot and FSD systems.

    Regulatory bodies are still investigating whether Tesla is sufficiently preventing driver distractions while users engage with the car’s semi-autonomous systems. However, there was no mention of these concerns in Musk’s presentation, leaving many to question just how secure the future of robotaxis will truly be.

    Is Tesla’s vision realistic, or just another hype?

    Elon Musk excels in public relations and has a knack for making people believe in the future of self-driving vehicles and robots. Nonetheless, when it comes to Tesla’s robotaxi project, the presentation fell short of impressive. Several critical factors, including the production timeline, regulatory hurdles, safety issues, and business model, play a significant role.

    As a result, many investors and analysts remain doubtful. While it’s easy to get caught up in the concept of affordable robotaxis, actualizing this vision is far more challenging. Unless these hurdles are addressed, the Tesla robotaxi may remain more of a promotional concept than a tangible product, at least for the time being.

    The future Musk envisions may be incredible, but achieving it will require more than just flash and appeal. The robotaxi transformation may not be far away, but it will still take time before it becomes a reality, particularly until safer technologies are developed and regulations governing these vehicles are clarified.

    Musk expressed during the analyst call that he is “confident” Cybercabs will achieve volume production by 2026.

    “I am confident that Cybercab will reach volume production in ’26, not just begin production, but achieve volume production in ’26,” he mentioned.

    The company must obtain regulatory approval for the Cybercab’s operation, and Musk anticipates receiving this approval next year in Texas and California, which would also enable the launch of its ride-hailing application. In discussing Tesla’s vehicle sector, Musk projected a 20% to 30% increase in vehicle sales next year “despite negative external factors.”

    Tesla aims to manufacture at least 2 million Cybercabs annually

    Musk stated in the call that Tesla intends to produce a “significant” number of robotaxis each year

    The Tesla CEO noted, “We’re targeting at least 2 million units a year of Cybercab. This will occur in more than one factory, but I believe it’s at a minimum of 2 million units yearly, potentially up to 4 million in the end.”

    Musk tempered his statement, referring to these figures as his “best estimates.”

    Musk indicated that the Cybercab will be priced at “approximately $25,000.”

    When Musk initially unveiled the Cybercab at the “We, Robot” event, he mentioned that the company projected a selling price of “below $30,000.”

    During Wednesday’s earnings call, Musk revised that to a cost of “approximately $25,000.” “What we’ve designed is optimized for autonomy,” Musk said. “It will cost around 25K, so it is a 25K vehicle. And you can, you will be able to purchase one exclusively if you wish. It simply won’t include steering wheels and pedals.”

    Tesla will not offer a Cybercab variant featuring a steering wheel or pedals.

    If you were expecting a more conventional sub-$30,000 Tesla model with a steering wheel and pedals, the Cybercab will not have that.

    “So, I believe we’ve made it clear that we — the future is autonomous,” Musk said when asked about the timeline for a $25,000 non-robotaxi vehicle.

    Musk described a regular $25,000 model as “pointless,” asserting that a “hybrid, manual, automatic” vehicle would not be “as good” as an autonomous version. He stated that Tesla is developing a vehicle that is “optimized for autonomy.”

    Musk described the experience of riding in the Cybercab as akin to being in “a personal movie theater.”

    Musk indicated that Tesla will continue to enhance the offerings on Tesla car displays, and once full autonomy is achieved, “you can do anything you want” while in the vehicle because it will be self-driving.

    He provided examples such as browsing the internet, interacting with AI, watching films, playing video games, or engaging in some “productive tasks.”

    “So that’s why the Cybercab features a large screen and a quality sound system so you can watch a great movie,” Musk explained.

    Musk described the machine creating the Cybercab as “revolutionary.”

    He said Tesla is “designing a lot of high volume production,” as well as the “machine that builds the machine,” which he labeled as “revolutionary.”

    “It’s not merely a groundbreaking vehicle design, but also a revolution in vehicle manufacturing accompanying the Cybercab,” Musk stated. “The cycle time, like, the units per hour of the Cybercab production line is — this is truly something exceptional.”

    Musk mentioned that the machine constructing the machine is designed to be five times more efficient than a conventional factory regarding cycle time.

    Tesla asserted that it has effectively combined factors such as who will manufacture the vehicle, its production location, shipping methods, and assembly processes to create “the most efficient factory possible.” This will be evident in Tesla’s capital expenditure efficiency once implemented, in addition to the selection of parts and overall performance, as highlighted by the company during the call.

  • Tesla’s Next Move 2025: Model 2 Or Model Y Juniper? Wait and See

    Tesla has always been clear – making cars is, for Musk’s marque, more a crusade than a commercial enterprise. Its Fremont plant has a display that perfectly sums up its mission statement about transitioning the world to sustainable transport: a 20th-century petrol pump next to a sleek 21st-century Tesla Supercharger, echoing the classic illustration depicting the evolution of primate to homo sapiens. You must go back here to understand the origins of the Tesla Model 2.

    Losing sight of the mission statement, nothing much Tesla does makes sense. Back in 2016, it could have relaxed with the Model S and Model X and stayed a niche, premium player. But no. The Model 3 arrived, orders soared, and Tesla faced growing pains as it adapted. The Model Y, its fourth car, has been even more popular. Despite recent price reductions, the most affordable Tesla remains a £40k proposition. To complete the job, Tesla needs a £25k car, named the Model 2. It aims to be nothing less than the battery-electric equivalent of the Ford Model T.

    CEO Elon Musk has described the new car as ‘our next-generation low-class vehicle’, and for ‘low-class’ read financially accessible. A teaser silhouette revealed at the shareholder meeting last May hinted at a smaller Model Y, designed for aerodynamics and ease of manufacture rather than a standout design like the Cybertruck, which is a relief.

    Similar to the Model 3 and Model Y, there are likely two cars in the works – Musk informed shareholders of this last May. Both will utilize a new architecture, codenamed NV9X, and additional versions are anticipated, although Musk has criticized established manufacturers for creating ‘variants for the sake of variants’, so those waiting for, for example, an estate will probably be disappointed.

    Tesla needs two body styles because it requires international sales. Larger models have a broad appeal globally, but the major markets differ when it comes to smaller cars. Hatchbacks will sell in Europe, but not as much in the US or China. Similarly, small sedans are niche in Europe but popular in China.

    Collectively, Tesla aims for annual sales of five million units, up from a total of 1.81 million in 2023 (1.74 million of which were Model Y/3). Musk aspires to surpass the Toyota Corolla or VW Golf globally.
    In February, Ford CEO Jim Farley referred to the upcoming smaller Tesla as ‘the ultimate competition’. Before fulfilling that ambitious promise, Tesla must perfect the assembly process. Once again, the company is focusing its innovation on the production of the car, rather than reinventing the elements that the consumer will engage with.

    ‘This is a revolutionary manufacturing system; far more advanced than any other automotive manufacturing system in the world by a significant margin,’ Musk boasted to analysts on the company’s earnings call in January.

    What Tesla excels at is also what the Chinese excel at, which is building EVs more affordably. This enables both disruptors to sell at lower prices and capture market share from established car makers.

    Tesla has been relentless in reducing the cost of Model 3 and Model Y, some of which was reflected in price cuts while the rest contributed to profit margins. However, a significant change was needed to bring the new Model 2 down to $25k, the price that Musk mentioned in 2020. ‘We are approaching the limits within our current platforms,’ chief financial officer Vaibhav Taneja stated on the January call.

    Tesla aims for a 50 per cent cost reduction in building the next-generation vehicle. The major innovation is to modernize Henry Ford’s 111-year-old production line and transition to what Tesla calls ‘unboxing’. Instead of the car slowly taking shape from initial metal stamping to body shop to paint shop and then final assembly – ‘Most of the time we’re doing nothing to it,’ head of vehicle engineering Lars Moravy said – Tesla intends to reorganize the factory to sub-assemble related parts.

    For instance, the rear ‘megacast’ platform will be equipped with wheels, seats, and the rear drive unit, while the front seats and center console will be installed onto the battery pack. All the pre-assembled parts will then be assembled together in one final burst of efficiency.

    Tesla aims to operate with fewer workers to increase cost-effectiveness, allowing for a 40% reduction in the manufacturing footprint. Initially, Tesla planned to build the car in a new plant in Mexico, but it has since announced that the first production will take place in Austin, Texas alongside the Cybertruck.

    According to Musk, ‘Giga Texas’ was selected because the engineers need to be present during the initial phase, and it’s more feasible there than elsewhere, especially considering the potential challenges from German unions in Berlin. A third production site is being considered, possibly in Berlin, given the model’s significance in Europe.

    Musk cautioned that the ramp-up will be gradual, citing the production challenges experienced with the Model 3. Although the Model 3 entered production in 2017, it wasn’t until 2019 that the car became available in the UK. It may take until 2027 for the next-generation car to arrive in the UK, by which time new competitors will likely emerge to challenge Tesla.

    The Cybertruck, Tesla’s newest model, will incorporate some of the latest technology, specifically the transition to a 48-volt electrical architecture from the current 12 volts. This change offers cost savings by reducing the use of expensive copper while enabling faster communication between electronic components, as noted by Musk.

    Tesla has been at the forefront of developing the ‘software-defined car,’ where fewer but more powerful computers process data more efficiently than numerous smaller ECUs. This ‘centralized compute’ system is also easier to update over the air, allowing for the quick addition of new digital features to the large central screen.

    Another potential carryover from the Cybertruck is drive-by-wire technology, which would eliminate the steering column and make adjustments to the yoke wheel ratio, but this may come with additional costs that Musk might not be willing to accept for the base model.

