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How will Tesla Version 8 compare to current Autopilot in the real world?
Tesla’s upcoming Version 8 software will be the company’s most significant Autopilot upgrade since its October 2014 initial release, but how will these updates compare to current Autopilot behavior in the real world?
This will be the first time the company will switch from using the vehicle’s front-facing camera as the core hardware responsible for visual image recognition, to radar technology which will now become the primary sensor used in creating a virtual picture of the vehicle’s surroundings.
With these improvements, to be rolled out via an over-the-air software update in the coming weeks, Model S equipped with the Autopilot hardware suite and Model X should theoretically be able to handle emergency braking situations with more precision, provide a smoother Traffic Aware Cruise Control (TACC) experience, take highway exits on its own, and provide drivers and passengers with an overall safer experience.
Let’s take a look at each of these features and see how Autopilot in Version 8 will differ from current Version 7 capabilities.
Automatic Emergency Braking
Following the much publicized death of Joshua Brown after his Model S crashed into the side of a tractor trailer while driving on Autopilot, reliability of Autopilot’s Automatic Emergency Braking (AEB) feature was immediately put to question. Tesla released a statement stating that the high, white side of the tractor trailer, combined with a radar signature that would have looked very similar to an overhead sign, caused automatic braking not to fire. “Since January 2016, Autopilot activates automatic emergency braking in response to any interruption of the ground plane in the path of the vehicle that cross-checks against a consistent radar signature,” said Tesla.
Spy shots taken from the Naval Air Station reveal Tesla was testing and calibrating its AEB system this past summer. But despite the tests which seemingly show a Model S automatically braking in a staged collision event, Tesla has been overly cautious when it comes to activation of its AEB feature. AEB is reliant on imagery received from its front-facing camera, and supplemented by radar input, to decide on the degree of confidence that would trigger a braking event.
Some Tesla owners have even taken it upon themselves to stage scenarios that would seemingly trigger the AEB response of the vehicle, but to no avail leaving further mystery as to how AEB works.
The current Autopilot system under Version 7 is limited in its ability to reliably detect people or pinpoint false positives such as reflective objects that may appear larger than they are. Tesla uses the concave bottom of a soda can as an example. When the radar signal is reflected back from the can’s bottom dish-shaped surface, the reflected signal is amplified to many times its actual size leading the radar to believe there’s a large object before it. Because of that, programming the AEB system to suddenly engage could lead to a dangerous situation so Tesla decided to limit the scenarios that could actually trigger an automatic emergency braking response.
However, Version 8 will combine the power of fleet learning with “radar snapshots” to improve the vehicle’s ability to more accurately depict the circumstances of an event. In other words, we can expect Autopilot under Version 8 to have a much higher degree of confidence when it comes to engaging automatic emergency braking. Tesla CEO Elon Musk believes this set up will provide safety improvements by a factor of three over existing Autopilot.
Traffic Aware Cruise Control
Beyond being able to track a vehicle that’s directly in front of the car, Version 8 of Autopilot will also be able to see the vehicle ahead of that. Tesla describes this update as follows: Tesla will also be able to bounce the radar signal under a vehicle in front – using the radar pulse signature and photon time of flight to distinguish the signal – and still brake even when trailing a car that is opaque to both vision and radar. The car in front might hit the UFO in dense fog, but the Tesla will not.
The improvement will lead to smoother braking events when TACC is engaged since Autopilot will no longer solely rely on the actions from the vehicle before it. If a hard braking event happened in front of the vehicle that Autopilot is immediately tracking, Version 8 will be able to identify it and slow the Model S (or Model X) even before the vehicle directly ahead may have applied the brakes.
The following video captures an incident whereby the vehicle being tracked by Version 7 of Autopilot could not see the hard braking event that took place two cars ahead. TACC seemingly did not have enough time to stop the Model S.
Being able to see two cars ahead in Version 8 will provide a smoother TACC experience and increased safety.
Improved Auto Lane Change and Freeway Exiting
What we’re particularly excited about is the new feature in Version 8.1 that will allow an Autopilot-equipped Model S and Model X to take highway exits using the onboard navigation system.
Currently, Version 7 of Autopilot is capable of handling lane changes when the driver explicitly uses the turn signal stalk. Signaling left and the vehicle will make a left lane change, and vice versa. However with the ability to punch in a destination through Tesla Nav and have the vehicle assist with freeway exiting, assuming that’s part of the route, in our minds, Tesla is taking a critical step towards the ultimate goal of building fully autonomous self-driving vehicles. It’s a small step, but nonetheless it’s a notable step.
Photo credit: Rob M.
Full details of Tesla Version 8 can be found here.
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
