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SpaceX wants to launch its next Starship ASAP

Starship SN10 is ironically front and center in this SN9 prelaunch photo published by SpaceX.

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Contrary to recent comments from CEO Elon Musk, SpaceX appears to be forging ahead at full speed in a bid to launch its next Starship ASAP.

Known as Starship serial number 10 (SN10), the prototype is the latest in a series of four ships SpaceX has ultimately set aside from low(er)-altitude development testing. Starship SN8 – the first functional prototype to reach its full height – debuted on December 8th, 2020, blowing expectations out of the water with a failure mere seconds before the end of a more than six-minute flight test. According to Musk, had a fuel tank remained properly pressurized from start to finish, SN8 could have very well stuck the landing on the first try.

Two months later, after the better part of two weeks of licensing and static fire test delays, Starship SN9 attempted to carry the torch forward but suffered an unrelated failure slightly earlier than SN8’s. One of two Raptor engines failed to ignite for a high-risk flip and landing burn, causing the Starship to impact the ground even more violently than its predecessor. It’s unclear why the ill-fated Raptor failed to ignite or why the engine that did ignite appeared to experience a major failure shortly thereafter but rocket propulsion is extraordinarily difficult – and Raptor is near – or at – the end of that scale.

While SpaceX obviously hasn’t spun around and fixed a complex Starship propulsion issue in a matter of days, Musk eventually revealed his opinion that he, his engineers, or some combination of both “were too dumb” to exploit one obvious way to mitigate the risk of engine failure during flip and landing. That ‘obvious’ tweak: reignite all three of Starship’s available landing engines, not just two.

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In theory, with a fast-enough response time, Starship could ignite all three Raptors, perform a supercharged flip from a belly- to tail-down orientation, and selectively shut off one of the engines based on the data from what is essentially a midair static fire. In the event that all three engines are performing nominally, Starship would shut down the least useful engine (i.e. the Raptor with the least leverage) for a gentle two-engine landing burn.

A failed two-engine landing burn vs. a successful three-engine ascent burn. (SpaceX)

Impressively, Musk said that SpaceX would implement those changes immediately, attempting the first three-engine reignition as early as Starship SN10’s launch debut. Already at the launch pad when Starship SN9 lifted off, SpaceX revealed plans to launch SN10 as early as February 2021 at the end of SN9’s test flight webcast.

A few days prior to SN9’s ill-fated test flight, Musk had also stated that Starship SN10 would perform a “cryoproof” test and only then have its three Raptor engines installed. Instead, in an apparent change of plans, SpaceX installed Starship SN10’s Raptors – SN39, SN50, and an unknown third engine – from February 5th to 7th.

On Sunday, local longtime resident Mary (aka BocaChicaGal) received an official safety alert from SpaceX, signaling plans for an explosive Starship test of some kind as early as Monday, February 8th. Historically, those overpressure safety warnings have only been distributed when SpaceX is preparing for a Starship static fire attempt. In other words, it’s possible that Starship SN10’s very first test could be a live wet dress rehearsal (WDR) with flammable liquid oxygen and methane propellant. If that WDR goes well, SpaceX could move directly into a one, two, or three-engine static fire.

Of course, as SN9’s lengthy test period rubbed in, Starship is still in the prototype stage and is far from a mature system, meaning that it’s always safer to expect delays than an on-time performance. To be clear, it’s far more likely that SpaceX will perform a familiar “cryo proof” test with non-flammable liquid nitrogen – perhaps hoping to complete a cryoproof and static fire in the same test window.

Either way, stay tuned for updates and follow along with NASASpaceflight’s excellent live coverage in the event that SpaceX really is prepared to static fire Starship SN10 between 9am and 6pm CST (UTC-6) on Monday.

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Eric Ralph is Teslarati's senior spaceflight reporter and has been covering the industry in some capacity for almost half a decade, largely spurred in 2016 by a trip to Mexico to watch Elon Musk reveal SpaceX's plans for Mars in person. Aside from spreading interest and excitement about spaceflight far and wide, his primary goal is to cover humanity's ongoing efforts to expand beyond Earth to the Moon, Mars, and elsewhere.

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Tesla Optimus V3 hand and arm details revealed in new patents

Two new patents, which were coincidentally filed on the same day as the “We, Robot” event back in October 2024, protect Tesla’s mechanically actuated, tendon-driven architecture.