    The ‘Full Self-Driving’ suite, which is actually a hands-on, eyes-on Level 2 autonomous system at least in Europe, will likely be included, although with the removal of more sensors than additions, it remains uncertain if the Model 2 would achieve Level 2+ hands-off, eyes-on capability, let alone full autonomy.

    Tesla emphasizes data learning over sensor input to address challenging self-driving scenarios, but regulatory approval of this approach may be a point of contention.

    Range will be a critical factor. While Tesla cannot directly improve battery chemistry, this responsibility falls to suppliers such as China’s CATL and BYD for the more affordable LFP chemistry, as well as South Korea’s LG Chem and Panasonic from Japan.

    However, Tesla plans to utilize the larger 4680 cylindrical battery, which the company has been developing to replace the smaller 2170 battery. Tesla claims that this battery’s increased energy density will result in extended range, as well as improved manufacturing efficiency and reduced costs. According to Tesla, the larger battery involves 15 parts and 21 manufacturing processes, compared to 17 parts and 33 processes for the smaller 2170 cell.

    Tesla is also scrutinizing the design and construction of the electric drive unit (motor, inverter, gearbox) to reduce costs. The company aims to achieve a 75% reduction in silicon carbide, a material that enhances range and efficiency but adds to costs. Tesla also claims that the next-generation permanent-magnet motor does not require rare earths. Overall, Tesla estimates that it has reduced the cost of its drive unit to around $1000.

    It is unclear how much Tesla will reduce the battery size to achieve an attractive price point, such as under £30,000 in the UK. However, it is expected that at least one version will achieve a range of over 300 miles on the official range test, and an all-wheel-drive option is also likely, considering the potential demand from wealthier car buyers in Europe’s snow-prone regions.

    It is fair to say that Tesla has been working towards this car since its inception, starting from the production of the first Roadster by Lotus for Tesla in 2008. The company’s journey has been focused on relentlessly driving down the costs of electric cars to a point, perhaps three years from now, when this car will be affordable for buyers who currently opt for a Golf or Qashqai, prompting them to switch. This prospect should make competitors like Volkswagen and Toyota extremely nervous.

    The much-anticipated affordable entry-level electric car from Tesla, commonly referred to as the Tesla Model 2, is expected to be launched in the first half of 2025, as reaffirmed by Tesla CEO Elon Musk during the company’s latest financial results call.

    It’s possible that we may soon get a proper look at the highly anticipated EV, as Musk mentioned: “We delayed the unveiling of the Robotaxi product to 10 October. I wanted to make some important changes that I believe will enhance the Robotaxi and we’ll also showcase a couple of other things.”

    The timing seems appropriate, as presentation slides for investors indicate that Tesla’s more affordable model will start production in the first half of 2025. It will utilize elements of the company’s next-generation platform along with some from its existing architectures and will be manufactured on the same production lines as its current vehicle lineup.

    Tesla acknowledges that this approach won’t allow for as much cost reduction as previously expected but will enable the company to “Prudently grow our vehicle volumes in a more capex efficient manner during uncertain times”. This will help fully utilize the current expected maximum capacity of close to three million vehicles, enabling more than 50% growth over 2023 production before investing in new manufacturing lines.

    Positioned as a more affordable addition to Tesla’s four-strong model range, the Tesla Model 2 has been in development for some time as the company aims to lower the entry price to its range of EVs below the base Model 3 that currently starts from £39,990 in the UK.

    Only one official teaser image of the new ‘baby Tesla’ has been unveiled so far. It was revealed in 2023 at an annual shareholder meeting and depicts the curving roofline of a car with similar design cues to those of the existing Model Y SUV and Model 3 saloon.

    Our exclusive images interpret Tesla’s existing line-up and teaser images in a scaled-down format to illustrate how a baby Tesla Model 2 model might appear. Based on the single teaser image we’ve received and a video shared on social media showing some design sketches, the new car could borrow numerous design elements from the Model Y SUV. We also anticipate that it will reflect the newly facelifted Model 3 with thinner headlights compared to Tesla’s older models.

    The Model 2 should be positioned as a competitor to traditional family hatchbacks, with a length of around 4.4 meters. This could be achieved through a more aggressive rear roofline while still allowing for a conventional bonnet with luggage space beneath it.

    Despite speculation about the car being called the Tesla Model 2, this name is not guaranteed to be used, especially since Model 3 was chosen as a reverse of Model E, which Ford initially warned Tesla against using.

    Musk has stated, “We’re going to take everything we learned from [Models] S, X, 3 and Y, the Cybertruck, and the Semi into that platform. We’re trying to get to that 50 per cent number again.”

    This refers to the Model Y, which has significantly lower bare construction costs than the Model 3. Tesla used improved processes to eliminate a significant amount of complexity from the Y; for example, a fresh pair of larger stamped components in its bodyshell alone perform the job of 171 separate parts in the Model 3, saving more than 1,600 welds during manufacturing.

    Tesla is expected to utilize its “revolutionary” new manufacturing process called ‘unboxed’ to produce its entry-level EV, which is designed to be more efficient than current production lines and should also be faster.

    Elon Musk informed analysts in 2023 that the next-generation vehicle “Will be about half the cost of the Model 3 and Y platform”. However, as we mentioned, Tesla doesn’t anticipate achieving that level of cost reduction.

    Nevertheless, the baby Tesla could still significantly undercut the starting price of a Model 3, which is currently £39,990. We estimate the Model 2 could feasibly start at around the £30,000 mark.

    This would considerably expand Tesla’s potential market, providing the company with a competitor for European-made electric hatchbacks such as the Volkswagen ID.3 and even Chinese models from the likes of MG and BYD. Considering that the Model Y was not only the world’s best-selling EV but also the most popular car overall last year, with 1.23 million units sold, a more affordable alternative from Tesla itself certainly has the potential to achieve a similar level of popularity.

    In addition to the Model 2 being more affordable to purchase, former Tesla CFO Zach Kirkhorn asserted that the total cost of ownership for the company’s entry-level model per mile over five years will be significantly lower than a base Model 3 or Toyota Corolla.

    In 2023, Colin Campbel, who was the powertrain head at Tesla, announced that the new electric motor for the upcoming vehicle would not utilize any rare earth materials. Additionally, the powertrain would be compatible with any battery chemistry, providing greater flexibility for sourcing.

    The successful production of Tesla’s new smaller car is highly dependent on the choice of battery chemistry and the method of cell installation. The company has previously utilized lithium-iron phosphate cells (LFP), which are more cost-effective to manufacture than nickel manganese cobalt (NMC) cells.

    Currently, the manufacturer incorporates LFP cells into some of its vehicles, and this is likely to be a significant component of the technical makeup of the more affordable model. The company is reportedly preparing to introduce ‘cell-to-chassis’ technology in German-built Model Ys as part of a collaboration with China’s BYD. This innovative method, which is lighter and more compact than traditional module-based construction, conserves space that can be utilized for additional cells to compensate for LFP’s lower energy density, thereby achieving a comparable range.

    Elon Musk is confident that Tesla can build on its recent milestone of producing three million cars and expand its output to more than 100 million vehicles by the end of the decade. To accomplish this, he stated that the company would require “roughly a dozen factories,” with most facilities capable of producing up to two million cars annually.

    There is significant anticipation surrounding the anticipated Model Y Juniper update, and a prominent Tesla observer now suggests that the unveiling of a Model 2 may take place at a Tesla event on October 10. Referred to as the 2025 Model 2, this vehicle, which has been described as a “stripped down Model 3,” is the subject of much anticipation. The vehicle, hyped by CEO Elon Musk as a $25,000-$30,000 car, could potentially be a focal point at Tesla’s autonomous electric ride-hailing taxi event, dubbed “We, Robot,” at Warner Bros. Studios in Burbank, California, on October 10, according to Gene Munster, a managing partner at Deepwater Asset Management, an investor in Tesla.

    “I’m expecting the unveiling of three vehicles (although most are anticipating two), and I believe we will only receive information about the production timeline for the Model 2, which I anticipate will commence in late 2025,” according to a note from the investment firm dated October 4. “This timeline is a few months later than what Elon’s comments suggested on the June earnings call. One potential surprise could be that the more affordable Model 2 is essentially a stripped down Model 3, which would be viewed unfavorably by investors,” the note mentioned.

    Although Tesla CEO Elon Musk is known for being flexible with delivery dates, it appears that a more affordable vehicle is indeed in development. “We are on track to deliver a more affordable model in the first half of next year,” he stated during the company’s second quarter earnings conference call. While not officially named by Tesla, analysts commonly use the Model 2 moniker to refer to the car.

    (UPDATE: On October 10, Musk discussed a low-cost vehicle, but it was a fully-autonomous Cybercab with no steering wheel and no pedals. It is expected to be priced under $30,000 and is due in 2026.)

    The Model 2 may be linked to Tesla’s upcoming October event, even if Musk does not explicitly mention the future affordable Tesla. “The vehicle to be introduced may have dual purpose for consumer sales and robotaxi use,” said Stephanie Brinley, an analyst at S&P Global Mobility, referring to a future low-cost Tesla. This suggests that the car could be an integral part of Tesla’s strategy for fully autonomous ride-hailing vehicles.

    Musk has publicly expressed confidence in this strategy. “We’re convinced we can make a compelling $25,000 electric vehicle that’s also fully autonomous,” he stated in 2020.

    The 2025 Model Y Juniper: Following the 2024 Model 3 refresh, Tesla enthusiasts are eagerly anticipating the next version of the Model Y. The Tesla SUV is the best-selling electric vehicle in the U.S. and is one of the most widespread cars in urban areas such as Los Angeles, as well as one of the top-selling cars globally. It was unveiled in 2019.

