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Elon Musk left OpenAI due to conflict of interest with Tesla
OpenAI, the nonprofit research firm co-founded by Elon Musk, announced that the serial tech entrepreneur is stepping down from the organization’s board of directors. According to an official announcement by the nonprofit, Elon’s departure is partly due to Tesla’s AI projects, which could result in a potential conflict of interest for the CEO.
Musk’s departure from OpenAI’s board does not mean that he is relinquishing ties with the nonprofit, however. In a blog post about its new supporters, the research firm asserted that the Tesla CEO will be staying on as a benefactor and advisor for the organization.
“Elon Musk will depart the OpenAI Board but will continue to donate and advise the organization. As Tesla continues to become more focused on AI, this will eliminate a potential future conflict for Elon.”
As Tesla continues to evolve its Autopilot suite of features and aims to complete its first coast-to-coast fully autonomous drive this year, the Silicon Valley electric carmaker is said to be working on its own AI-based chips that will power the company’s future fleet of driverless cars. Musk revealed his efforts to produce a custom AI chip during a machine learning conference held last year, telling event attendees that Tesla is developing specialized AI hardware that will be the “best in the world.” According to The Register, Musk told event attendees, “I wanted to make it clear that Tesla is serious about AI, both on the software and hardware fronts. We are developing custom AI hardware chips”.
Stepping down from OpenAI’s board seems to be a logical step for Musk as his focus on developing advanced artificial intelligence systems can be misconstrued by a non-profit that aims to be the watchdog for friendly AI development. Prior to the announcement of Elon Musk’s departure from OpenAI’s board, the nonprofit published a paper discussing the possible dangers of AI-based attacks. According to OpenAI’s study, it is now time for policymakers and individuals to be aware of ways that AI-based systems can be used maliciously, especially considering the ever-evolving artificial intelligence landscape.
To conduct the study, OpenAI collaborated with a number of researchers from other organizations, including the Future of Humanity Institute, the Centre for the Study of Existential Risk, the Center for a New American Security, and the Electronic Frontier Foundation.
Discussing the findings of their research, the authors of the study wrote that while investigations on the benefits of AI are widespread, studies on the dangers of advanced, intelligent machines are relatively few. As the field of artificial intelligence begins to expand and evolve, OpenAI’s researchers believe that threats associated with the technology would also start to grow and develop.
As noted in the study, artificial intelligence can expand existing threats, since the scalable use of AI technology can be utilized to lower the cost of attacks. With AI, even real-world attacks requiring human labor can be accomplished by machines that could think within and beyond their programming.
OpenAI’s new paper also discussed the emergence of new threats, which could rise through the use of systems that engage in tasks that are impractical for humans. The researchers also advised that the time might soon come when the AI-focused attacks can be finely targeted and challenging to attribute. With these in mind, the OpenAI researchers, together with co-authors of the study, recommended a series of contingencies that policymakers, as well as those involved in the research field, can implement to prevent and address scenarios when intelligent systems can be used maliciously.
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According to the recently published OpenAI paper, the time is right for policymakers to collaborate with technical researchers to investigate, prevent, and mitigate potential malicious uses of artificial intelligence. OpenAI also advised engineers and researchers to acknowledge the dual-use nature of their work, allowing misuse-related considerations to be part of their research priorities. Furthermore, the nonprofit called for more mature methods when addressing AI’s dual-use, especially among stakeholders and domain experts involved in the field.
In conclusion, the OpenAI researchers and their peers admitted that while uncertainties remain in the AI industry, it is almost certain that artificial intelligence will play a huge role in the landscape of the future. With this in mind, a three-pronged approach — consisting of digital security, physical security, and political security — would be a great way to prepare for the upcoming use and possible misuse of artificial intelligence.
Co-founded by Tesla and SpaceX CEO Elon Musk back in 2015, OpenAI is a nonprofit research firm that aims to create and distribute safe artificial general intelligence (AGI) systems. As we noted in a previous report, OpenAI seems to be giving clues that it is ramping up its activity this year, as shown in a recent job posting for a Recruiting Coordinator who will be tasked to train and onboard the company’s new employees.
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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.