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Tesla terminates employee and FSD Beta tester who shared drives on YouTube

Credit: AI Addict/YouTube

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A Tesla employee and FSD Beta tester has been terminated over what the company states is a conflict of interest. The employee in question, Jon Bernal, is also the owner of the AI Addict YouTube channel, which features both casual and stress tests of Full Self-Driving Beta in real-world situations. 

Over the past year, Bernal shared numerous videos of FSD Beta in action, and being one of the system’s users who typically pushes the advanced driver-assist system to its limits, some of his videos featured flaws and shortcomings in Full Self-Driving Beta’s capabilities. This included a rather dramatic video of FSD Beta 9 in downtown San Francisco, which featured several mistakes in the system’s maneuvers, as well as an actual accident involving FSD Beta 10.10 in downtown San Jose, which featured Bernal’s Model 3 hitting a traffic bollard

Following his termination from the company, Tesla opted to cut off Bernal’s access to FSD Beta. This, according to the former employee, was despite the fact that he has not encountered any safety strikes while using the system. Bernal’s 2021 Tesla Model 3 is still equipped with the company’s Full Self-Driving suite, however, which was given to him as a free perk when he purchased the vehicle as an employee. Tesla’s FSD suite is currently offered as a $12,000 option, though it was priced at $8,000 when Bernal took delivery of his Model 3 in December 2020. 

Bernal started his employment at Tesla in August 2020, working as a data annotation specialist in an office in San Mateo, California. As per records shared by the former employee to CNBC, he was later moved into the role of advanced driver assistance systems test operator. He was terminated from the company on the second week of February 2022. Prior to his dismissal, Bernal stated that managers verbally informed him that he “broke Tesla policy” and that his AI Addict YouTube channel was a “conflict of interest.” 

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While Bernal did previously admit in the comments section of one of his YouTube videos that he was a Tesla employee, the AI Addict channel does not prominently indicate or disclose that its host works for the EV maker. That being said, Bernal maintains that he has been transparent about his YouTube channel, even with his colleagues at Tesla. He also maintains that he has never disclosed anything in his videos that the company has not rolled out to the public. 

“The FSD Beta releases I was demonstrating were end-user consumer products,” the former Tesla employee said. 

While he cannot use his personal Model 3 for FSD Beta videos today, the former employee noted that he has attained access to other Teslas with FSD Beta. As such, Bernal noted that he should be able to continue his independent research and reviews. One such video has already been uploaded on the AI Addict YouTube channel, where Bernal briefly discussed his departure from Tesla before taking FSD Beta in his typical stress tests. 

Despite his experiences with the EV maker, Bernal has noted that he still cares a lot about the company and what it is attempting to accomplish with products like Autopilot and FSD Beta. “I still care about Tesla, vehicle safety, and finding and fixing bugs,” he said. 

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Bernal’s latest video, which includes his thoughts on his departure from Tesla, could be viewed below.

Don’t hesitate to contact us with news tips. Just send a message to simon@teslarati.com to give us a heads up.

Simon is an experienced automotive reporter with a passion for electric cars and clean energy. Fascinated by the world envisioned by Elon Musk, he hopes to make it to Mars (at least as a tourist) someday. For stories or tips--or even to just say a simple hello--send a message to his email, simon@teslarati.com or his handle on X, @ResidentSponge.

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Tesla Hardware 3 owners could be made whole this month

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tesla-asia-model-3
Credit: Tesla Asia/Twitter

Tesla Hardware 3 owners are set to get a new Full Self-Driving version this month as the company plans to release what it is referring to as v14 Lite.

The rollout is not yet confirmed for June, but Tesla executives have stated on several occasions that this more refined FSD iteration will work with their cars and increase its capabilities.

This comes after Tesla admitted during its last Earnings Call that these Hardware 3 vehicles would not be able to achieve Full Self-Driving, something that they did not know when they bought these cars. We regularly receive messages from Hardware 3 owners asking when v14 Lite will come out, what they should expect, and whether it is worth it to upgrade the self-driving computer or buy a new car altogether.

It is hard not to feel for them; Tesla CEO Elon Musk said at the company’s 2019 Autonomy Day that all vehicles produced at the time, including Hardware 3 cars, had “all the hardware necessary, compute and otherwise, for Full Self-Driving.”

Musk also said in March of that year that, “Anyone who purchased Full Self-Driving will get FSD computer upgrade for free.”

However, during the Q1 2026 Earnings Call, Musk admitted that Hardware 3 vehicles would not be capable of FSD, as “It has only 1/8th the memory bandwidth of Hardware 4, and memory bandwidth is one of the key elements needed for unsupervised FSD.”

Tesla has made some effort to remedy these Hardware 3 owners by offering:

  • Discounted trade-ins toward AI4 cars
  • Hardware retrofits, which would replace the self-driving computer and upgrade all cameras
  • Full Self-Driving v14 Lite

The issue is that many of these owners were led to believe their cars would be capable of unsupervised self-driving. Now, they’re left scrambling for options, and while there are several, they will all require more money out of their pockets.

Expectations for Tesla v14 Lite for Hardware 3 Owners

The big differences between the AI4 v14 and v14 Lite for Hardware 3 owners will stem primarily from hardware constraints. Tesla developed v14 Lite with an optimized frame of mind; the v14 neural nets are toned down to run on an HW3 computer.

Tesla v14 will use the same behavior, but its limits will be hardware-related, especially given that the cameras on HW3 vehicles are lower-resolution.