    There was widespread speculation this summer after a Reddit post appeared to show a future Model Y wrapped in black. Subsequent “leaks” purported to reveal a new Model Y with a rear light bar. However, there will not be a Juniper model released this year. “No Model Y ‘refresh’ is coming out this year,” Musk stated in June. “I should note that Tesla continuously improves its cars, so even a car that is 6 months newer will be a little better,” he explained.

    One thing is for sure, though. The design is starting to show its age. “Tesla is now delivering vehicle volumes like a traditional automaker, and traditional automakers understand that a fresh lineup is what retains customers,” Joseph Yoon, an analyst for consumer insights at Edmunds, informed me in July.

    Model Y Juniper might resemble the Model 3 update: the Model 3 update likely provides hints about the Model Y that is set to be released in 2025.

    Performance: The Model 3 Performance boasts more horsepower (up to 510 hp) and accelerates from 0–60 mph in 2.9 seconds. Front: The front now features a smoother hood (bump removed) and low-profile headlights for improved aerodynamics.
    Ride: “Frequency response dampeners” have been added to ensure a smoother ride in the updated Model 3.
    Tires: Enhanced tires and wheels have been installed to extend the range and reduce noise.
    Seats: Ventilated seats have been incorporated.
    Cabin: The cabin is now quieter due to 360-degree acoustic glass, meaning all windows are now made of acoustic (double-glazed) glass, not just the windshield and front side glass.
    Screen: A rear entertainment screen for passengers has been introduced, allowing for gaming, streaming, and climate control.
    Stalkless: The stalks on the steering wheel have been removed, with physical controls now moved to thumb buttons on the steering wheel.
    Controls: More software (display-based) controls, including a gear selector integrated into the touch screen, have been added.
    Sound: An improved sound system has been included.
    Hardware 4 (HW4): Anticipated to feature the latest Hardware 4, bringing enhancements in computing power and sensor capabilities for Autopilot and FSD.
    Motor: Potentially enhanced motors, such as a more efficient rear motor, may have been installed.

    And other potential upgrades not influenced by the Model 3 update:

    Rear: Updated taillights and bumper; there are rumors of a rear light bar.
    Cameras: An additional camera could be integrated into the front bumper to enhance Autopilot and FSD capabilities — although this is not confirmed.
    Battery: There could be a larger battery pack (unverified rumors suggest a massive 95 kWh battery) that could significantly increase the range. Currently, the largest battery pack in the Model Y is 75 kWh. Additionally, it’s almost guaranteed that Tesla is consistently enhancing its battery technology, so new battery tech in the Model Y Juniper will likely be more efficient, providing more miles per kilowatt hour (kWh).

    Is there still a plan for a more affordable Tesla Model 2?

    In April, Tesla refuted rumors about canceling their entry-level EV project and Elon Musk dismissed them as fabrications. Shortly after, design chief Franz von Holzhausen hinted at something in the pipeline, despite much of the focus being on the robotaxi project.

    The speculated Tesla Model 2 has no official launch date and details on its design remain mysterious. Our artists have envisioned a potential five-door body style that blurs the lines between hatchbacks and crossovers. This smaller Tesla could offer practicality and leverage smart electric architecture.

    Potential competition for this offering includes electric hatchbacks like the VW ID.3 and MG4, as well as similarly sized crossovers like the Renault Megane E-Tech and the upcoming Nissan Leaf. It could serve as a new entry point in Tesla’s lineup, positioned below the Model 3 sedan and Model Y crossover in terms of pricing.

    Launching a new model demands significant investments in production and R&D, and Tesla must ensure that demand justifies these costs. Additionally, smaller segments often yield less profit compared to larger, more premium counterparts due to thin margins, and the development and testing phases require careful consideration.

    Recent sales slumps and a sharp drop in overall EV registrations across Europe serve as reminders that the EV market is unpredictable. To achieve its goal of selling 20 million vehicles annually by 2030, Tesla needs competitive products and a favorable climate for EV popularity worldwide. Predicting the latter remains uncertain.

    The smaller EV would be the most affordable member of Tesla’s lineup, priced at less than A$40,000. The public and media have even named the new Tesla model “the Model 2.”

    Despite public events making Elon uneasy, he knows how to generate interest. He has a history of teasing products that take years to materialize, such as the Cybertruck, the Tesla Semi, the Roadster, and now the Cybercab — allegedly due in 2026.

    The We, Robot event took place at Warner Brothers Movie Studios in California and featured Musk being picked up by a small two-door electric vehicle and taken away. The fully autonomous Cybercab (or Robotaxi) was introduced as the future of personal transportation, allowing owners to send it out to transport paying passengers to their destinations while they could stay at home and relax.

    Apart from its large, disc wheels (which are actually a visual illusion achieved with some additional gold paint) and scissor-opening doors, the gold-colored Cybertaxi did not appear significantly different from other Tesla vehicles. It featured the sleek sports car nose and bulging front wheel arches of the Model 3, while the rear design gave off strong Cybertruck vibes.

    However, what if this was actually the Model 2 and no one realized it? It’s the type of joke that Musk would likely find very amusing.

    Should we be preparing ourselves for a tweet that is completely out of context, asking for opinions on the looks of the Model 2? Or perhaps the display was a way to gauge public opinion on the new or proposed design of what will eventually become the Model 2. Only Musk and his inner circle would have that information.

    Up until now, the only image of what could potentially be the Model 2 that has been revealed by Tesla is a silhouette of a vehicle shown during the company’s annual shareholder meeting in 2023.

    Then, at the beginning of this year, a low-resolution photo of a two-door hatch-style vehicle started circulating, reportedly of the Model 2 being developed at Tesla’s Giga factory in Berlin. This is not an official Tesla image, but many believe it to be a genuinely leaked photo of a mule or prototype, possibly for the Model 2.

    The exclusive CarsGuide image you can see here is our artist’s interpretation of what the Model 2 could look like based on Musk’s announcements, the design of the Cybercab from the We, Robot event, and those previous teasers. Time will tell how accurate our rendering was compared to the production model.

    All we have to rely on is what Musk has disclosed, which is that an affordable, smaller vehicle will be added to the lineup in 2025 and will be positioned below the Model 3. He hasn’t even confirmed that Model 2 will be the name.

    According to Musk, this smaller EV is expected to be manufactured at Tesla’s Giga Factory in Texas, alongside the Model Y, and is set to launch in 2025. It was initially expected to utilize a completely new platform shared with the Robotaxi, but reports have indicated that it will combine new production techniques from the Cybercab with a cost-cut version of the Model Y’s underpinnings.

    “I think the revolution in manufacturing that will be represented by that car will blow people’s minds,” Musk said. “It’s a level of production technology that is far in advance of any automotive plant on Earth.”

    Musk needs a smaller, lower-priced model in his lineup if he intends to compete or survive against new players such as BYD and other Chinese carmakers who are moving faster than mainstream brands to bring affordable electric vehicles to consumers.

    Unlike other deadlines that have been delayed by years, Musk’s plans to introduce the Model 2 next year must come to fruition, otherwise Tesla might not be able to keep up with the new rivals who are already off to a very quick start.

    If Tesla gets it right, the Model 2 has the potential to surprise the market and challenge established brands like Ford, Toyota, Hyundai, Mazda, Volkswagen, and Nissan.

    However, it might already be too late. Following the We, Robot event, Musk’s net worth dropped by US$15 billion as Tesla’s shares plummeted by nine percent. There is some optimism, though, with Musk pledging that the Cybercab will be relatively affordable at under US$30,000 (A$45,000) per unit, suggesting that a more traditional small Model 2 could meet the promised price target.

    Although the Cybercab event seems to have been a major disappointment, most viewers were probably more disappointed that Musk did not use We, Robot to unveil the Model 2. But perhaps he did.

    Tesla Guide: Tesla Dual Motor VS Single Motor?

    Tesla’s popularity has been on the rise for good reasons. These electric vehicles don’t resemble traditional electric cars; they are high-performance vehicles that can easily go unnoticed by Tesla fans. Despite their high cost, many people have opted for the rear-wheel-drive model with just one motor. However, there is a debate about whether the dual-motor option is worth the extra expense.

    Tesla Dual Motors vs. Single Motor: The choice between a single and a dual motor depends on your specific needs and preferences. Dual motor Teslas offer all-wheel drive, more horsepower, and faster acceleration, while single motor Teslas are more affordable and have rear-wheel drive.

    If you are thinking about purchasing a Tesla and want to make an informed decision between a dual or single motor, it’s crucial to do your research. Understanding the differences between the two motor types is essential in making the right choice.

    What is Tesla? It’s important to comprehend the distinction between dual motors and single motors.

    Tesla is based in Palo Alto, California, and is known for producing electric vehicles that do not rely on gasoline. These cars are equipped with powerful batteries that can be charged at home or using Superchargers on the road.

    Regardless of whether they feature dual motors or just one motor, Teslas offer great value. They eliminate concerns about fluctuating gas prices and regular maintenance costs. While the upfront cost of a Tesla may be higher, it results in significant savings over time compared to gasoline-powered vehicles.

    Teslas are an excellent choice for environmentally conscious individuals as they produce no harmful pollutants due to their lack of reliance on gas or oil, contributing to cleaner air.

    The appealing appearance of Tesla’s vehicles is a major selling point for many customers. Prior to Tesla, electric cars were easily recognizable, but Tesla sought to change that by creating stylish electric vehicles.

