News
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
Elon Musk handed Grok something no other AI company can get their hands on
Elon Musk says SpaceX will feed engineering data into Grok’s next model, avoiding restricted material.
Elon Musk said Tuesday that SpaceX will feed its internal engineering data into the next major training run for Grok, the AI model now folded into SpaceX following February’s merger. In a post on X, Musk wrote that SpaceX’s “massive corpus of world-class engineering data,” excluding anything restricted under U.S. arms export law, will be added during supplemental training of what he called the “2T run,” a reference to a roughly two trillion parameter model that would nearly double the parameters behind the latest Grok 4.5 that’s rolling out.
SpaceX’s massive corpus of world-class engineering data (excluding material blocked by ITAR) will be added during supplemental training of the 2T run.
This will dramatically improve Grok’s engineering capabilities. https://t.co/BbQEViFByn
— Elon Musk (@elonmusk) July 21, 2026
The excluded material that Musk is referring to would fall under the International Traffic in Arms Regulations (ITAR), which restricts export of technical data tied to defense and space hardware. That likely rules out propulsion specifics for Merlin and Raptor engines along with guidance and control details for SpaceX’s launch vehicles, but leaves manufacturing knowledge, materials science, and Starlink hardware design on the table.
The announcement extends a pattern that has been building since SpaceX’s Nasdaq debut in June, when the company went public with Grok and xAI’s Colossus supercomputer folded into the pitch to investors.
Days after that listing, SpaceX closed its $60 billion all stock acquisition of coding startup Cursor, giving xAI both enterprise software distribution and a stream of real world developer data to train on. Grok 4.5 launched July 8 running partly on that Cursor training data, with Musk describing it as roughly comparable to Anthropic’s Opus 4.7 but faster and cheaper to run.
Feeding SpaceX’s own engineering data into the next AI model follows the same logic Musk has applied across xAI’s sister companies. Tesla supplies real world driving data and manufacturing expertise, X supplies conversational data, and now SpaceX supplies aerospace engineering data built up since 2002.
Musk did not give a release date for the upcoming AI model, referred to elsewhere as Grok 4.6. He has said the two trillion parameter run is in its final training phase and expected to wrap this week.
Tesla has extended its Bay Area ride-hailing service to include pickups and drop-offs at San Francisco International Airport (SFO). The update, shared via the company’s official channels on July 21, allows users in the region to request rides directly to and from one of California’s busiest airports.
The expansion builds on Tesla’s secured limousine permit for SFO operations. Public records show the permit became effective March 20, 2026, and remains active through January 31, 2027. Tesla vehicles operating the service now display authorized limousine permits issued by the City and County of San Francisco.
Our Bay Area rideshare service now goes to SFO ✈️
— Tesla AI (@Tesla_AI) July 21, 2026
Tesla’s ride-hailing program in California relies on Model Y vehicles equipped with Full Self-Driving (Supervised) technology. Human safety drivers remain present in compliance with state regulations, distinguishing the service from fully driverless operations.
The Bay Area geofence covers a broad area spanning north of San Francisco to south of San Jose, offering extensive connectivity across the region.
UPDATE: Elon Musk reveals why Tesla didn’t say ‘Robotaxi’ upon California launch
This SFO addition follows earlier progress at other Bay Area airports. Tesla previously expanded service to San Jose Mineta International Airport (SJC) in late 2025. The company had engaged with SFO, SJC, and Oakland International Airport officials as early as September 2025 to secure necessary approvals for passenger transport.
The service provides a new option for travelers seeking electric, app-based transportation integrated with Tesla’s ecosystem. Rides are booked through Tesla’s dedicated ride-hailing application, which handles matching, routing, and payments. Pricing follows standard ride-hailing models, with potential adjustments based on distance, time, and demand.
Tesla’s California ride-hailing program launched in July 2025 with an initial invite-only rollout in the Bay Area. It started alongside operations in Austin, Texas, marking the company’s second major U.S. market.
The Bay Area remains a primary focus in California, with service centered on high-demand corridors connecting residential, commercial, and now major transportation hubs. This latest airport integration represents a practical step in Tesla’s broader mobility ambitions within the state.
Tesla has officially revealed its 2026 Summer Update, which comes with a variety of crazy new features, including Navigation fixes that owners have been wanting for months.
Tesla routinely releases a larger update with the Spring, Summer, Fall, and Winter updates, where it ships a variety of new features, bug fixes, and other additions to customer cars.
The 2026 Spring Update featured things like “Hey Grok” voice assistance, a redesigned self-driving app, Unreal Engine visual upgrades, and more.
🚨 TESLA’S SUMMER UPDATE FOR 2026 IS HERE:
Featuring:
✅ Self-Driving Stats in Mobile App
✅ Caraoke with Scoring
✅ Automatic Navigation
✅ Preferred Routes
✅ Set Arrival Energy from Mobile App
✅ Send Custom Wraps from Mobile App
✅ Rear Display Lock
✅ Other Improvements
🔌… https://t.co/C9IW3egEhH— TESLARATI (@Teslarati) July 21, 2026
Tesla’s Summer Release has about ten new features; we’ll show you each and detail them below:
New Grok Voice Commands
“Grok can now make phone calls, search and play music, adjust climate, open the glovebox, and answer questions about your Tesla.”
Self-Driving Stats in Mobile App
“View and share self-driving stats from the mobile app.”
Caraoke With Scoring
“Caraoke now scores your singing while in Park. High scores are saved to your Tesla profile.”
Automatic Navigation
“Automatic Navigation now adapts to your routine.
In addition to Home, Work, and upcoming calendar events, your vehicle can now suggest and route to places you visit regularly – like a school drop-off on the way to work, or the gym on the way home.”
Preferred Routes
“For a more personalized experience, navigation now prioritizes routes that you’ve taken before”
Set Arrival Energy from Mobile App
“Set your desired Arrival Energy from your phone.”
Send Custom Wraps from Mobile App
“Skip the USB drive and upload a custom wrap of your car from the mobile app. Instructions for creating a custom wrap here: https://github.com/teslamotors/custom-wraps.”
Rear Display Lock
“Kids can watch content on the rear screen, but only the front row can control it through the rear screen app.”
Other Improvements
- Find Superchargers by name when searching for a destination
- Add Apple Music songs to queue from search and artist page
- Set your preferred zoom level for the Self-Driving visualization
- Intro animations for new Model 3 and Y
Elon Musk handed Grok something no other AI company can get their hands on
Tesla expands ridesharing service in California to new hotspot
