News
Elon Musk explains Tesla’s pure vision approach to Autopilot and Full Self-Driving
A recent set of updates from Elon Musk has revealed that Tesla is looking to eventually update its Autopilot and Full Self-Driving suite to a camera-based system. This means that in the future, Tesla’s all-electric vehicles would be navigating themselves and performing driver-assist functions without the use of components such as radar.
Musk’s update came as a response to a post from Tesla owner and FSD Beta user @WholeMarsBlog, who shared a clip of his Model 3 navigating away from a parking lot to its destination without input from its driver. In his response, Musk noted that FSD Beta V9.0, which has been highly-anticipated by the EV community, is almost ready.
Almost ready with FSD Beta V9.0. Step change improvement is massive, especially for weird corner cases & bad weather. Pure vision, no radar.
— Elon Musk (@elonmusk) April 9, 2021
Elaborating further, Musk explained that the V9.0 update should improve the FSD Beta’s performance in corner cases and bad weather, which remain challenging to the advanced driver-assist system today. But this was not all, as Musk noted that the update would be “pure vision, no radar.” When prodded further, the Tesla CEO admitted that Tesla eventually plans to get rid of radar altogether in its future vehicles.
Unsurprisingly, Musk’s statements about Tesla’s impending removal of radar attracted its own fair share of critics, many of whom argued that a pure vision approach is a step backward. This is especially notable as Tesla is already using fewer sensors for its driver-assist systems compared to competitors like Cruise and Waymo, both of whom rely on lidar and high-definition maps to navigate.
Musk responded to these concerns, highlighting that ultimately, vision has the potential to be far superior to radar.
Sensors are a bitstream and cameras have several orders of magnitude more bits/sec than radar (or lidar).
Radar must meaningfully increase signal/noise of bitstream to be worth complexity of integrating it.
As vision processing gets better, it just leaves radar far behind.
— Elon Musk (@elonmusk) April 10, 2021
“When radar and vision disagree, which one do you believe? Vision has much more precision, so better to double down on vision than do sensor fusion. Sensors are a bitstream and cameras have several orders of magnitude more bits/sec than radar (or lidar). Radar must meaningfully increase signal/noise of bitstream to be worth complexity of integrating it. As vision processing gets better, it just leaves radar far behind,” Musk explained.
Tesla’s approach to full self-driving is partly based on the notion that humans do 100% of their driving through vision alone, without any radar or lidar use. This was highlighted by Tesla executives since Autonomy Day back in 2019, when the company unveiled its custom FSD computer. As for concerns about whether cameras could provide the same level of safety as radar in detecting what is happening several cars ahead, Musk noted that there’s a high probability that vision could perform just as well.
These things are best thought of as probabilities. There are 5 forward-facing cameras. It is highly likely that at least one of them will see multiple cars ahead.
— Elon Musk (@elonmusk) April 10, 2021
“These things are best thought of as probabilities. There are 5 forward-facing cameras. It is highly likely that at least one of them will see multiple cars ahead,” Musk said.
Tesla is not the only company in the market that is looking into a vision-only approach. Last year, Intel Corp released a video of an autonomous car from MobilEye that was navigating around Jerusalem for about 20 minutes. Unlike other self-driving vehicles, MobilEye’s car was only equipped with a suite of cameras and nothing else. The brief video was impressive, showing the MobilEye autonomous car going through four-way intersections with no traffic lights, as well as inner-city lanes that required the vehicle to avoid pedestrians.
Don’t hesitate to contact us for news tips. Just send a message to tips@teslarati.com to give us a heads up.
Elon Musk
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
Tesla CEO Elon Musk has provided an updated estimate for the training data needed to achieve truly safe unsupervised Full Self-Driving (FSD).
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
10 billion miles of training data
Musk comment came as a reply to Apple and Rivian alum Paul Beisel, who posted an analysis on X about the gap between tech demonstrations and real-world products. In his post, Beisel highlighted Tesla’s data-driven lead in autonomy, and he also argued that it would not be easy for rivals to become a legitimate competitor to FSD quickly.
“The notion that someone can ‘catch up’ to this problem primarily through simulation and limited on-road exposure strikes me as deeply naive. This is not a demo problem. It is a scale, data, and iteration problem— and Tesla is already far, far down that road while others are just getting started,” Beisel wrote.
