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Tesla’s Neural Network adaptability to hardware highlighted in new patent application
Tesla’s developments in the artificial intelligence arena are one of the most important aspects of its current and future technology, and this includes adapting neural networks to various hardware platforms. A recent patent publication titled “System and Method for Adapting a Neural Network Model On a Hardware Platform” provides a bit of insight into how the electric car maker is taking on the challenge.
In general, a neural network is a set of algorithms designed to gather data and recognize patterns from it. The particular data being collected depends on the platform involved and what kind of information it can send to the network, i.e., cameras/image data, etc. Differences between platforms mean differences in the neural network algorithms, and adapting them is something time consuming for developers. Just as apps have to be programmed to work based on the operating system or hardware on a phone or tablet, for example, so too do neural networks. Tesla’s answer to the adaptation issue is automation (of course).
During the adaptation process of a neural network to specific hardware, decisions must be made by a software developer based on available options built into the hardware being used. Each of these options, in turn, usually requires research, hardware documentation review, and impact analysis, with each set of options chosen, eventually adding up to a configuration for the neural network to use. Tesla’s application calls these options “decision points,” and they are a vital part of how their invention functions.
According to the application, after plugging in a neural network model and the specific hardware platform information for adaptation, software code traverses the network to learn where the decision points are, then runs the hardware parameters against those points to provide available configurations. More specifically, the software method looks at the hardware constraints (such as processing resources and performance metrics) and generates setups for the neural network that will satisfy the requirements for it to operate correctly. From the application:
“In order to produce a concrete implementation of an abstract neural network, a number of implementation decisions about one or more of system’s data layout, numerical precision, algorithm selection, data padding, accelerator use, stride, and more may be made. These decisions may be made on a per-layer or per-tensor basis, so there can potentially be hundreds of decisions, or more, to make for a particular network. Embodiments of the invention take many factors into account before implementing the neural network because many configurations are not supported by underlying software or hardware platforms, and such configurations will result in an inoperable implementation.”
Tesla’s invention also provides the ability to display the neural network configuration information on a graphical interface to make assessment and selection a bit more user friendly. For instance, different configurations could have different evaluation times, power consumption, or memory consumption. Perhaps an analogy for this process would be selecting configurations based on differences between Track Mode and Range Mode but instead for how you’d want your AI to work with your hardware.
This patent application looks to be one of the products of Tesla’s reported acquisition of DeepScale, an AI startup focused on Full Self Driving and designing neural networks for small devices. The listed inventor, Dr. Michael Driscoll, was a Senior Staff Engineer for DeepScale before transitioning to a Senior Software Engineer position at Tesla. Prior CEO of DeepScale, Dr. Forrest Iandola, also transitioned to Tesla as a Senior Staff Machine Learning Scientist before moving on to independent research this year.
Elon Musk broke his silence regarding the jury decision to throw out the case against OpenAI and Sam Altman. The Tesla, SpaceX, and xAI frontman has already indicated that an appeal will be filed regarding the decision, which went against him yesterday.
A Federal jury dismissed this high-profile lawsuit after less than two hours of deliberation due to a statute-of-limitations issue.
In a strongly worded post on X on May 18, Musk addressed the federal jury’s dismissal of his high-profile lawsuit against OpenAI, vowing to appeal the ruling to the Ninth Circuit Court of Appeals. The decision, according to Musk, was centered not on the substantive claims but on a statute-of-limitations technicality.
Musk’s lawsuit, filed in 2024, accused OpenAI co-founders Sam Altman and Greg Brockman of breaching the organization’s original nonprofit mission. OpenAI was established in 2015 as a non-profit dedicated to developing artificial intelligence for the benefit of all humanity, with Musk as a key early donor and co-founder before departing in 2018.
Musk alleged that Altman and Brockman improperly shifted the company toward a for-profit model, enriched themselves through massive valuations and partnerships (including with Microsoft), and betrayed founding agreements.
In his post, Musk emphasized that the judge and jury “never actually ruled on the merits of the case, just on a calendar technicality.” He stated unequivocally: “There is no question to anyone following the case in detail that Altman & Brockman did in fact enrich themselves by stealing a charity. The only question is WHEN they did it!”
