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Tesla “whistleblower’s” lawyer opens up about Martin Tripp’s sudden Twitter departure

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Less than a day after posting images supposedly supporting his case against Tesla, alleged saboteur and self-proclaimed “whistleblower” Martin Tripp has opted to leave Twitter. Tripp’s departure from the social media platform comes amid the aftermath of his posts yesterday, which allegedly depicted flawed battery packs that Tesla installed on some Model 3.

Apart from photos taken inside Gigafactory 1, Tripp also released a list of Model 3 VINs which he claimed were equipped with damaged battery packs. The former employee shared screenshots of emails he sent to Elon Musk about Tesla’s operations as well. These images were quickly picked up by several media outlets.

Unfortunately for Tripp, his account was slapped with a 12-hour suspension by Twitter, due to one of his tweets containing an email address listing Elon Musk’s name. In a statement to Gizmodo, Tripp noted that Twitter warned him that he “may not publish or post other people’s private information without their express authorization and permission.”

Stuart D. Meissner, Tripp’s lawyer in his countersuit against Tesla, also contacted Linette Lopez, one of the reporters who covered the former Tesla employee’s tweets. It was not long before Martin Tripp opted to depart from Twitter completely.

https://twitter.com/StuartMeissner/status/1029905643208101889

In a series of recent tweets, Meissner announced that Tripp decided to take down his Twitter page on his advice. The lawyer also denied reports that Tripp’s Twitter account was suspended earlier today. Meissner maintained that Tripp’s departure from the social media platform was voluntary, so that there will not be any more confusion about his case against Tesla. Furthermore, the lawyer also claimed that a number of his client’s social media pages were hacked.

Following are Meissner’s updates explaining why Tripp opted to leave Twitter. 

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https://twitter.com/StuartMeissner/status/1030138369840500736

https://twitter.com/StuartMeissner/status/1030139433276846081

https://twitter.com/StuartMeissner/status/1030142208572358657

Martin Tripp, a former Tesla engineer working at Gigafactory 1, was accused by the electric car maker of sabotage last June. A lawsuit filed by the company against Tripp alleged that the former employee hacked into Tesla’s Manufacturing Operating System, sent confidential data to external sources, and misreported to the media. Among Tripp’s contacts in the press was Business Insider reporter Linette Lopez, who, in turn, published a number of articles based on information provided by the former Tesla engineer. Lopez confirmed this when she was featured in a segment at CNBC’s Halftime Report last month.

Interestingly, Lopez’s comment on CNBC was a bit different from Tripp’s statement immediately after he received a lawsuit from Tesla. Tripp claimed to CNN Money that he contacted several media outlets about his allegations against the company, and that he had spoken at length with one of them, but the news outlet was yet to do a story about his revelations. During this time, Lopez had already published articles that included information seemingly provided by Tripp.

Tesla, for its part, has denied Tripp’s claims. In response to the release of Model 3 VINs that were allegedly equipped with damaged battery packs, the electric car maker was firm in the notion that the former Tesla engineer’s allegations were false.

“As we’ve said before, these claims are false, and Mr. Tripp does not even have personal knowledge about the safety claims that he is making. No punctured cells have ever been used in any Model 3 vehicles in any way, and all VINs that have been identified have safe batteries. Notably, there have been zero battery safety issues in any Model 3.”

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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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Elon Musk

Tesla AI boss reveals how big Optimus is going to get

Tesla’s Optimus chief corrected himself on X, confirming a staggering 10 million robot production target.

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Tesla Optimus Gen 3 [Credit: Tesla]

Tesla’s Optimus program has a new number attached to it, after Ashok Elluswamy, the executive who has run the humanoid robot program since June 2025, posted a three word correction on X Thursday, “Correction, 10 million robots.”

The line clarifies the long term annual capacity Tesla is building toward its planned second Optimus production line at Gigafactory Texas, a figure Musk has cited repeatedly since last year’s shareholder meeting.

The scale is worth noting, because ten million robots a year would mean Tesla building more units annually than most countries sell in new cars. Tesla has framed this as a second line, not the first. The buildout is happening in two phases: a roughly one million unit per year line inside Tesla’s Fremont factory, installed on the floor space vacated when Model S and Model X production ended earlier this year, and a much larger dedicated facility under construction at Giga Texas that broke ground on its first steel structure in May. That Texas facility is the one Elluswamy’s correction refers to, and is expected to reach volume production sometime in 2027.

Tesla Optimus project fires up as Musk sees production line progress

Elluswamy took over Optimus from Milan Kovac last summer and has spent the months since talking up the program’s trajectory. Elon Musk has also floated the ten million figure at Tesla’s 2025 shareholder meeting.

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Ending Model S and Model X production to make room for the first Optimus line was one of the more consequential manufacturing decisions in the company’s recent history, retiring two flagship vehicles in favor of a robot that has yet to enter mass production. Musk has previously estimated per unit production costs at $20,000 to $25,000 once Tesla reaches a million units a year, though he hasn’t said what that cost looks like at ten times the volume.

