Tesla may be targeting the release of FSD Beta 10.8 on Tuesday together with the company’s fun Holiday Update, but this has not stopped the EV maker from releasing FSD Beta 10.7 this past weekend nonetheless. And despite its impending quick replacement with v10.8, v10.7 seems to include a number of key updates that make the advanced driver-assist system smoother to operate.
Immediately recognizable from v10.7’s detailed Release Notes was that vehicles could now react to things quite a bit faster. With v10.7, FSD Beta would also be less likely to slow down due to bad readings from other cars and objects on the road. Also, the aggressiveness of FSD Beta seems to have been toned down to some degree, with the system now rolling and stopping smoothly for jaywalkers, instead of slamming on the brakes.
Release notes for #FSDBeta V10.7 pic.twitter.com/BFFiQh7iww
— Dirty Tesla (@DirtyTesLa) December 19, 2021
Perhaps most interestingly, however, was that FSD Beta 10.7 also effectively enables one-pedal driving by expanding the use of vehicles’ regenerative braking systems. This should make stops smoother while keeping the physical brakes as infrequently used as possible. This update would likely be a welcome change, as conversations in the r/TeslaMotors subreddit among FSD Beta testers suggest that some users are annoyed by the system’s use of physical brakes in past iterations.
The following are the specific Release Notes for Tesla’s FSD Beta 10.7.
FSD Beta v10.7 Release Notes
– Improved object attributes network to reduce false cut-in slowdowns by 50% and lane assignment error by 19%.
– Improved photon-to-control vehicle response latency by 20% on average.
– Expanded use of regenerative braking in Autopilot down to 0 mph for smoother stops and improved energy efficiency.
– Improved VRU (pedestrians, bicyclists, motorcycles, animals) lateral velocity 1 error by 4.9% by adding more auto-labeled and simulated training examples to the dataset.
– Reduced false slowdowns for crossing objects by improved velocity estimates for objects at the end of visibility.
– Reduced false slowdowns by adding geometric checks to cross-validate lane assignment of objects.
– Improved speed profile for unprotected left turns when visibility is low.
– Added more natural behavior to bias over bike lanes during right turns.
– Improved comfort when yielding to jaywalkers by better modeling of stopping region with soft and hard deadlines.
– Improved smoothness for merge control with better modeling of merge point and ghost objects positioned at the edge of visibility.
– Improved overall comfort by enforcing stricter lateral jerk bounds in trajectory optimizer.
– Improved short deadline lane changes through richer trajectory modeling.
– Improved integration between lead vehicle overtake and lane change gap selection.
– Updated trajectory line visualization.
Tesla FSD 10.8 plus holiday fun software release probably Tuesday
— Elon Musk (@elonmusk) December 18, 2021
While FSD Beta 10.7 seems quite impressive, Elon Musk has noted that v10.8 would probably be released this coming Tuesday, together with the company’s Holiday Update. Tesla’s Holiday Updates are typically comprised of fun additions to vehicles’ features such as games and tricks like the external boombox.
This time around, however, it appears that the company is ensuring that its Holiday Update brings more functionality to its ever-expanding group of FSD Beta testers. These include the capability of FSD Beta to work with other features such as Waypoints, a function that was confirmed by Musk on Twitter.
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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.