Regarding the OpenAI case, the judge & jury never actually ruled on the merits of the case, just on a calendar technicality.
There is no question to anyone following the case in detail that Altman & Brockman did in fact enrich themselves by stealing a charity. The only question…
— Elon Musk (@elonmusk) May 18, 2026
Musk argued that allowing such actions to stand without review sets a dangerous precedent. “I will be filing an appeal with the Ninth Circuit, because creating a precedent to loot charities is incredibly destructive to charitable giving in America,” he wrote. He reiterated OpenAI’s founding purpose: “OpenAI was founded to benefit all of humanity.”
The jury’s unanimous advisory verdict found that Musk’s claims of breach of charitable trust and unjust enrichment were filed outside California’s three-year statute of limitations. U.S. District Judge Yvonne Gonzalez Rogers adopted the finding and dismissed the case. OpenAI hailed the outcome as vindication, while Musk’s legal team immediately signaled plans to appeal.
The trial, which featured testimony from Musk, Altman, Brockman, Microsoft CEO Satya Nadella, and others, exposed deep rifts in Silicon Valley over AI’s direction.
Musk has long warned that profit-driven AI development, especially with closed models and powerful corporate ties, risks endangering humanity—contrasting it with OpenAI’s original open, safety-focused charter. OpenAI countered that the suit stemmed from business rivalry and that Musk himself had explored for-profit paths earlier.
Musk’s appeal could prolong the saga, potentially affecting OpenAI’s valuation (reportedly over $800 billion) and IPO ambitions. Supporters view his stance as defending nonprofit integrity, while critics see it as sour grapes from a competitor whose own xAI is racing in the AI arena.
Regardless of the legal outcome, the case has spotlighted critical questions about trust, governance, and mission drift in the rapidly evolving AI industry. Musk’s willingness to fight on suggests this chapter is far from closed, with broader implications for how charitable organizations—and the tech giants born from them—operate in the future.
Elon Musk
NASA updated Artemis III and SpaceX’s role just got more complicated
SpaceX’s Starship is the key to NASA’s Moon plan and the timeline is already slipping.
SpaceX has been at the center of NASA’s Moon ambitions for five years, and the updated Artemis III plan recently released by NASA makes that relationship more visible than ever. In April 2021, NASA awarded SpaceX a $2.89 billion contract to develop the Starship Human Landing System, selecting it as the sole provider to land astronauts on the Moon under Artemis III. Blue Origin filed legal protests, lost, and eventually received its own contract, but SpaceX was always the program’s primary lander contractor.
The original plan called for Starship to land two astronauts on the lunar south pole. That mission slipped as Starship development ran behind schedule, and in February 2026, NASA officially revised the Artemis III architecture entirely. The mission will now remain in low Earth orbit and serve as a crewed rendezvous and docking test between the Orion spacecraft and both the SpaceX Starship HLS pathfinder and Blue Origin’s Blue Moon Mark 2 pathfinder, with the actual Moon landing pushed to Artemis IV in 2028.
What makes SpaceX’s position particularly significant is the direct line between this week’s Starship V3 launch and the Artemis timeline. The Starship HLS is essentially a modified version of the V3 upper stage, meaning SpaceX cannot realistically prepare a lander for a 2027 docking test until it has demonstrated that the base vehicle flies reliably at scale. Flight 12, targeting this week, is the first data point in that sequence.
NASA has spent nearly $7 billion on Human Landing System development since awarding contracts to SpaceX and Blue Origin in 2021 and 2023, and NASA administrator Jared Isaacman has indicated a desire to drive down costs going forward. As Teslarati reported, before Starship HLS can put anyone on the Moon it has to solve a problem no rocket has demonstrated at scale, which is refueling in orbit, requiring approximately ten tanker launches worth of propellant loaded into a depot before the lander has enough fuel to reach the lunar surface.
The Artemis III mission described by NASA is essentially a stress test for every system that needs to work before any of that happens.