    Tesla offers a variety of models, including the popular sedan models Model 3 and Model S, as well as the Model Y and Model X.

    The more affordable versions of the Model S and Model X are the Model 3 and Model Y.

    The Difference Between Single and Dual Motor Systems: It’s important to understand the distinctions between these two motor systems in order to make an informed decision. By learning about their key differences and operations, you can make a more informed decision.

    What is a Single Motor System? The single motor option is less expensive and involves a single rear motor. Not all Tesla models offer this option, and selecting it means the vehicle is only rear-wheel-drive.

    Pros of a single motor system:

    – Potentially improved reliability due to fewer vehicle parts.
    – Lower cost.

    Cons of a Single Motor System:

    – Limited to rear-wheel drive.
    – Not available in all Tesla models.
    – Shorter range.
    – Lower horsepower.
    – Slower 0-60 acceleration.

    While the single-motor system may be sufficient for most users, it is limited to rear-wheel drive. This system is easier to maintain and may be more cost-effective than a dual motor system.

    What is a Dual Motor System? A dual motor system includes two separate motors: one rear motor, which is the same as in a vehicle with a single engine, and an additional front motor. The front motor enables all-wheel drive and faster acceleration.

    Pros of a Dual Motor System:

    – Increased vehicle range.
    – More horsepower.
    – Faster acceleration (0-60).
    – Four-wheel drive.

    Cons of a Dual Motor System:

    – Higher cost.
    – Potential for increased likelihood of breakdown due to more parts (although this is not a significant concern).

    Dual motor systems are the best choice for individuals seeking all-wheel power and requiring greater acceleration, range, or power.

    Tesla Dual Motor: Worth the Price? After understanding the differences between single motors and dual motors, it’s important to determine whether a dual motor is the right choice for you.

    Dual-motor vehicles with AWD offer numerous benefits. All-wheel drive (AWD) is one of the advantages of choosing a dual motor. AWD allows the vehicle to quickly adapt to changing road conditions and distribute weight to maintain traction regardless of weather conditions.

    What is all-wheel power? A quick overview: Dual motor systems are utilized to provide all-wheel drive. For instance, when the vehicle is exerting greater effort during acceleration, it redistributes weight from the front to the back. This enables the front motor to reduce power to prevent wheel spin and maintain stability. During this process, the excess energy from the front-mounted motor is transferred to the rear-mounted motor to ensure vehicle stability.

    In challenging weather conditions, the dual-motor system operates in the opposite way. Instead of transferring power from the front motor to the back, it provides more torque and power to the front.

    What is AWD?

    For those living in areas with infrequent snow or rain, all-wheel drive may not be necessary.

    Consider all-wheel drive as the safest option in extreme weather conditions. AWD is a system that enables power distribution to all wheels at all times.

    Why do we need AWD?

    If you reside in a region with frequent wet and snowy conditions, an all-wheel system will make your vehicle safer compared to a rear-wheel drive vehicle.

    A dual-motor option is optimal for areas with harsh weather conditions.

    Conclusion

    Some consumers are comfortable and confident in purchasing a single motor system. The dual-motor electric car will provide more power, acceleration, and a greater range.

    The last thing you want is to buy a single motor and later regret not choosing the dual-motor. I have seen this happen to Tesla users in the past, which is why I am grateful I chose the Dual Motor option.

    A Tesla is an excellent choice, regardless. I hope this article has helped you decide which model, single motor or dual-motor, is best suited for you.

  • Tesla uses a neural network for the autopilot system in the vehicles

    What are Neural Networks?Neural networks are a series of algorithms that aim to imitate the human brain in order to identify patterns from data. They process information using machine perception by grouping or labeling raw input data.

    Consider the complexity of the human brain, which is composed of a network of neurons. It has the remarkable ability to quickly grasp the context of various scenarios, something that computers struggle to do.

    Artificial Neural Networks are designed to address this limitation. Initially created in the 1940s, Artificial Neural Networks seek to mimic the functioning of the brain. Sometimes referred to as perceptrons, an Artificial Neural Network is a hardware or software system. It consists of a layered network designed to emulate the operations of brain neurons.

    The network includes an input layer for data processed entry and an output layer for presenting information. Connecting the two is a hidden layer, or layers, comprised of units that transform input data into useful information for the output layer.

    In addition to emulating human decision-making processes, Artificial Neural Networks enable computers to learn. Their structure allows ANNs to efficiently and effectively identify complex patterns that may be challenging for humans to discern. Furthermore, they enable us to rapidly classify and categorize large volumes of data.

    How do Biological Models of Neural Networks Work?
    What aspects of human brain structure do neural networks imitate, and how does the training process function?

    All mammalian brains are made up of interconnected neurons that transmit electrochemical signals. Neurons have various components: the body, which includes a nucleus and dendrites; axons, which connect to other cells; and axon terminals or synapses that transmit information or stimuli from one neuron to another. Together, they carry out communication and integration functions in the nervous system. The human brain possesses a vast number of processing units (86 billion neurons) that facilitate the performance of highly intricate functions.

    How do Artificial Neural Networks Work?

    Artificial Neural Networks consist of several layers, each containing artificial neurons known as units, which process, categorize, and organize information. The layers are accompanied by processing nodes, each holding specific knowledge, including programmed rules and learned rules, allowing the network to learn and react to various types of data. Most artificial neural networks are fully connected across these layers, with weighted connections determining the influence between units.

    The input layer receives information in various forms, which then progresses through hidden layers for analysis and processing. This processing helps the network learn more about the information until it reaches the output layer, where it works out responses based on the learned information. ANNs are statistical models designed to self-adapt and understand concepts, images, and photographs using learning algorithms.

    For processing, developers arrange processors in parallel-operating layers: input layer, hidden layer, and output layer, analogous to the dendrites, cell body, and synaptic outputs in the human brain’s neural network, respectively. The hidden layer uses weighted inputs and a transfer function to generate output.

    Various types of Neural Networks

    The recurrent neural network, a commonly used type, allows data to flow in multiple directions, enabling complex tasks such as language recognition. Other types include convolutional neural networks, Hopfield networks, and Boltzmann machine networks, each suited for specific tasks based on the entered data and application. More complex tasks may require the use of multiple types of ANN.

    Tesla is betting big on autonomy based on neural networks with an impressive showcase.

    Today, Tesla hosted an “Autonomy Investor Day” at their headquarters in Palo Alto, CA. At the event, Tesla detailed its plans for advanced driver assistance and eventual car autonomy. The presentation delved into more technical details than previous Tesla disclosures, significantly improving my perception of Tesla’s methods and prospects. This was undoubtedly Tesla’s most significant press event to date.

    Unlike most companies working on fully autonomous vehicles, Tesla has taken a distinctive approach. The company plans to rely solely on radar and an array of video cameras around the vehicle to accomplish this.

    Most other teams also use these technologies, but supplement them with LIDAR (laser) sensors, which provide the vehicle with exceptional 3-D vision regardless of lighting conditions. During the presentation, Tesla provided a more in-depth explanation of why it has chosen this approach and its criticisms of alternative approaches.

    Not only did Tesla express disagreement with other methods, but Elon Musk also derided LIDAR as a “fool’s errand” and asserted that those who depend on it are “doomed.” He also predicted that all other players “will dump LIDAR, mark my words .” Similar sentiments were expressed regarding the use of detailed “HD” maps to understand the road based on previous trips over it.

    In essence, Tesla is making a substantial bet that they can address all self-driving challenges using neural networks. They believe that neural network approaches are indispensable for solving the problem, asserting that other methods, including additional sensors like LIDAR, are distractions and unnecessary expenses.

    If this bet proves successful, it will be a significant triumph, potentially positioning Tesla as the leader in what is perhaps the most substantial opportunity in modern industry.
    There is a lot to dissect from this presentation, and more articles on this topic will follow.

    New Chip

    Tesla has developed its own custom chip tailored for the specific processing needs of their vehicles, and they are now integrating this chip into all new cars. They are convinced that it provides all the computing power necessary for full self-driving. The chip was designed to dedicate its silicon exclusively to driving-related tasks and to keep power consumption under 100 watts to avoid affecting the vehicle’s range.

    The majority of the chip is allocated to conducting dot products for neural network convolutions. Musk contends that this chip surpasses all others globally in terms of neural network capabilities, a claim that may be disputed by other companies developing similar chips. Tesla primarily compared its performance to NVIDIA’s general-purpose GPU chips.

    The hardware boasts impressive specifications and is likely adequate for the required computations. While similar chips may become available from other providers, Tesla anticipates that designing their own chip and integrating it into millions of cars will yield long-term cost savings, even factoring in development In addition to the neural network hardware, the chip features a mid-level GPU and 12 64-bit ARM cores for general-purpose computing. The hardware is designed with redundancy to withstand the failure of any component.

    Network training

    Tesla has focused on enhancing its neural networks with its new network hardware, emphasizing the training of better neural networks to categorize objects encountered on the roads. The company believes its competitive advantage lies in the extensive fleet of cars, currently amounting to around half a million cars, which they utilize for network training.

    Andrej Karpathy outlined some of the strategies they employed. Initially, they trained their networks using human-labeled images, and when they encountered something they wanted to improve network training on, they requested their car fleet to upload relevant images, enabling them to amass thousands of images for training data to enhance network performance.

    Their approach encompassed various stationary and moving objects and also involved identifying patterns of movement, such as requesting examples of cars cutting in front of Tesla cars. This enabled them to analyze pre-cut-in video footage to train the network to predict future car activities on the road.

    They also applied this methodology to path planning, observing human drivers’ path choices in different road scenarios to understand typical human responses. In cases where errors were observed, they prioritized obtaining better data to network enhance training.

