A California judge has forced General Motors’ (GM) self-driving unit Cruise to increase its settlement offer to the maximum amount, after one of the company’s robotaxis pinned and seriously injured a pedestrian in October.
On October 2, a driverless Cruise vehicle dragged and pinned a pedestrian in San Francisco, and the company’s license to operate self-driving cars was immediately revoked by the California Department of Motor Vehicles (DMV). The DMV later said that Cruise “misrepresented” and “omitted” crucial details about its response to the accident, and the California Public Utilities Commission (CPUC) in December ordered the company to appear before a judge this month.
During the hearing, which was held on Tuesday, California Administrative Law Judge (ALJ) Robert Mason III suggested that Cruise revise its $75,000 settlement offer to the maximum penalty of $112,500, after calling the company’s proposed amount “low,” and even suggesting the company was seeking a “discount.”
While Judge Mason III said he appreciated Cruise attempting to take “corrective action” in its crash response procedures, he added that the company should “take a hint” following his multiple questions about the offer amount, suggesting directly that Cruise change its settlement offer to the full penalty.
“Point taken, your Honor,” responded Craig Glidden, Cruise President and Chief Administrative Officer. “We immediately revise our offer to the amount requested.”
Waymo could face new legal barriers in its expansion to Los Angeles
The hearing discussed findings from an investigation conducted by the law firm Quinn Emanuel, which Cruise hired, including that internet connectivity hampered the company’s sharing of video footage from the accident with regulators in meetings that followed.
In response to the motion for approval to settle at $75,000, the commission can adopt, adopt with revisions, or reject Cruise’s filing. Following the hearing, the next step is for Judge Mason to write a proposed decision on the case for the commissioner’s consideration, with the general timeframe falling within about 60 days, as a CPUC spokesperson clarified to Teslarati.
Cruise said it was eager to resolve the case and move past the incident, adding that it wanted to continue to “advance the mission of bringing driverless cars that are safer to the public and also greater accessibility to the public to the market.”
However, Mason didn’t make it sound like the commission was eager to set the case aside:
“While the commission does fall on the side of getting its cases resolved, I don’t know that this is one of those protracted pieces of litigation that we’re usually most anxious to put aside and then move forward with the regulatory process,” Mason added.
In the original motion, filed on January 30, Cruise outlines the key requirements it would have to follow as part of the settlement:
1. Cruise will adopt voluntarily several new data reporting enhancements that will provide additional data to the Commission concerning California collisions and AVs operating in California under a deployment permit that enter a minimal risk condition (“MRC”) state and result in conditions described in Attachment A;
2. Cruise will provide the Commission with Cruise’s responses to the permit reinstatement questions from the California Department of Motor Vehicles (“DMV”) at the same time Cruise provides those responses to the DMV;
3. Cruise will make a payment of $75,000 to the State General Fund within ten (10) days of the Commission’s approval of the Settlement Agreement without modification; and
4. Upon the Commission’s approval of the Settlement Agreement, the OSC proceeding will be closed.
“We are committed to working in partnership with the CPUC, other regulators and government agencies to improve transportation safety in support of a shared goal –– providing better, safer and more accessible transportation to the public in our communities,” a Cruise spokesperson wrote in an email to Teslarati. “Over the past several months, we have taken important steps to improve our leadership, processes and culture, and we are committed to resolving matters to the Commission’s satisfaction as we work to restore regulatory and public trust.”
Cruise also noted that the accident, which occurred after the pedestrian had already been hit by a human driver, was partially caused by the driverless ride-hailing vehicle falsely identifying the situation as a side-impact collision rather than a frontal collision, causing the Minimal Risk Condition (MRC) response that forces the vehicle to pull over.
In addition, Cruise said it is currently expecting a new Chief Safety Officer in the “not too distant future,” after two co-founders resigned immediately following the accident, and after the company fired nine executives and laid off nearly a quarter of its staff on the same day in December.
GM recently announced plans to cut spending on Cruise in half this year, though it said it also hoped to “refocus and relaunch” the company’s operations. GM CEO Mary Barra highlighted significant changes at Cruise, which the company began implementing following the Quinn Emanuel investigation.
“At Cruise, we are committed to earning back the trust of regulators and the public through our commitments and our actions,” Barra said following GM’s 2023 earnings call.
You can see the full January 30 filing from Cruise below, including the findings from the Quinn Emanuel investigation, which Cruise made public last month.
What are your thoughts? Let me know at zach@teslarati.com, find me on X at @zacharyvisconti, or send your tips to us at tips@teslarati.com.
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.
Tesla intertwines FSD with in-house Insurance for attractive incentive
Tesla finalizes AI5 chip design, Elon Musk makes bold claim on capability