SpaceX has gone from a launch contractor to the single most critical hardware provider in America’s return-to-the-Moon program. With an IPO targeting a $1.75 trillion valuation and Elon Musk’s compensation tied directly to Mars colonization, the pressure on every Starship milestone between now and 2028 has never been higher.
Tesla is continuing to refine and improve its Robotaxi program from A to Z, and it is now going to make some sweeping changes to the smartphone app portion of the suite.
The company is aiming to make some sweeping changes with the release of Robotaxi app version 26.4.5, which was recently decompiled by Tesla App Updates on X. The update reveals significant new code, focused on remote operations, safety protocols, and seamless autonomous ride-hailing.
These improvements evidently signal Tesla’s preparations for scaling unsupervised Cybercab deployments, particularly the steering wheel-less variants spotted in production. The enhancements emphasize providing a reliable experience that gives passengers support when needed, along with operational efficiency.
Version 26.4.5 of the Robotaxi app has been de-compiled and we’ve got some interesting things added this update (https://t.co/jInbED7fOv):
– Remote Operator Voice Calls 📞
– Proactive Remote Assistance 🤖
– Manual Override + Remote Start for wheel-less Cybercabs 🎮
-…
— Tesla App Updates (iOS) (@Tesla_App_iOS) May 16, 2026
Remote Operator Voice Calls
One standout addition is support for remote operator voice calls. The app now includes a dedicated native voice-communication system linking passengers directly to Tesla teleoperators via the vehicle’s cabin microphone and speakers.
This feature allows real-time assistance during rides, addressing issues like navigation questions or comfort adjustments without disrupting the autonomous journey. It builds on existing support protocols, making human intervention more accessible and intuitive.
Proactive Remote Assistance
The update introduces proactive remote assistance capabilities. Rather than waiting for passenger-initiated requests, the system can anticipate and offer help based on monitored conditions.
This might include something like suggesting route changes, climate adjustments, or addressing potential delays. By integrating AI-driven monitoring with human oversight, Tesla aims to deliver a smoother, more attentive experience that exceeds traditional ride-sharing services.
Manual Override and Remote Start for Steering Wheel-less Cybercabs
A key highlight for the wheel-less Cybercab fleet is manual override plus remote start functionality. Fleet operators and technicians can now temporarily take control or remotely start vehicles lacking steering wheels. This is crucial for lower-speed maneuvers, such as getting vehicles from tight parking situations or even performing maintenance.
Controls are strictly limited for safety–typically to speeds under 2 MPH–ensuring these interventions remain emergency measures only.
Tesla is adding a secure “Enable Manual Drive” mode that will allow those fleet operators or others to take control temporarily.
Additionally, a Remote Start feature, which authorizes an empty vehicle to begin a driverless ride alone.
Ride-Hailing and Dispatch Features
Ride dispatch has been enhanced with soft-matching and multi-stop support. The app can intelligently pair riders with available Cybercabs while accommodating multiple destinations in a single trip.
This optimizes fleet utilization, reduces wait times, and improves efficiency for shared rides. Soft-matching likely considers factors like proximity, rider preferences, and vehicle availability for better user satisfaction.
Rider-Cabin Sync, Real-Time Routing
New synchronization tools allow the rider’s app to mirror and control cabin settings like seating, climate, and entertainment directly from their phone. Real-time routing updates adapt dynamically to traffic or road conditions, while dynamic safety monitoring continuously assesses the environment.
The app can now push updates directly to the main screen, enabling Center Display Control. Additionally, there is a dedicated navigation protocol sharing the exact coordinates of road closures and construction, which could prevent the car from getting stuck and needing manual override.
These features create a cohesive, responsive experience where the vehicle and app work in harmony.
Kill Switch
A high-security command lets Tesla completely freeze a vehicle’s ability to drive. This would take the vehicle out of the Robotaxi fleet for any reason Tesla sees fit, and would not allow it to be put into gear even with the correct equipment, like valid keys.
Elon Musk breaks silence on OpenAI trial decision
NASA updated Artemis III and SpaceX’s role just got more complicated
