News
Opinion: Tesla and India is the right thing at the wrong time
Tesla and India will not be working together any time soon, as new reports now indicate that Tesla has pulled its team responsible for entrance into the Indian market to other regions. Tesla and India might be a powerful one-two punch in the future, but in 2022, the two are just the right thing at the wrong time.
When Tesla first started making moves toward entering the Indian automotive market, there was a lot of excitement. The unbelievable potential of a partnership between the world’s leading electric car company and a government that primarily focuses on domestic manufacturing efforts, mainly due to the Make in India initiative, had people buzzing. However, there were still hoops to jump through. Any person with any sort of knowledge about India and cars knows that it is an expensive place to own one, especially if it was not built there. Getting cars from outside of India into the country doubles the cost of the vehicle on most occasions due to import duties. This is when Tesla started to realize how difficult this whole process might be.
Tesla places its India entry on hold after failing to secure lower import taxes: report
In routine negotiations, even with companies and governments, there is always a brief standoff period to see who will budge first. The hypothetical game of chicken can be magnified when dealing with two large entities, but eventually, something happens where someone makes a move, and things start to come together. I thought a great, recent, and relevant example of this would be the Elon Musk-Twitter buyout, where, as the board of the platform mozied over the Tesla CEO’s offer, new developments were few and far between, as expected. Nothing was going to move forward until someone budged.
The issue is that sometimes people choose not to budge because their needs in a particular deal are non-negotiable. When the needs of both sides are non-negotiable, it complicates the entire ordeal, and this is what made the Tesla-India deal stagnate: Two large entities that had specific requirements to make something happen. Neither was asking for a small thing, so it is not necessarily unreasonable that Tesla put its plans for India on hold.
Tesla needed to test demand for its cars. It would only be able to do this by building them in Fremont, California, Austin, Texas, Brandenburg, Germany, or Shanghai, China, and then shipping them to India. The problem with this system was it would not be an accurate representation of what Tesla might be able to sell in the market, as the vehicles would still be subjected to massive import duties that would double the cost of the car in some cases. Only a small percentage of the population would be able to afford that, and with very little EV infrastructure in India, it made the company’s products even less attractive. Tesla was effectively stuck between a rock and a hard place because it had an interest in building and selling cars in India, it just needed to confirm that the people of India wanted to buy the cars. Indian government officials rarely offered commentary that was indicative of a willingness to budge.
India wanted Tesla to commit to building a new Gigafactory in their country, which would align with the government’s focus on domestic manufacturing efforts and would likely give officials enough to pull back import duties for Tesla. However, Tesla could not commit to this: there was no indication that demand would be high enough to justify an entire factory, and Tesla was not sure it would be able to export vehicles from the Indian factory to other countries. Given the economic situations across the world during the past two years due to the COVID-19 pandemic, neither entity would be able to budge from their needs.
India and Tesla were the right thing, just at the wrong time. Given the extreme demands that both Tesla and Indian officials needed, it was best to not beat a dead horse any longer and move on from the potential partnership, at least temporarily. Tesla does have a lot of potential in India, but it cannot justify purchasing massive land plots for a new facility, it cannot justify spending millions more on showrooms and service centers, and it can not adequately test the want for its vehicles with massive import taxes trailing behind every car sent to the market.
Try again in a few years, hopefully.
I’d love to hear from you! If you have any comments, concerns, or questions, please email me at joey@teslarati.com. You can also reach me on Twitter @KlenderJoey, or if you have news tips, you can email us at tips@teslarati.com.
Elon Musk
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.
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.
Tesla’s Optimus V3 robot hand looks to have been revealed in a new international patent published today.
The patent describes a tendon/cable-driven hand:
• Actuators in the forearm
• Each finger has 4 degrees of freedom
• The wrist has 2 degrees of freedom
• Tendon-driven… pic.twitter.com/eE8xLEYSrx— Sawyer Merritt (@SawyerMerritt) April 16, 2026
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.
Boom! @Tesla_Optimus 의 3세대 구조로 추정되는, 로봇 팔 및 관절에 대한 특허가 공개되었습니다.
아티클 작업에 들어가겠습니다.
1년 넘게 기다려 온, 정말 귀한 특허인데, 조회수 100만대로 터져줬으면 좋겠네요. 😉@herbertong @SawyerMerritt@GoingBallistic5 @TheHumanoidHub pic.twitter.com/CCEiIlMFSX
— SETI Park (@seti_park) April 16, 2026
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.”
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.
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.
Tesla Optimus V3 hand and arm details revealed in new patents
Tesla intertwines FSD with in-house Insurance for attractive incentive