    Additionally, they achieved significant success in training their networks to estimate distances to objects in the field of view. One method involved leveraging car radars, which provided precise distance measurements to all radar targets. By correlating radar targets with visual targets, they trained the network to estimate distances to visual targets accurately.

    Tesla’s extensive fleet of drivers granted them immediate access to new data relevant to their team. It is important to note that any entity with a vast network of dashcam recordings could potentially leverage this approach, although accessing radar data might be a limitation. This type of data is available to multiple parties should they choose to record it. However, Tesla can more effectively manage its fleet due to its regular software updates across all its cars.

    This approach has empowered Tesla to establish a robust system for training neural networks for perception and driving. The pivotal question revolves around whether this approach is adequate to achieve the utmost reliability, often referred to as the “final 9s,” necessary to eliminate the car’s steering wheel. Tesla contends that reaching this extremely high level of reliability requires extensive training data, an area in which they have a competitive edge with their large fleet. While it is widely acknowledged that more data is beneficial, there is ongoing debate on whether it is sufficient or if additional techniques are imperative to achieve such an exceptional level of reliability.

    Managing software

    Tesla has implemented this approach with its recent update for “Navigate on Autopilot,” allowing the vehicle to make lane changes automatically. Initially, this feature required drivers to confirm each lane change. Tesla analyzed drivers’ responses to suggested changes and used the data to improve the system. With automatic lane changes, the system now receives feedback on 100,000 automated changes daily, reporting no accidents related to these maneuvers.

    The company also intends to apply this method to enhance its automatic emergency braking (AEB) system to anticipate potential obstacles, including pedestrians, cyclists, and sudden lane intrusions, by the end of this year.

    Comparison: Tesla vs. Industry

    The main focus of the entire presentation revolved around Tesla’s distinct choice to forego the use of both LIDAR technology and detailed high-definition maps, unlike most other major players in the industry. by other companies.)

    The decision by Tesla not to utilize LIDAR has sparked controversy. Though Musk’s viewpoint that LIDAR is a crutch represents a minority stance, the company has presented a compelling argument in support of this position. For a more in-depth analysis of this pivotal issue of cameras versus LIDAR, refer to my detailed article on the matter.

    In summary:
    1. LIDAR provides consistent visibility in all lighting conditions, while camera views are heavily influenced by factors like day/night variations, weather, and the sun’s position.
    2. LIDAR offers true 3D perception, whereas cameras rely on software to interpret the scene and determine the spatial positioning of objects.
    3. LIDAR observes the environment at shorter ranges and lower resolutions.
    4. Although LIDAR is considerably more expensive, its cost is rapidly decreasing. However, it is not yet commercially available in sufficient quantities and quality levels, except for Waymo. In contrast, cameras are highly affordable.
    5. The reliability of computer vision required for camera-based systems to enable self-driving capabilities is not currently at an adequate level, although many are optimistic about imminent breakthroughs.
    6. LIDAR alone is insufficient for certain scenarios, such as accurately identifying road debris, traffic signals, and distant objects. tested, extensive computer vision capability is essential.

    Tesla Network

    Elon Musk presented on the upcoming Tesla network, which I will provide a more detailed account of tomorrow. Users will have the ability to set specific times and regulations governing the use of their vehicles by others.

    Initial key points:

    Tesla has pledged to eventually establish a ride-hailing service, resembling Uber in appearance, where Tesla owners’ private vehicles will operate in autonomous mode, generating income for the owner. For instance, owners could designate their car as available for the next 5 hours , after which it would join the network and provide rides before returning. They have projected that this service could be available in just 3 years, significantly increasing the value of each Tesla due to its potential revenue-generating capability.

    The extent of interest in this option remains uncertain, as well as how many owners will keep their vehicles prepared for immediate deployment to serve others. (Many people store personal items in their cars and may be unwilling to deplete the battery suddenly.) For those who do opt for this, the car will naturally incur expenses and depreciation, estimated at around 37 cents per mile, but Tesla anticipates it could be reduced to 18 cents per mile with their vehicle. Tesla forecasts a network cost of $1 per mile, which is half of Uber’s, but final conclusions have not been reached.

    Tesla is highly committed to this concept. In fact, Musk has announced that they will start encouraging customers to purchase the lower-end “Standard Plus” Model 3 instead of the long-range Model 3, as they are constrained by the number of batteries they can produce.

    Selling cars with smaller batteries means they can sell more cars, leading to an increased number of vehicles for their future robotaxi service. Musk was questioned about Tesla’s spending on Autonomy and he stated “It’s essentially our entire expense structure,” indicating a significant investment in this plan.

    This year, Tesla acquired over $2 million worth of lidar sensors from Luminar. Despite Elon Musk’s disdain for lidar, which he has previously described as a “crutch” and indicated that companies relying on lidar for autonomous capabilities were “doomed,” Tesla appears to be stockpiling these sensors.

    Luminar, an Orlando-based lidar manufacturer, revealed in its quarterly earnings report that Tesla was its “largest LiDAR customer in Q1,” accounting for over 10 percent of the company’s revenue for the quarter, which amounts to approximately $2.1 million worth of lidar based on Luminar’s $21 million quarterly revenue. This substantial purchase from Tesla helped offset a decrease in revenue driven by a reduced volume of sensors supplied to non-automotive companies. However, it was not enough to prevent Luminar from announcing layoffs affecting around 20% of its workforce, and Tesla also initiated employee layoffs.

    This marks a significant turnaround for Tesla, as the company has significantly reduced the number of sensors it uses to power advanced driver-assist features like Autopilot and Full Self-Driving over the years. These are features that Musk has consistently positioned as a precursor to a fully autonomous vehicle fleet. It is expected that Tesla will unveil a robotaxi prototype later this year, a project on which Musk is staking the future of the company.

    Musk’s aversion to lidar was evident during Tesla’s recent quarterly earnings call, during which he emphasized the reliance on camera-based vision systems to power the vehicles’ driver-assist features and boasted about the potential for achieving self-driving with a relatively low-cost inference computer and standard cameras, without the need for lidars, radars, or ultrasonic sensors.

    The purpose of Tesla’s acquisition of $2.1 million worth of Luminar lidar sensors remains unknown. Luminar spokesperson Milin Mehta declined to comment, and Tesla has not formally responded to any reporters’ inquiries since 2019.

    Nevertheless, it should not be entirely surprising that Tesla is showing interest in lidar technology. In 2021, a Tesla Model Y was spotted in Florida with rooftop lidar sensors manufactured by Luminar. Additionally, Bloomberg reported that Tesla had partnered with Luminar to utilize lidar for “testing and developing,” although the specifics of this collaboration remain undisclosed.

    When questioned in 2021 about the Tesla deal, Luminar founder and CEO Austin Russell declined to comment, citing “customer confidentiality.” He mentioned that Luminar sells its older Hydra lidar units to certain customers for “testing, development, data collection, [and] benchmarking.”

    Even if Tesla is using Luminar’s lidar to validate its Full Self-Driving feature for an upcoming robotaxi launch, that’s still a substantial amount of lidar. According to Luminar, individual lidar sensors cost around $1,000, including software. Could it be that Tesla purchased 2,100 lidars for its vehicles? Possibly! The company is quietly operating an autonomous testing fleet in multiple cities, including San Francisco and Las Vegas. Will it retrofit those company-owned vehicles with Luminar’s lidar? If it does, people will take notice, just like they did with the one Model Y in Florida several years ago. We will soon find out whether those vehicles are ready to hit the road.

    In response to a Musk-fan account mocking this article on X, Musk stated that Tesla didn’t require the lidar for validation purposes, without clarifying the purpose of the sensors.

    What does appear evident is that Tesla is shifting its stance on lidar, even if Musk publicly remains opposed to it. Eventually, the CEO himself may be compelled to set aside his pride and acknowledge that lasers are indeed valuable.

    NHTSA reports that at least 20 vehicle crashes occurred after Tesla recalled 2 million vehicles with Autopilot. The government is seeking to understand the reasons behind this.

    Following Tesla’s voluntary recall of 2 million vehicles with Autopilot, there have been at least 20 crashes involving Tesla vehicles with Autopilot engaged. The National Highway Traffic Safety Administration (NHTSA) disclosed this information in a recent filing.

    Tesla issued a recall for over 2 million vehicles with Autopilot in response to NHTSA’s investigation into numerous crashes involving the company’s driver-assist feature, including several fatal ones. The recall aimed to address concerns related to driver inattention and Tesla’s warning systems, which NHTSA stated have contributed to hundreds of crashes and dozens of fatalities. However, last month, the agency initiated a new investigation into Tesla’s fix and is now requesting additional information from the company.

    In its request for information, NHTSA mentioned that a preliminary analysis revealed at least 20 crashes in Tesla vehicles equipped with the updated version of Autopilot. Of these crashes, nine involved Teslas colliding with other vehicles or pedestrians in their path — termed “frontal plane” crashes by the agency. These crashes suggest that Tesla’s camera-based vision system may be insufficient in detecting certain objects in front of the vehicle when Autopilot is engaged.

    NHTSA is asking Tesla to provide data that will enable its investigators to compare vehicle performance in these types of crashes before and after the recall, including the number of “Hands-on-Wheel” warnings issued to drivers. Last month, NHTSA criticized Tesla’s ” weak driver engagement system with Autopilot’s permissive operating capabilities.”

    Other details requested by NHTSA include explanations for Tesla’s one-week suspension policy for misuse of Autopilot, driver monitor warnings, driver-facing alerts, and the single pull versus double pull of the driver stalk to activate Autopilot. NHTSA is also seeking information about ” Tesla’s use of human factor science in its design,” including the number of employees dedicated to these designs.