Musk responded to Beisel’s post, stating that “Roughly 10 billion miles of training data is needed to achieve safe unsupervised self-driving. Reality has a super long tail of complexity.” This is quite interesting considering that in his Master Plan Part Deux, Elon Musk estimated that worldwide regulatory approval for autonomous driving would require around 6 billion miles.
FSD’s total training miles
As 2025 came to a close, Tesla community members observed that FSD was already nearing 7 billion miles driven, with over 2.5 billion miles being from inner city roads. The 7-billion-mile mark was passed just a few days later. This suggests that Tesla is likely the company today with the most training data for its autonomous driving program.
The difficulties of achieving autonomy were referenced by Elon Musk recently, when he commented on Nvidia’s Alpamayo program. As per Musk, “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.” These sentiments were echoed by Tesla VP for AI software Ashok Elluswamy, who also noted on X that “the long tail is sooo long, that most people can’t grasp it.”
News
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla emerged as one of the most recognized automakers at MotorTrend’s 2026 Software-Defined Vehicle (SDV) Innovator Awards.
As could be seen in a press release from the publication, two key Tesla employees were honored for their work on AI, autonomy, and vehicle software. MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla leaders and engineers recognized
The fourth annual SDV Innovator Awards celebrate pioneers and experts who are pushing the automotive industry deeper into software-driven development. Among the most notable honorees for this year was Ashok Elluswamy, Tesla’s Vice President of AI Software, who received a Pioneer Award for his role in advancing artificial intelligence and autonomy across the company’s vehicle lineup.
Tesla also secured recognition in the Expert category, with Lawson Fulton, a staff Autopilot machine learning engineer, honored for his contributions to Tesla’s driver-assistance and autonomous systems.
Tesla’s software-first strategy
While automakers like General Motors, Ford, and Rivian also received recognition, Tesla’s multiple awards stood out given the company’s outsized role in popularizing software-defined vehicles over the past decade. From frequent OTA updates to its data-driven approach to autonomy, Tesla has consistently treated vehicles as evolving software platforms rather than static products.
This has made Tesla’s vehicles very unique in their respective sectors, as they are arguably the only cars that objectively get better over time. This is especially true for vehicles that are loaded with the company’s Full Self-Driving system, which are getting progressively more intelligent and autonomous over time. The majority of Tesla’s updates to its vehicles are free as well, which is very much appreciated by customers worldwide.
Elon Musk
Judge clears path for Elon Musk’s OpenAI lawsuit to go before a jury
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder.
A U.S. judge has ruled that Elon Musk’s lawsuit accusing OpenAI of abandoning its founding nonprofit mission can proceed to a jury trial.
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder. These claims are directly opposed by OpenAI.
Judge says disputed facts warrant a trial
At a hearing in Oakland, U.S. District Judge Yvonne Gonzalez Rogers stated that there was “plenty of evidence” suggesting that OpenAI leaders had promised that the organization’s original nonprofit structure would be maintained. She ruled that those disputed facts should be evaluated by a jury at a trial in March rather than decided by the court at this stage, as noted in a Reuters report.
Musk helped co-found OpenAI in 2015 but left the organization in 2018. In his lawsuit, he argued that he contributed roughly $38 million, or about 60% of OpenAI’s early funding, based on assurances that the company would remain a nonprofit dedicated to the public benefit. He is seeking unspecified monetary damages tied to what he describes as “ill-gotten gains.”
OpenAI, however, has repeatedly rejected Musk’s allegations. The company has stated that Musk’s claims were baseless and part of a pattern of harassment.
Rivalries and Microsoft ties
The case unfolds against the backdrop of intensifying competition in generative artificial intelligence. Musk now runs xAI, whose Grok chatbot competes directly with OpenAI’s flagship ChatGPT. OpenAI has argued that Musk is a frustrated commercial rival who is simply attempting to slow down a market leader.
The lawsuit also names Microsoft as a defendant, citing its multibillion-dollar partnerships with OpenAI. Microsoft has urged the court to dismiss the claims against it, arguing there is no evidence it aided or abetted any alleged misconduct. Lawyers for OpenAI have also pushed for the case to be thrown out, claiming that Musk failed to show sufficient factual basis for claims such as fraud and breach of contract.
Judge Gonzalez Rogers, however, declined to end the case at this stage, noting that a jury would also need to consider whether Musk filed the lawsuit within the applicable statute of limitations. Still, the dispute between Elon Musk and OpenAI is now headed for a high-profile jury trial in the coming months.
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