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Autonomous vehicle red tape gets slashed by Trump Administration

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Credit: Zoox

The Trump Administration today made several key moves to help with the deployment of autonomous vehicles by cutting overreaching red tape that has stifled growth and innovation for years.

The moves, which were put forth by the National Highway Traffic Safety Administration (NHTSA), aim to grant temporary exemptions to at least one company currently, although that could expand in the coming months. Additionally, it will work with organizations to develop standards and a sound but efficient regulatory landscape.

Zoox is the only company mentioned explicitly by the Trump Administration in its press release announcing the new terms today. They will receive a temporary two-year exemption that will allow the commercial deployment of up to 2,500 vehicles annually for two years.

There is a potential exemption for Robomart, Inc., which “requests a temporary exemption from certain FMVSS No. 500 requirements for a low-speed vehicle operated by an ADS without a human driver onboard. NHTSA will publish a separate notice seeking public comment on its merits once the initial evaluation is complete,” the agency said.

Here are the five new terms that Secretary Sean Duffy has implemented through the NHTSA today:

  1. Allow Zoox to commercially deploy its robotaxis through a temporary exemption.
    This temporary exemption will allow the commercial deployment of up to 2,500 vehicles annually for two years, subject to an enhanced, adaptable oversight structure that can evolve as Zoox’s technology advances.
  2. Accelerate development of first-ever AV performance standards through a partnership with SAE Industry Technologies Consortia (ITC).
    This partnership will fund a three-year, $5 million “A2SCEND” consortium, bringing together experts to gather data and accelerate creation of the first-ever AV performance standards. This project will inform a single national standard for AV safety to eliminate the patchwork regulatory landscape that has stifled innovation for years.
  3. Publish an interim final rule that allows vehicles manufactured prior to an exemption to be eligible for a commercial deployment exemption.
    This rule will modernize the application process and improve access to exemptions for innovators, including AV developers, by granting the NHTSA Administrator the discretion to apply temporary exemptions to vehicles manufactured prior to the effective date of an exemption grant.
  4. Streamline the application process for Part 555 exemptions by updating guidance and soliciting feedback from the public.
    By updating the Part 555 exemption process—which allows automakers to temporarily sell a limited number of non-compliant vehicles, primarily to test new technologies—NHTSA is aiming to create a more flexible oversight structure for exemptions and summarize recent AV framework activities, including expanded exemption pathways, streamlined crash reporting, and ongoing efforts to modernize Federal Motor Vehicle Safety Standards (FMVSS).
  5. Establish a new Federal Docket for public feedback on NHTSA’s updated safe AV development and deployment guidance.
    NHTSA is updating its technical guidance for AVs for the first time since 2017—focusing on key safety areas like emergency responder interactions, safety management systems, remote assistance, and post-crash behavior to help the industry scale up driverless deployments safely.

Additionally, the NHTSA said it has modernized some safety standards by proposing updates to:

  • FMVSS 102 – Transmission shifting
  • FMVSS 103/104 – Windshield defrosting and wiping
  • FMVSS 110 – Tire placards
  • FMVSS 135 – Braking systems
  • FMVSS 101 – Controls and displays
  • FMVSS 108 – Vehicle lighting
  • FMVSS 111 – Mirrors and rearview display
  • FMVSS 126 – Electronic stability control systems
  • FMVSS 201/208 – Sun visors and warning labels

These changes aim to make the regulatory process for autonomous vehicles more streamlined and efficient, which could help the U.S. gain dominance over autonomous vehicle systems moving forward.

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Elon Musk

Elon Musk has a crazy prediction about AI in two years

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Daniel Oberhaus, CC BY-SA 4.0 , via Wikimedia Commons

Elon Musk is, in many respects, one of the biggest and most influential figures in modern-day artificial intelligence.

Given that Tesla, SpaceX, and xAI are all looked at in their respective fields as leaders to an extent, each of them has a heavy influence on the future of AI, even though two of them are not thought of, at face value, as AI companies.

Musk has grand expectations for what is to come with AI, not only as a form of assistance to make human lives easier, but to make humans multiplanetary and solve some of the biggest issues that face us today. But even he is astounded by AI’s pace of progress.

He believes that in two years, AI will be so mind-blowing it might be unrecognizable.

This progress can be seen in a variety of ways, but perhaps the most popular way people have shown AI’s progress, especially on social media, is through an incredibly arbitrary way of watching Will Smith eat spaghetti:

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This is a great way to show people how AI is improving, especially from a perspective that examines how it can manufacture images and video from prompts. AI is an incredibly complex concept, however, and it goes much deeper than Will Smith eating Italian food.

Musk’s most widely adopted method of AI is likely Tesla Full Self-Driving, which impacts millions of people as they utilize it to increase safety with their travel. Musk has routinely pushed incredibly aggressive timelines for self-driving, especially unsupervised.

Perhaps this perspective is why he feels that things will be solved in a timeframe that is much more aggressive than most of us would think. Regardless, the progress of AI is moving fast, and it seems that Musk’s expectations for it could be high.

But if it can actually achieve full-length motion pictures and even more realistic production value, it will be hard to distinguish between reality and AI very soon.

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