    NHTSA is requesting data from Tesla regarding the collection of telemetry data following crashes that happen when the vehicle is in Autopilot or Full Self-Driving mode. Additionally, it is seeking more information about how Tesla utilizes the in-cabin camera to monitor driver attention. The agency warns that failure to comply with its information request could result in Tesla facing fines of up to $135 million. Tesla has time until July 1st, 2024, to provide the requested information.

    Elon Musk, the CEO of Tesla, has previously expressed his opinion that lidar sensors are a crutch for autonomous vehicles. Nevertheless, Tesla has become the top customer of the lidar manufacturer Luminar after purchasing a significant number of lidar sensors from the company.

    Luminar recently revealed in its first-quarter earnings report that Tesla contributed to over 10% of its revenue in the first quarter of 2024, totaling a little more than $2 million. Despite a 5% decline in revenue from the previous quarter, mainly attributed to reduced sensor sales to non-automotive clients, Luminar’s revenue was bolstered by increased sensor sales to Tesla, its largest lidar customer in Q1. Luminar also noted a 45% year-over-year revenue gain.

    During the first quarter, Luminar reported a net loss of $125.7 million, an improvement compared to the $146.7 million loss reported during the same period the previous year. The company attributed its net loss to accelerated depreciation for equipment expected to be abandoned following certain outsourcing actions initiated in fall 2023.

    In recent news, Luminar announced plans to reduce its workforce by 20% and outsource a significant portion of its lidar sensor production as part of a restructuring effort to scale the business.

    Tesla has been observed using lidar and other sensors on its test vehicles, and there have been reports of a partnership with Luminar dating back to 2021. However, details of this collaboration have never been disclosed. Luminar included Tesla in its earnings report in line with historical SEC guidance, revealing the information just prior to Tesla’s anticipated reveal of a robotaxi on August 8.

    Elon Musk has consistently argued against the use of lidar for autonomous vehicle navigation, stating that it is an unnecessary and expensive sensor. Musk previously asserted at Tesla’s “Autonomy Day” event in 2019 that relying on lidar is futile and akin to having multiple unnecessary appendices .

    Musk also mentioned at the same event in 2019 that Tesla would launch a fleet of robotaxis within a year, a promise that did not materialize. Instead, Tesla’s involvement in purchasing lidar sensors continues.

    The term “lidar” stands for light detection and ranging and was initially developed alongside the invention of lasers in the 1960s. While it was intended to play a significant role in the advancement of autonomous vehicles, negative remarks from the leader of a prominent autonomous vehicle company were not favorable for the Lidar technology sector.

    Chinese car manufacturers are at the forefront of the shift towards Lidar technology in the automotive industry.

    In 2023, more new cars were equipped with Lidar compared to the previous four years, with Chinese automakers leading this trend. Analysts at the Yole Group predict that around 128 car models with Lidar will be launched by Chinese manufacturers this year, surpassing the expected releases in Europe and the US.

    The cost of Lidar technology in Chinese cars has substantially decreased, with an average price of USD 450-500, compared to the global average of USD 700-1000. The global market for Lidar in passenger cars, light commercial vehicles, and robotaxis was estimated to be USD538 million in 2023, marking a 79% increase from the previous year.

    Although more passenger cars are currently integrating Lidar compared to robotaxis, this gap is expected to narrow as the market continues to expand. Japanese and South Korean car manufacturers are also likely to introduce car platforms with Lidar in 2024 or shortly thereafter. The decreasing cost of Lidar technology has facilitated its adoption in lower-priced car segments.

    This trend highlights how certain technologies may take time to mature but can experience rapid growth once their moment arrives. For example, QR code technology only gained prominence in Australia after the COVID-19 lockdowns, and Bluetooth technology, developed by Hedy Lamarr in 1941, became widely utilized in recent decades.

    Despite Elon Musk’s previous skepticism, he has now begun integrating Lidar into vehicles, although without a full endorsement. Lidar, which stands for “Light Detection and Ranging”, utilizes laser projections to create detailed real-time maps of the surrounding environment. Besides aiding autonomous vehicles, Lidar is used for creating precise 3D scans of various landscapes and structures.

    Furthermore, it played a role in the production of Radiohead’s House of Cards music video. When mounted on a vehicle, Lidar can generate accurate 3D maps of the surroundings up to 60 meters in all directions, enhancing the vehicle’s ability to detect obstacles and avoid collisions Despite its cost, Lidar provides visibility in scenarios where other sensors may fall short.

    “Lidar is a hybrid technology, situated between cameras and radar, that can detect distance and objects while discerning the shape of those objects,” said Richard Wallace, who leads the Transportation Systems Analysis group in the Center for Automotive Research.

    Cameras and radar, both employed in the Tesla Model S, have their limitations, Wallace noted. “Cameras, like our eyes, rely on optics. In low light or during a blizzard, cameras struggle.”

    On the other hand, radar excels at detecting objects and their distance but cannot provide information on the shape or size of the object. The radar in the Model S likely detected the truck it collided with, but it is programmed to ignore objects that resemble overhead road signs to avoid “false braking events.”

    “They have to do that, otherwise imagine going down a highway and every time you come to an overpass it hits the brakes,” Wallace explained. “Clearly the algorithm needs some refinement.”

    While appreciative that the Model S is not designed to be fully autonomous, Wallace suggested that Tesla may need to reconsider its stance on Lidar to achieve its self-driving ambitions.

    “I know Elon Musk has said Lidar isn’t necessary. He’s obviously a smart guy, but ultimately, I believe it will be proven that Lidar is needed,” he said. “It adds a level of resiliency and redundancy that makes the integration easier to solve.”

    The integration Wallace refers to involves the algorithms and intelligence that coordinate the function of the various sensors. “All sensors have their own limitations. How can you create the brain that integrates them and makes the correct decisions?”

    Wallace believes that lidar and vehicle-to-vehicle communication, where each car communicates its location to others nearby, will both be crucial in building safer self-driving fleets.

    Google uses Lidar units that cost up to $70,000 in its self-driving cars, although there are now units available for as little as $250. This could potentially make Lidar more accessible for the mass market.

    However, simply having Lidar does not guarantee the safety of a driverless car. Google’s fleet has experienced its fair share of accidents and technical issues, although there have been no reported fatalities to date.

    Tesla declined to comment but referred the Guardian to Musk’s previous comments about Lidar not being necessary for driverless navigation. The company also pointed to a list of factors in the Model S user manual that can impede the performance of autopilot, including poor visibility, bright light , damage or obstructions caused by mud, ice, snow, and extreme temperatures.

    The list of limitations is accompanied by a warning stating: “Never depend on these components to keep you safe. It is the driver’s responsibility to stay alert, drive safely, and be in control of the vehicle at all times.”

    The company also directed readers to a blogpost titled Your Autopilot Has Arrived, which asserts: “The driver is still responsible for, and ultimately in control of, the car. What’s more, you always have intuitive access to the information your car is using to inform its actions.”

    Understanding the construction of a LiDAR system

    A LiDAR system requires specific equipment to measure a million distances from sensors to surface points. It operates at a high speed, capable of calculating distances based on the speed of light, which is 300,000 kilometers per second. In various applications, including automotive vehicles, aircraft, and UAVs, LiDAR systems consist of three main components:

    Laser Scanner

    LiDAR systems emit laser light from different mobile platforms like automobiles, airplanes, and drones, and receive the light back to measure distances and angles. The scanning speed significantly impacts the number of points and echoes recorded by a LiDAR system, while the choice of optic and scanner profoundly influences its resolution and operating range.

    Navigation and positioning systems

    It is essential to determine the absolute position and orientation of a LiDAR sensor when mounted on aircraft, a vehicle, or an unmanned aerial system (UAS) to ensure the usefulness of the captured data. Global Navigation Satellite Systems (GNSS) provide accurate geographical information about the sensor’s position (latitude, longitude, height), while an Inertial Measurements Unit (IMU) precisely defines the sensor’s orientation (pitch, roll, yaw) at this location. The data recorded by these devices are then used to create static points comprising the basis of the 3D mapping point cloud.

    Computing technology

    Computation is necessary for a LiDAR system to define the precise position of echoes and make the most of the captured data. It is used for on-flight data visualization, data post-processing, and to enhance precision and accuracy in the 3D mapping point cloud.

    Matching project needs with LiDAR specifications

    Laser Scanner: Evaluate the accuracy, precision, point density, range, and swath that best suits your project requirements.
    GNSS: Assess the compatibility of the GNSS reference station (terrestrial) and GNSS receiver (moving) with the GNSS used (GPS, GLONASS, BEiDOU, or Galileo) and determine if a ground station is needed.
    Batteries: Determine if the LiDAR system uses internal or external batteries and the required autonomy to cover the intended mapping area.
    Mounting: Consider if the LiDAR system can be easily mounted on the aerial/airborne platform (drone, aircraft) or automotive platform (vehicle) you intend to use.
    Datafile: Look into the format of the generated data file, for example, YellowScan LiDAR models associated with CloudStation software can export point clouds as .LAZ or .LAS files, as well as digital terrain or elevation models.
    Data Post-processing: Assess the ease of using the data and delivering the best 3D mapping point cloud to your end customer. Consider classification, colorization using additional high-resolution cameras, DTM generation, and what to do with the post-processed data.

