News
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.
News
Tesla intertwines FSD with in-house Insurance for attractive incentive
Every mile logged under FSD now carries a documented financial value—lower risk, lower cost—based on Tesla’s internal driving data rather than external crash statistics alone.
Tesla intertwined its Full Self-Driving (Supervised) suite with its in-house Insurance initiative in an effort to offer an attractive incentive to drivers.
Tesla announced that its new Safety Score 3.0 will automatically have a perfect score of 100 with every mile driven with Full Self-Driving (Supervised) enabled.
The change is designed to boost customers’ average safety scores and deliver noticeably lower monthly premiums.
The move marks the clearest link yet between Tesla’s autonomous driving technology and its proprietary insurance product. Tesla Insurance already relies on real-time vehicle data—such as acceleration, braking, following distance, and speed—to calculate a Safety Score between 0 and 100. Higher scores have long translated into cheaper rates.
Under the previous system, however, even brief manual interventions could drag down the average, frustrating owners who rely heavily on FSD. Version 3.0 eliminates that penalty for supervised autonomous miles, effectively treating FSD-driven segments as the safest possible driving behavior.
The incentive is immediate and financial. Drivers who keep FSD engaged for the majority of their trips will see their overall score rise, potentially shaving hundreds of dollars off annual premiums.
Tesla framed the update as a direct response to customer feedback, many of whom had complained that the old scoring model punished the very behavior it was meant to encourage.
For now, the program applies only to new policies in six states: Indiana, Tennessee, Texas, Arizona, Virginia, and Illinois.
Existing policyholders are not yet included, a point that drew swift questions from the Tesla community. Many owners in other states, including California and Georgia, expressed hope that the benefit would expand nationwide soon.
The announcement arrives as Tesla continues to roll out FSD Supervised updates and push for regulatory approval of more advanced autonomy. By tying insurance savings directly to FSD usage, the company is putting its own actuarial weight behind the technology’s safety claims.
Every mile logged under FSD now carries a documented financial value—lower risk, lower cost—based on Tesla’s internal driving data rather than external crash statistics alone.
Tesla has not disclosed exact premium reductions or the full rollout timeline beyond the six launch states.
Still, the message is clear: the more drivers trust FSD Supervised, the more Tesla Insurance will reward them. In an era when legacy insurers remain cautious about autonomous tech, Tesla is betting that its own data will prove the safest miles are the ones driven hands-free.
Elon Musk
Tesla finalizes AI5 chip design, Elon Musk makes bold claim on capability
The Tesla CEO’s words mark a strategic shift. Tesla has long emphasized software-hardware co-design, squeezing maximum performance from every transistor. Musk previously described AI5 as optimized for edge inference in both Robotaxi and Optimus.
Tesla has finalized its chip design for AI5, as Elon Musk confirmed today that the new chip has reached the tape-out stage, the final step before mass production.
But in a brief reply on X, Musk clarified Tesla’s AI hardware roadmap, essentially confirming that the new chip will not be utilized for being “enough to achieve much better than human safety for FSD.”
He said that AI4 is enough to do that.
Instead, the AI5 chip will be focused on Tesla’s big-time projects for the future: Optimus and supercomputer clusters.
Musk thanked TSMC and Samsung for production support, noting that AI5 could become “one of the most produced AI chips ever.” Yet, the key pivot came in his direct answer: vehicles no longer need the bleeding-edge silicon.
And thank you to @TaiwanSemi_TSC and @Samsung for your support in bringing this chip to production! It will be one of most produced AI chips ever.
— Elon Musk (@elonmusk) April 15, 2026
Existing AI4 hardware, which is already deployed in hundreds of thousands of HW4-equipped Teslas, delivers safety metrics superior to human drivers for Full Self-Driving. AI5 will instead accelerate Optimus robot development and massive Dojo-style training clusters.
The Tesla CEO’s words mark a strategic shift. Tesla has long emphasized software-hardware co-design, squeezing maximum performance from every transistor. Musk previously described AI5 as optimized for edge inference in both Robotaxi and Optimus.
Now, with AI4 proving sufficient, the company avoids costly retrofits across its fleet while redirecting next-generation compute toward higher-value applications: dexterous robots and exponential training scale.
But is it reasonable to assume AI4 enables unsupervised self-driving? Yes, but with important caveats.
On the hardware side, the claim is credible. Tesla’s FSD stack runs end-to-end neural networks trained on billions of miles of real-world data. Internal safety data reportedly shows AI4-equipped vehicles already outperforming average human drivers by a significant margin in controlled metrics (collision avoidance, reaction time, edge-case handling).