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Credit: Tesla China

Tesla is planning to soon reveal its latest and greatest version of the Optimus humanoid robot, and a series of new patents for the hands and arms, with the former being, admittedly, one of the most challenging parts of developing the project.

Two new patents, which were coincidentally filed on the same day as the “We, Robot” event back in October 2024, protect Tesla’s mechanically actuated, tendon-driven architecture.

The designs relocate heavy actuators to the forearm, route cables through a sophisticated wrist design, and employ innovative joint assemblies to achieve human-like dexterity while enabling lightweight construction and high-volume manufacturing.

Core Tendon-Driven Hand Architecture

The primary patent, which is titled “Mechanically Actuated Robotic Hand,” details a cable/tendon-driven system.

Actuators are positioned in the forearm rather than the hand. Each finger features four degrees of freedom (DoF), while the wrist adds two more.

Three thin, flexible control cables (tendons) per finger extend from the forearm actuators, pass through the wrist, and connect to the finger segments. Integrated channels within the finger phalanges guide these cables selectively—routing behind some joints and forward of others—to enable independent bending without unintended motion.

Patent diagrams illustrate thick cable bundles emerging from the wrist into the palm and fingers, with labeled pivots and routing guides. This setup closely mirrors human forearm-muscle and tendon anatomy, where most hand control originates proximally.

Advanced Wrist Routing Innovation

One of the standout features is the wrist’s cable transition mechanism. Cables shift from a lateral stack on the forearm side to a vertical stack on the hand side through a specialized transition zone.

This geometry significantly reduces cable stretch, torque, friction, and crosstalk during combined yaw and pitch wrist movements — common failure points in simpler tendon systems that cause imprecise or jerky motion.

By minimizing these issues, the design supports smoother, more reliable multi-axis wrist operation, essential for complex real-world tasks.

Companion Patents on Appendage and Joint Design

Two supporting patents provide additional depth. “Robotic Appendage” covers the overall forearm-to-palm-to-finger assembly, with a palm body movably coupled to the forearm and finger phalanges linked by tensile cables returning to forearm actuators. Tensioning these cables repositions the phalanges precisely.

“Joint Assembly for Robotic Appendage” describes curved contact surfaces on mating structures paired with a composite flexible member. This allows smooth pivoting while maintaining consistent tension, enhancing durability, and simplifying assembly for mass production.

Executive Insights on Hand Development Challenges

Tesla executives have consistently described the hand as the most difficult component of Optimus.

Elon Musk has called it “the majority of the engineering difficulty of the entire robot,” emphasizing that human hands possess roughly 27–28 DoF with an intricate tendon network powered largely by forearm muscles. He has likened the challenge to something “harder than Cybertruck or Model X… somewhere between Model X and Starship.”

Elon Musk shares ridiculous fact about Optimus’ hand demos

In mid-2025, Musk acknowledged that Tesla was “struggling” to finalize the hand and forearm design. By early 2026, he stated that the company had overcome the “hardest” problems, including human-level manual dexterity, real-world AI integration, and volume production scalability.

He estimated the electromechanical hand represents about 60 percent of the overall Optimus challenge, compounded by the lack of an existing supply chain for such precision components.

These patents directly tackle the acknowledged pain points: relocating actuators reduces hand mass and inertia for better speed and efficiency; advanced wrist routing and joint geometry address friction and crosstalk; and simplified, stackable parts visible in the diagrams indicate readiness for high-volume manufacturing.

Implications for Optimus Production and Leadership

Collectively, the patents portray the Optimus v3 hand not as a mere prototype, but as a production-oriented system engineered from first principles.

The 22-DoF architecture, forearm-driven tendons, and crosstalk-minimizing wrist deliver a clear competitive edge in dexterity. They align with Musk’s view that high-volume manufacturing is one of the three critical elements missing from most other humanoid projects.

For Optimus to become the most capable humanoid robot, its hand needed to replicate the useful and applicable design of the human counterpart.

These filings demonstrate that Tesla has transformed years of engineering challenges into patented, elegant solutions — positioning the company strongly in the race toward general-purpose robotics.

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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.

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tesla interior operating on full self driving
Credit: TESLARATI

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.

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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.

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Credit: Elon Musk | X

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.

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.

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.

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