    Uncovering applications of LiDAR on UAVs

    Energies & Utilities: conducting powerline surveys to identify sagging issues or plan trimming operations
    Mining: undertaking surface/volume calculations to enhance mine operations (stockpile, excavation) or decide on mine extension
    Construction & engineering: creating maps for leveling, planning, and infrastructure optimization (roads, railways, bridges, pipelines, golf courses) or renovating post natural disasters, conducting beach erosion surveys to develop emergency plans
    Archaeology: mapping through forest canopies to accelerate discoveries of objects
    Forestry: mapping forests to optimize activities or assist in tree counting
    Environmental research: measuring growth speed and disease spreading

    Exploring the use of UAV for LiDAR mapping

    • Learn more about DJI UAVs for LiDAR mapping such as DJI M600 or DJI M300.
    • Selecting the appropriate UAV for your next LiDAR surveys is a challenging task. Read further about how to select your UAV to commence your LiDAR operations.
    • Discover the crucial aspects of a good UAV LiDAR integration or some instances of integrating our LiDAR models on drone or airborne platforms.

    Is it possible for LiDAR to penetrate through trees?

    LiDAR systems with multiple returns and higher pulse rates can aid in reducing the impact of vegetation interference. Additionally, specialized processing methods can be utilized to filter out foliage and generate more precise ground elevation models. While LiDAR can offer valuable insights even in vegetated areas, its effectiveness relies on the specific conditions and technology used.

    Can LiDAR be employed for scanning in low light?

    Indeed, LiDAR can be utilized for scanning in low light since it does not rely on visible light like conventional cameras. LiDAR systems emit their own laser pulses, which are then reflected off objects and returned to the sensor. The system measures the time it takes for the pulses to return, enabling the creation of a detailed 3D map of the environment, irrespective of ambient light conditions.

    This functionality makes LiDAR particularly useful for tasks such as autonomous driving vehicles, surveillance, and navigation under low-light or nighttime conditions. Moreover, LiDAR is increasingly utilized in the consumer market, as seen in Apple’s iPhone. The integration of LiDAR technology into the iPhone’s camera results in faster, more accurate autofocusing, particularly in low-light conditions, contributing to the delivery of sharp, focused images even in challenging lighting situations.

    How does LiDAR identify objects?

    LiDAR identifies objects through the emission of rapid laser pulses and the use of sensors to measure the time it takes for those pulses to bounce back after hitting surfaces. The system calculates the distance based on the time delay, creating a point cloud that represents the shape and position of the object in 3D space. This enables accurate object detection and mapping in various applications such as autonomous driving vehicles, environmental monitoring, and others. The point cloud can also be utilized to generate a digital elevation model (DEM) or a digital terrain model (DTM).

    Can LiDAR penetrate through the ground?

    LiDAR is capable of penetrating the ground to some extent, depending on the material and conditions. The ability of LiDAR to penetrate the ground is constrained by factors like the type and thickness of the material. For instance, LiDAR can penetrate vegetation or even water, employing bathymetric lasers to measure underwater surface depth. However, dense soil or rock cannot be penetrated by LiDAR. Ground-penetrating radar (GPR) is a distinct technology designed specifically to penetrate the ground and provide information about subsurface structures, functioning on different principles compared to LiDAR scanning.

    At what range is LIDAR accurate?

    The accuracy of LiDAR can vary based on several factors, including the type of LiDAR system, the technology utilized, the quality of the equipment, and the specific application. Generally, LiDAR is renowned for its high accuracy in measuring distances, often achieving sub-centimeter to centimeter-level accuracy under favorable conditions.

    For airborne LiDAR systems, commonly employed for mapping large areas, the accuracy can be maintained even at longer distances. High-end airborne LiDAR systems can attain accuracies of a few centimeters at distances ranging from tens to hundreds of meters.

    It’s essential to note that accuracy can be influenced by factors such as atmospheric conditions, the reflectivity of the surfaces being measured, and the quality of the LiDAR equipment. Calibration, data processing, and correction techniques in software also play a critical role in achieving accurate results.

    Self-Driving Cars

    What embodies the “future” more than a self-driving car? Over the past 30 years, we’ve envisioned cyberpunk dystopian worlds where androids dreaming of electric sheep evade captors by boarding driverless vehicles. Perhaps these vehicles could fly, but you understand the point.

    Autonomous vehicles are no longer just a dream. While most of them are still in prototype stage, they are unquestionably a reality today. Numerous companies

    Artificial Neural Networks in Financial Services

    In the realm of AI banking and finance, Artificial Neural Networks are well-suited for making predictions. This capability is largely due to their capacity to swiftly and accurately analyze vast amounts of data. Artificial Neural Networks can process and interpret both structured and unstructured data . Once this information is processed, Artificial Neural Networks can make precise forecasts. The accuracy of the predictions improves as more information is provided to the system.

    Enhancing Operational Efficiency of Banks

    The predictive capabilities of Artificial Neural Networks are not limited to the stock market and exchange rate scenarios. These capabilities also have applications in other areas of the financial sector. Mortgage assessments, overdraft calculations, and bank loan evaluations are all based on the analysis of an individual account holder’s statistical information. Previously, the software used for this analysis was driven by statistics.

    Banks and financial providers are increasingly transitioning to software powered by Artificial Neural Networks. This shift enables a more comprehensive analysis of the applicant and their behavior.

    As a result, the information presented to the bank or financial provider is more accurate and valuable. This, in turn, allows for better-informed decisions that are more suitable for both the institution and the applicant. According to Forbes, many mortgage lenders anticipate a surge in the adoption of systems powered by Artificial Neural Networks in the coming years.

    Tesla has been making promises regarding its Full Self-Driving (FSD) capability for some time, even selling a beta version to customers willing to purchase the software. FSD is marketed as a more advanced option compared to its Autopilot and Enhanced Autopilot driver assistance features.

    Often characterized as the more sophisticated but still experimental component of Tesla’s driver assistance lineup, FSD includes what the company refers to as Autosteer on City Streets along with Traffic and Stop Sign Control.

    The most recent update, version 12.1.2, stands out from earlier iterations due to one significant change.

    “FSD Beta v12 enhances the city-streets driving technology by implementing a single, comprehensive neural network trained using millions of video clips, thus replacing over 300k lines of dedicated C++ code,” Tesla noted in its release documentation.

    Neural networks, commonly known as artificial neural networks (ANNs), are generally described as a form of machine learning technology that improves its efficiency and accuracy through training data over time. In Tesla’s application, these neural networks have been educated using actual video footage to make decisions instead of relying on extensive lines of code.

    The introduction of neural networks in this FSD beta update marks a new direction for the automaker, which has shifted to a vision-exclusive method for its software and sensor configuration in recent years, moving away from the combination of vision, radar, and lidar used by competitors working on autonomous technologies.

    This transition to a neural network-centric approach in FSD beta reinforces Tesla’s commitment to a vision-only sensor setup, which helps clarify the decision to eliminate other sensors a couple of years back.

    The efficacy of the latest beta version in delivering enhancements remains uncertain, but numerous overarching questions still linger regarding FSD.

    For example, it hasn’t become any clearer over time to pinpoint exactly what Tesla envisions FSD will ultimately provide.

    “Full autonomy will depend on achieving reliability that far surpasses human drivers, as evidenced by billions of miles of driving experience, along with obtaining regulatory approval, which may vary in timing by region,” Tesla states concerning its three systems, while deliberately avoiding the SAE level classification.

    Previously, Tesla has informed California regulators that FSD’s capabilities do not exceed SAE Level 2.

    If this still holds true, it makes sense from a regulatory standpoint, as SAE Level 3, often defined as systems allowing the driver to disengage from active monitoring, are currently allowed only in a select few states. This has already resulted in considerable challenges for European and Japanese automakers who have implemented such systems in other markets but cannot do so across all states in the U.S.

    These SAE Level 3 systems permit drivers to look away from the road for extended periods, enabling them to read, watch videos, or respond to emails—capabilities that FSD does not currently permit.

    “Always keep in mind that Full Self-Driving (Beta) does not make Model Y autonomous and necessitates that the driver remains fully attentive, ready to act instantly at any moment,” Tesla clarifies on its site.

    If FSD were to suddenly acquire the capability to function for hours without the need for driver intervention or even attention to external conditions, Tesla could face substantial regulatory challenges in the majority of U.S. states and would have to acknowledge it as a Level 3 system.

    A more pressing concern is that Tesla has spent five years refining what still appears to be a Level 2 system without officially labeling it as such, while other manufacturers, including Mercedes-Benz, have already begun deploying SAE Level 3 systems in select U.S. states as well as abroad.

    Tesla has also not disclosed any developments regarding SAE Level 4 robotaxi technology, which it once aimed to achieve, but which has already seen operational rollouts in various U.S. cities by other companies, alongside some setbacks and controversies over the past year.

    It’s important to note that all these Level 3 and Level 4 systems utilize more than just vision, incorporating a variety of radar and lidar sensors in addition to cameras.

    The future evolution of FSD into a Level 3 system remains uncertain in the coming years, especially as regulators in individual states continue to be cautious about such systems from other manufacturers.

    It’s time to explore again how Tesla plans to execute FSD. Once more, a thank you to SETI Park on X for their outstanding reporting on Tesla’s patents.

    This time, the focus is on Tesla developing a “universal translator” for its AI, which enables its FSD and other neural networks to seamlessly adjust to various hardware systems.

    This translation layer will let a complex neural network—such as FSD—function on virtually any platform that fulfills its basic requirements. This will significantly shorten training times, accommodate platform-specific limitations, and enhance both decision-making and learning speed.

    Let’s examine the main points of the patents and simplify them as much as possible. This latest patent is likely how Tesla plans to apply FSD in non-Tesla vehicles, Optimus, and other devices.

