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Tesla Autopilot update for better speed limit sign recognition is coming soon
Tesla CEO Elon Musk fielded several requests to address Autopilot’s ability to determine speed limit signs accurately, and the accuracy of its map data.
Amid reports that Autopilot users are still experiencing inaccuracies with the software’s ability to accurately read speed limit signs, Musk reassured users over Twitter that improvements are of utmost priority and an update is coming soon.
In the past, Tesla vehicles have displayed issues with recognizing Speed Limits correctly. Researchers at McAfee Advanced Threat Research managed to trick Tesla’s speed limit recognition technologies in the past by adjusting the appearance of the number “3” on a 35 MPH speed limit sign. This adjustment tricked the Tesla into thinking the speed limit was 85 MPH.
Yes, this is a high priority
— Elon Musk (@elonmusk) May 8, 2020
Some owners on Tesla’s forums stated their vehicles had issues recognizing speed limit signs accurately. Sometimes, the car would not register a speed limit sign at all. The problem caused some owners to have their vehicles driving through zones at excessive speeds, causing a safety issue and risking them to receive a ticket.
One owner in the forum stated, “Was wondering why some speed limits signs are not recognized on my Tesla. Don’t need a ticket.”
It seems that some owners whose cars still utilize Mobileye and Hardware 1 are the only drivers whose vehicles recognize signs accurately the majority of the time. However, when Tesla and Mobileye ended a partnership in 2016, Tesla was forced to make its own software to recognize speed limits. Tesla vehicles manufactured after the partnership ended use GPS-based speed limit recognition and not camera-based identification.
Arguably one of the most substantial hurdles Tesla must jump through on its journey to autonomous driving features is the accuracy of sign recognition. Without the ability to read road signs and speed limits, the autonomous features are pointless because the vehicle will not function properly. Tesla’s Artificial Intelligence program is working diligently to improve the functionality of Autopilot, and it starts with accurate street sign recognition.
Coming soon
— Elon Musk (@elonmusk) May 8, 2020
When Tesla’s Head of AI Andrej Karpathy spoke about the processes of identifying street signs, he explained that the vehicles depend on code to recognize instructions. The issue with this is that many states utilize different words or layouts to describe the same action. For example, Karpathy stated Tesla holds the most extensive set of “Except Right Turn” signs in its database. These signs often say the same thing but are different sizes, fonts, or shapes, all of which are factors that can spell trouble for a software system.
The improvement of accurately recognizing signs will move Tesla closer to finishing its Full Self-Driving suite. After Tesla released the Stop Sign and Traffic Light Control feature, only City Driving remains on the list of FSD features that have yet to be unveiled. Recently, the company also published its safety statistics, marking Autopilot’s safest year to date. With added improvements over time, thanks to the contribution of data to the company’s Neural Network, Tesla can continue to improve upon its already impressive FSD performance.
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.”
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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
