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How will Tesla Version 8 compare to current Autopilot in the real world?

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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.

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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.

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Traffic Aware Cruise Control

Tesla-Autopilot-Traffic-Rain

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.

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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.

I'm friendly. You can email me. gene@teslarati.com

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Nvidia CEO Jensen Huang explains difference between Tesla FSD and Alpamayo

“Tesla’s FSD stack is completely world-class,” the Nvidia CEO said.

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Credit: Grok Imagine

NVIDIA CEO Jensen Huang has offered high praise for Tesla’s Full Self-Driving (FSD) system during a Q&A at CES 2026, calling it “world-class” and “state-of-the-art” in design, training, and performance. 

More importantly, he also shared some insights about the key differences between FSD and Nvidia’s recently announced Alpamayo system. 

Jensen Huang’s praise for Tesla FSD

Nvidia made headlines at CES following its announcement of Alpamayo, which uses artificial intelligence to accelerate the development of autonomous driving solutions. Due to its focus on AI, many started speculating that Alpamayo would be a direct rival to FSD. This was somewhat addressed by Elon Musk, who predicted that “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.”

During his Q&A, Nvidia CEO Jensen Huang was asked about the difference between FSD and Alpamayo. His response was extensive:

“Tesla’s FSD stack is completely world-class. They’ve been working on it for quite some time. It’s world-class not only in the number of miles it’s accumulated, but in the way it’s designed, the way they do training, data collection, curation, synthetic data generation, and all of their simulation technologies. 

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“Of course, the latest generation is end-to-end Full Self-Driving—meaning it’s one large model trained end to end. And so… Elon’s AD system is, in every way, 100% state-of-the-art. I’m really quite impressed by the technology. I have it, and I drive it in our house, and it works incredibly well,” the Nvidia CEO said. 

Nvidia’s platform approach vs Tesla’s integration

Huang also stated that Nvidia’s Alpamayo system was built around a fundamentally different philosophy from Tesla’s. Rather than developing self-driving cars itself, Nvidia supplies the full autonomous technology stack for other companies to use.

“Nvidia doesn’t build self-driving cars. We build the full stack so others can,” Huang said, explaining that Nvidia provides separate systems for training, simulation, and in-vehicle computing, all supported by shared software.

He added that customers can adopt as much or as little of the platform as they need, noting that Nvidia works across the industry, including with Tesla on training systems and companies like Waymo, XPeng, and Nuro on vehicle computing.

“So our system is really quite pervasive because we’re a technology platform provider. That’s the primary difference. There’s no question in our mind that, of the billion cars on the road today, in another 10 years’ time, hundreds of millions of them will have great autonomous capability. This is likely one of the largest, fastest-growing technology industries over the next decade.”

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He also emphasized Nvidia’s open approach, saying the company open-sources its models and helps partners train their own systems. “We’re not a self-driving car company. We’re enabling the autonomous industry,” Huang said.

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Elon Musk confirms xAI’s purchase of five 380 MW natural gas turbines

The deal, which was confirmed by Musk on X, highlights xAI’s effort to aggressively scale its operations.

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Credit: xAI/X

xAI, Elon Musk’s artificial intelligence startup, has purchased five additional 380 MW natural gas turbines from South Korea’s Doosan Enerbility to power its growing supercomputer clusters. 

The deal, which was confirmed by Musk on X, highlights xAI’s effort to aggressively scale its operations.

xAI’s turbine deal details

News of xAI’s new turbines was shared on social media platform X, with user @SemiAnalysis_ stating that the turbines were produced by South Korea’s Doosan Enerbility. As noted in an Asian Business Daily report, Doosan Enerbility announced last October that it signed a contract to supply two 380 MW gas turbines for a major U.S. tech company. Doosan later noted in December that it secured an order for three more 380 MW gas turbines.

As per the X user, the gas turbines would power an additional 600,000+ GB200 NVL72 equivalent size cluster. This should make xAI’s facilities among the largest in the world. In a reply, Elon Musk confirmed that xAI did purchase the turbines. “True,” Musk wrote in a post on X. 

xAI’s ambitions 

Recent reports have indicated that xAI closed an upsized $20 billion Series E funding round, exceeding the initial $15 billion target to fuel rapid infrastructure scaling and AI product development. The funding, as per the AI startup, “will accelerate our world-leading infrastructure buildout, enable the rapid development and deployment of transformative AI products.”

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The company also teased the rollout of its upcoming frontier AI model. “Looking ahead, Grok 5 is currently in training, and we are focused on launching innovative new consumer and enterprise products that harness the power of Grok, Colossus, and 𝕏 to transform how we live, work, and play,” xAI wrote in a post on its website. 

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Elon Musk’s xAI closes upsized $20B Series E funding round

xAI announced the investment round in a post on its official website. 

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Credit: xAI

xAI has closed an upsized $20 billion Series E funding round, exceeding the initial $15 billion target to fuel rapid infrastructure scaling and AI product development. 

xAI announced the investment round in a post on its official website. 

A $20 billion Series E round

As noted by the artificial intelligence startup in its post, the Series E funding round attracted a diverse group of investors, including Valor Equity Partners, Stepstone Group, Fidelity Management & Research Company, Qatar Investment Authority, MGX, and Baron Capital Group, among others. 

Strategic partners NVIDIA and Cisco Investments also continued support for building the world’s largest GPU clusters.

As xAI stated, “This financing will accelerate our world-leading infrastructure buildout, enable the rapid development and deployment of transformative AI products reaching billions of users, and fuel groundbreaking research advancing xAI’s core mission: Understanding the Universe.”

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xAI’s core mission

Th Series E funding builds on xAI’s previous rounds, powering Grok advancements and massive compute expansions like the Memphis supercluster. The upsized demand reflects growing recognition of xAI’s potential in frontier AI.

xAI also highlighted several of its breakthroughs in 2025, from the buildout of Colossus I and II, which ended with over 1 million H100 GPU equivalents, and the rollout of the Grok 4 Series, Grok Voice, and Grok Imagine, among others. The company also confirmed that work is already underway to train the flagship large language model’s next iteration, Grok 5. 

“Looking ahead, Grok 5 is currently in training, and we are focused on launching innovative new consumer and enterprise products that harness the power of Grok, Colossus, and 𝕏 to transform how we live, work, and play,” xAI wrote. 

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