Tesla reveals its plans for Hardware 3 owners who are eager for updates

This will result in potentially more edge cases due to the lower quality perception and less long-range detection, but reaction time and overall confidence should be more refined.

There should also be a handful of additional features that are available on AI4 cars, such as:

  • Starting Full Self-Driving from Park
  • Auto Shift
  • Streaks
  • Speed Profiles
  • Improved Dynamics, like Pulling Over for Emergency Vehicles

Tesla plans to release v14 Lite this month, but we are all familiar with how the company can be with timelines. Additionally, if v14 Lite has not proven to be ready for a wide release, Tesla will slam the brakes on the rollout.

We would anticipate that Tesla is testing v14 Lite internally, and likely has been for several months.

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Elon Musk

SpaceXAI just launched into your kitchen with their new app

SpaceXAI just powered its first consumer app and it predicts what you want to buy.

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SpaceXAI just made its first move into consumer AI, and it involves your grocery cart. On June 3, 2026, Gopuff and SpaceXAI announced the launch of Go, a Grok-powered shopping assistant built directly into the Gopuff app that predicts what you need before you even start searching for it.

Gopuff is an instant delivery platform that operates more than 400 micro-fulfillment centers across the U.S., delivering everyday essentials, snacks, drinks, and household items in as little as 15 minutes. It is not a restaurant delivery app or a marketplace. It owns its inventory, controls its warehouses, and handles its own logistics, which means it has built one of the most detailed consumer behavior datasets in retail over its 13-year history.

Go combines SpaceXAI’s advanced reasoning, voice, and image generation models with Gopuff’s dataset of hundreds of millions of orders and real-time cultural signals from X to prepare a suggested cart the moment a customer opens the app. It learns each shopper’s habits and automatically builds a personalized cart based on time of day, location, order history, and real-time indicators. Returning customers can check out with a single tap.


Rather than searching for specific items, users can describe a situation like a game-day party or the desire for a healthy breakfast and Go will assemble a cart automatically. It can also predict when shoppers are running low on items like coffee or paper towels and have them packed and delivered in under 15 minutes. Grok voice integration lets users talk to the app in plain conversational language and check out completely hands-free.

Gopuff co-founder and co-CEO Yakir Gola said: “Today, we believe the greatest friction left in commerce is not delivery or instantaneous access to the essentials customers need. It’s the moment before: the thinking, the deciding, the remembering. We’re combining Gopuff’s demand intelligence with xAI’s frontier reasoning to create an everyday shopping experience that feels like a true extension of you.”

Why SpaceX just made a $60 billion bet on AI coding ahead of historic IPO

The timing carries context beyond the product launch. SpaceXAI was formed after SpaceX completed an all-stock merger with Elon Musk’s xAI earlier this year, folding one of the most advanced AI labs in the world into the same corporate structure as the company preparing what could be the largest IPO in history. SpaceXAI is dipping into consumer-focused AI just as it prepares for its public debut, and while Musk has openly discussed building an everything app, this launch uses Grok to power another company’s product rather than launching a standalone consumer platform. Every consumer-facing deployment of Grok ahead of the IPO roadshow adds tangible evidence that SpaceXAI is not just an infrastructure play but a direct competitor in the AI application layer where OpenAI and Google are already fighting for dominance.

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Tesla adds new Supercharger feature for a better idea of what to expect

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Credit: Tesla

Tesla has introduced an enhanced visualization in its Supercharger navigation system, building directly on the Site Maps feature rolled out a few months ago.

This latest software update adds detailed 3D icons that represent specific vehicle models parked at charging stalls, offering drivers a more precise view of site occupancy and layout.

The Site Maps debuted in Tesla’s 2025 Holiday Update, providing 3D overviews of select Supercharger locations with real-time stall availability.

Tesla supplements Holiday Update by sneaking in new Full Self-Driving version

Drivers could see which spots were open, occupied, or out of service when navigating to supported stations.

Now, the system takes this capability further by rendering accurate representations of Tesla vehicles, including distinctions between models such as the Model 3, Model Y, Model S, Model X, and Cybertruck. These icons appear as lifelike 3D renderings, complete with recognizable shapes and proportions that match the actual cars charging at the site:

This refinement improves the user experience during road trips and daily charging stops. As drivers approach a Supercharger, the navigation display now shows not just generic occupied markers but identifiable vehicle types plugged into each stall.

Blue indicators highlight active charging sessions, while other visual cues denote availability or maintenance status. The feature integrates seamlessly with the existing map interface, allowing quick assessment of the best available spot based on vehicle size and positioning.

Tesla continues to expand the availability of these detailed Site Maps across its global network. Initially piloted at a limited number of locations, the rollout has progressed steadily, with more stations gaining support in recent software versions.

Owners benefit from better planning, as the system helps identify compatible stalls and reduces uncertainty upon arrival. The update reflects Tesla’s ongoing commitment to refining its navigation and charging ecosystem through iterative software improvements.

In addition to model-specific icons, the enhanced maps maintain all prior functionalities, such as integration with nearby amenities and energy usage predictions. This ensures a comprehensive tool for efficient Supercharging.

As Tesla’s fleet grows and the network scales, such features play a key role in optimizing the overall ownership experience. Future updates may extend similar visualizations to additional sites and incorporate even more data points for drivers.

With this piggyback enhancement, Tesla demonstrates how small but thoughtful additions can elevate an already useful tool, making Supercharger visits smoother and more informed for its customers. The company is expected to broaden the feature’s reach in upcoming releases, further solidifying its leadership in EV charging infrastructure.

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