Dual-redundant AI4 chips provide ample headroom for the driving task, leaving bandwidth for future model improvements without new silicon. Musk’s assertion aligns with Tesla’s pattern of over-provisioning compute early, then optimizing ruthlessly, exactly as HW3 once sufficed before HW4 scaled further.
Optimus and our supercomputer clusters.
AI4 is enough to achieve much better than human safety for FSD.
— Elon Musk (@elonmusk) April 15, 2026
Unsupervised autonomy, meaning Level 4 or higher, is not solely a compute problem. Regulatory approval remains the primary gate.
Even if AI4 achieves “much better than human” safety statistically, agencies like the NHTSA demand exhaustive validation, liability frameworks, and public trust.
Tesla’s supervised FSD has shown rapid gains in recent versions, yet real-world edge cases, like construction zones, emergency vehicles, and adverse weather, still require driver intervention in many jurisdictions. Competitors like Waymo operate limited unsupervised fleets, but only in geofenced areas with extensive mapping. Tesla’s vision-only, fleet-scale approach is more ambitious—and harder to certify globally.
In short, Musk’s post is both pragmatic and bullish. AI4 is likely capable of unsupervised FSD from a technical standpoint. Whether regulators and consumers agree, and how quickly, will determine if Tesla’s bet pays off.
The company’s capital-efficient path keeps existing cars relevant while pouring future compute into robots. If the safety data holds, unsupervised autonomy could arrive sooner than many expect.
Elon Musk
Elon Musk signals expansion of Tesla’s unique side business
Long envisioning the Tesla Diner as more than a charging stop, Musk has clearly adopted the idea that the Supercharger and Restaurant combo is a good thing for the company to have. It’s a blend of classic American drive-in culture with futuristic Tesla flair, complete with a 1950s-inspired design, movie screens, and on-site dining.
Elon Musk has signaled an expansion of Tesla’s unique side business, something that really has nothing to do with cars or spaceships, but fans of the company have truly adopted it as just another one of its awesome ventures.
Musk confirmed on Wednesday that Tesla would build a new Diner location in Palo Alto, Northern California. After hinting last October that it “probably makes sense to open one near our Giga Texas HQ in Austin and engineering HQ in Palo Alto,” it seems one of those locations is being set into motion.
Sure
— Elon Musk (@elonmusk) April 15, 2026
Long envisioning the Tesla Diner as more than a charging stop, Musk has clearly adopted the idea that the Supercharger and Restaurant combo is a good thing for the company to have. It’s a blend of classic American drive-in culture with futuristic Tesla flair, complete with a 1950s-inspired design, movie screens, and on-site dining.
He first floated broader expansion plans shortly after the LA opening in July 2025, noting that if the prototype succeeded, Tesla would roll out similar venues in major cities worldwide and along long-distance Supercharger routes.
Earlier hints included a confirmed second site at Starbase in Texas, tied to SpaceX operations, underscoring the Diner’s role in enhancing Tesla’s ecosystem behind vehicles.
The Los Angeles location on Santa Monica Boulevard in West Hollywood has served as a high-profile test case. Opened in July 2025 at 7001 Santa Monica Blvd., it features the world’s largest urban Supercharging station with 80 V4 stalls open to all NACS-compatible EVs, over 250 dining seats, rooftop views, and 24/7 service.
The retro-futuristic building replaced a former Shakey’s and quickly became a destination. Tesla reported selling 50,000 burgers in the first 72 days—an average of over 700 daily—drawing crowds with Cybertruck-shaped packaging, breakfast extensions until 2 p.m., and movie screenings.
Palo Alto stands out as a logical next step for several reasons. As Tesla’s longstanding engineering headquarters in the heart of Silicon Valley, the city is home to thousands of Tesla employees, engineers, and executives who could benefit from a convenient, branded gathering spot.
The area boasts high EV adoption rates, dense tech talent, and heavy traffic along key corridors, making a large Supercharger-diner an ideal fit for both daily commuters and long-haul travelers.
Proximity to Stanford University and the innovation ecosystem would amplify its appeal, potentially serving as a showcase for Tesla’s vision of integrated mobility and lifestyle experiences. It could be a great way for Tesla to recruit new talent from one of the country’s best universities.
If Tesla and Musk decide to move forward with a Palo Alto diner, it would build directly on the LA prototype’s momentum while addressing Musk’s earlier calls for expansion near core Tesla hubs.
Whether it materializes as a full confirmation or evolves from these hints remains to be seen, but the pattern is clear: Tesla is testing ways to make charging stops memorable. For EV drivers and enthusiasts alike, a Silicon Valley outpost could blend cutting-edge tech with nostalgic comfort, further embedding Tesla into everyday culture. As Musk’s comments suggest, the future of the Diner looks promising.