    Decision-Making

    Consider a neural network as a mechanism for making decisions. However, constructing one also involves making a series of choices regarding its design and data processing techniques. Think of it like selecting the right ingredients and culinary methods for a complicated recipe. These selections, known as “decision points,” are vital to how effectively the neural network operates on a particular hardware platform.

    To automate these choices, Tesla has created a system akin to a “run-while-training” neural network. This clever system evaluates the hardware’s capabilities and modifies the neural network in real-time, guaranteeing peak performance regardless of the platform.

    Constraints

    Every hardware platform has its own limitations—such as processing capabilities, memory size, and supported instructions. These limitations serve as “constraints” that determine how the neural network can be set up. Picture it like attempting to bake a cake in a small kitchen with a limited oven and counter space. You must adjust your recipe and methods to suit the constraints of your equipment or environment.

    Tesla’s system automatically detects these constraints, enabling the neural network to function within the hardware’s limits. Consequently, FSD could be transferred between vehicles and quickly adapt to a new context.

    Now, let’s outline some of the essential decision points and constraints involved:

    Data Layout: Neural networks handle extensive amounts of data. The way this data is organized in memory (the “data layout”) greatly influences performance. Different hardware setups may favor distinct layouts. For instance, some may operate more efficiently with data arranged in the NCHW format (batch, channels, height, width), while others may prefer NHWC (batch, height, width, channels). Tesla’s system autonomously chooses the best layout depending on the target hardware.

    Algorithm Selection: Numerous algorithms can be employed for functions within a neural network, including convolution, which is vital for image processing. Some algorithms, like the Winograd convolution, offer faster processing but may need specific hardware support. Others, such as Fast Fourier Transform (FFT) convolution, are more flexible but could be slower. Tesla’s system smartly selects the optimal algorithm according to the capabilities of the hardware.

    Hardware Acceleration: Contemporary hardware often comes with specialized processors intended to boost the speed of neural network tasks. These include Graphics Processing Units (GPUs) and Tensor Processing Units (TPUs). Tesla’s system detects and leverages these accelerators, maximizing performance on the specific platform.

    Satisfiability

    To discover the ideal configuration for a specific platform, Tesla utilizes a “satisfiability solver.” This powerful tool, particularly a Satisfiability Modulo Theories (SMT) solver, functions like an advanced puzzle-solving mechanism. It translates the neural network’s requirements and the hardware’s limitations into logical formulas and searches for a solution that meets all constraints. Imagine it as assembling puzzle pieces once the borders (constraints) have been established.

    Here’s the process, step-by-step:

    Define the Problem: The system converts the needs of the neural network and the constraints of the hardware into a series of logical statements. For instance, “the data layout needs to be NHWC” or “the convolution algorithm must be compatible with the GPU.”

    Search for Solutions: The SMT solver navigates through the extensive range of potential configurations, employing logical reasoning to dismiss invalid options. It systematically experiments with various combinations of settings, such as adjusting data layouts, choosing algorithms, and enabling hardware acceleration.

    Find Valid Configurations: The solver determines configurations that comply with all constraints. These represent possible solutions to the “puzzle” of efficiently running the neural network on the selected hardware.

    Optimization

    Identifying a working configuration is just one part of the equation; pinpointing the optimal configuration is the true challenge. This involves optimizing various performance metrics, such as:

    Inference Speed: The rate at which the network processes data and renders decisions. This aspect is crucial for real-time functionalities like FSD.

    Power Consumption: This refers to the energy utilized by the network. It is crucial to optimize power consumption to extend battery life in both electric vehicles and robots.

    Memory Usage: This indicates the amount of memory needed to store the network along with its data. Reducing memory usage is particularly vital for devices with limited resources.

    Accuracy: It is critical to ensure that the network retains or enhances its accuracy on the new platform for the sake of safety and reliability.

    Tesla’s system assesses potential configurations using these metrics, choosing the one that provides the best overall performance.

    Translation Layer vs Satisfiability Solver: It’s essential to differentiate between the “translation layer” and the satisfiability solver. The translation layer encompasses the entire adaptation process, managing components that evaluate the hardware, set the constraints, and call upon the SMT solver. The solver is a specific tool employed by the translation layer to discover valid configurations. You can think of the translation layer as the conductor of an orchestra, whereas the SMT solver is one of the instruments playing a key role in the harmonious adaptation of AI.

    Simple Terms: Picture having a complicated recipe (the neural network) and wanting to prepare it in various kitchens (hardware platforms). Some kitchens have a gas stove, while others use electricity; some feature a spacious oven, and others only have a small one. Tesla’s system serves as a master chef, adjusting the recipe and techniques to best suit each kitchen, ensuring a delectable meal (efficient AI) regardless of the cooking environment.

    What Does This Mean? To summarize and contextualize this for Tesla—there’s a lot to it. Essentially, Tesla is developing a translation layer capable of adapting FSD for any platform that meets the minimum requirements.

    This implies that Tesla can quickly enhance the rollout of FSD across new platforms while identifying the optimal configurations to maximize both decision-making speed and energy efficiency across those platforms.

    Overall, Tesla is gearing up to license FSD, indicating an exciting future. This isn’t limited to vehicles; don’t forget about Tesla’s humanoid robot, Optimus, which also operates on FSD. FSD itself may represent a highly adaptable vision-based AI.

    What Tesla is Changing to Improve Sentry Mode Efficiency: Recently, Tesla implemented power efficiency upgrades for the Sentry Mode feature of the Cybertruck with software update 2024.38.4. These upgrades significantly enhance the vehicle’s power consumption while Sentry Mode is active.

    We now have uncovered more details on how Tesla accomplished such substantial reductions in power consumption, which is estimated to be 40%.

    Tesla implemented architectural changes regarding how it processes and analyzes video—optimizing the allocation of tasks among different components. Although the Cybertruck is the first to enjoy these advancements, Tesla intends to roll out these upgrades to other vehicles in the future.

    Sentry Mode Power Consumption: Tesla vehicles are equipped with two primary computers: the MCU (Media Control Unit), which drives the vehicle’s infotainment system, and the FSD computer, responsible for Autopilot and FSD functionalities. Both computers remain active and powered whenever the vehicle is awake, drawing around 250-300 watts.

    Generally, this power is only utilized when the vehicle is awake or in motion. This is not a major issue as the car automatically enters sleep mode and deactivates its computers after approximately 15 minutes of inactivity. However, the larger concern is that these computers must stay powered on when Sentry Mode is engaged, resulting in a continuous 250-watt draw during this time.

    Interconnected System: Currently, the vehicle’s cameras are linked to the FSD computer, which in turn connects to the MCU, followed by the USB ports. Due to this interconnected structure, everything must remain powered. Footage needs to be streamed from the FSD computer to the MCU, where tasks like motion detection take place. The data then has to be compressed before it can finally be recorded on the USB drive. This lengthy process necessitates that multiple computers remain powered to record and save live video.

    Architectural Changes: Tesla is implementing architectural modifications to mitigate the high power consumption of Sentry Mode by redistributing tasks among the vehicle’s computers. By reallocating motion detection and possibly compression tasks to the FSD computer, Tesla can now allow the MCU to remain in sleep mode. The MCU is still necessary to transfer the video to the USB drive, but Tesla can wake it up only when it is required.

    For example, while the FSD computer will still manage the connection to the vehicle’s cameras, it will also be responsible for detecting motion. When a Sentry event is triggered, it can activate the MCU to save the data to the USB drive and then return it to sleep mode.

    This strategy ensures that the MCU does not stay continuously powered for video analysis and compression, activating only when it is needed to manage data.

    Processor Isolation & Task Allocation

    Tesla’s existing architecture keeps the Autopilot Unit (APU) distinct from the MCU. This separation is motivated by several factors, with safety being the primary concern. The MCU can be rebooted independently during a drive without affecting the APU and crucial safety features.

    Furthermore, isolating the APU from the MCU allows tasks that are better suited for each component—such as processing and image transcoding—to be assigned to the appropriate processing unit. This ensures that both the APU and MCU operate at their peak power and performance levels, promoting more efficient energy consumption.

    Kernel-Level Power Management

    Tesla is focusing on more than just full self-driving (FSD) enhancements or new vehicle visualization updates; they are also optimizing the core kernel of the operating system. Though not extensively employed, Tesla minimizes the clock speed of both the MCU and APU, which leads to lower power consumption and reduced heat output.

    Moreover, other kernel enhancements and programming techniques, similar to those Tesla applies to boost the efficiency of its FSD models, contribute to the overall improved efficiency of the vehicles.

    Additional Benefits

    Given that Tesla vehicles come equipped with a Dashcam that handles video processing, it’s likely that these extra power savings will be observed when the vehicle is operational. This could also influence other functionalities, such as Tesla’s Summon Standby feature, which keeps the vehicle awake and processing video, allowing users near-instant access to the Summon feature of the vehicle.

    Roll Out to Other Vehicles

    Although the Cybertruck was the first to benefit from these power enhancements in Sentry Mode, it has been indicated that these improvements will be extended to other vehicles as well. Tesla is initially rolling out these changes with the Cybertruck, taking advantage of its smaller user base for preliminary testing before broadening the distribution to other models.

    USB Port Power Management

    To further enhance energy conservation and reduce waste, Tesla now shuts down USB ports even when Sentry Mode is activated. This adjustment has affected numerous users who depend on 12v sockets or USB ports for powering accessories like small vehicle refrigerators.

    It remains unclear if these modifications to Sentry Mode directly influence this change or if the power to the 12v outlets was turned off solely due to safety considerations.

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