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Tesla’s Neural Network adaptability to hardware highlighted in new patent application

(Credit: Tesla Driver/YouTube)

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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.

Credit: Tesla/USPTO

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.

Credit: Tesla/USPTO

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.

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Accidental computer geek, fascinated by most history and the multiplanetary future on its way. Quite keen on the democratization of space. | It's pronounced day-sha, but I answer to almost any variation thereof.

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Elon Musk

OpenAI cites distrust of SpaceX in decision to drop Cursor partnership

OpenAI will cut SpaceX-owned Cursor’s model access in November, citing Musk’s history of broken contracts.

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OpenAI, the company behind ChatGPT, announced late Friday that it is ending its partnership with Cursor, cutting off the coding tool’s access to its models on November 12. The move comes two weeks after SpaceX completed its $60 billion acquisition of Cursor’s parent company, Anysphere, folding the popular AI coding assistant into Elon Musk’s growing SpaceXAI division.

In a post on its website, OpenAI said the decision came down to trust, not technology. “We cannot be confident that SpaceX will use our technology within our terms of service, based on our experience with Elon Musk’s companies violating contracts,” the company wrote. OpenAI pointed to two specific incidents: X, now part of SpaceX, allegedly breaking the terms of an existing OpenAI contract after Musk bought Twitter.

That lawsuit is the backdrop for all of this. Musk cofounded OpenAI in 2015, left the board in 2018, and sued Sam Altman and Greg Brockman in 2024, arguing they abandoned the company’s nonprofit mission for profit. A federal jury sided with OpenAI in May, finding Musk waited too long to sue rather than ruling on the merits of his claims. Musk said at the time he would appeal to the Ninth Circuit, calling the outcome a “calendar technicality” rather than a real judgment.

Elon Musk breaks silence on OpenAI trial decision

SpaceX’s interest in Cursor predates that verdict by weeks. The company first struck a deal with Cursor in April, securing an option to acquire it for $60 billion or pay $10 billion for joint development work instead. As Teslarati reported at the time, the logic was straightforward: Cursor was paying retail prices to Anthropic and OpenAI, two of its most direct competitors, every time a developer used its product, while SpaceX had idle capacity on its Colossus supercomputer, roughly the equivalent of a million Nvidia H100 GPUs, that Cursor could use to train its own models instead. SpaceX exercised the option in June, days after its own IPO, and the deal closed in mid-August.

Once it closed, Musk moved fast. On an all-hands call with more than 1,000 Cursor employees, he reportedly told staff that SpaceXAI’s Grok was playing catchup in the AI race, unlike Tesla and SpaceX in their own markets, and singled out Anthropic as the company to catch. Cursor CEO Michael Truell now reports directly to Musk inside SpaceXAI.

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Elon Musk admits he was ‘clearly wrong’ about Anthropic

Losing OpenAI’s models leaves Cursor leaning harder on Anthropic’s Claude, which has its own compute agreement with SpaceX, and on Cursor’s in-house Composer model, the one SpaceX’s compute was supposed to accelerate in the first place. OpenAI framed the November deadline as maximum notice under its contract, and said it wants to “go above and beyond” to help developers through the transition. Whether Anthropic makes the same call is now the open question in AI coding.

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Tesla Theater might be getting plenty more streaming platforms

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Credit: YouTube/Tesla Theater

The in-car Tesla Theater is among the most unique features available within the cars. When charging, parked, camping, or just hanging out, vehicle occupants can access a variety of streaming platforms on the large center screen, helping keep them entertained during downtime.

However, the Theater might be getting plenty more streaming platforms, something that owners have requested for some time.

Tesla owners recently discovered that visiting Apple TV in the vehicle browser can launch a fullscreen interface that looks and behaves like a dedicated application rather than an ordinary webpage:

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The experience drops the usual address bar and browser chrome, presenting catalogs, continue watching rows, and playback controls in the same window Tesla Theater already uses for its listed services. Independent testers soon found similar treatment for HBO Max, Paramount+, Peacock, Disney+, and Prime Video when those sites are opened from the car browser.

This shift is a plausible early signal that Tesla is widening Theater support without a formal software note. Theater has long been a set of web views rather than native applications, so recognizing extra domains and stripping the browser frame is a small server-side change that can expand the catalog quickly.

Owners still lack permanent Theater icons for the newly recognized services, and video remains limited to Park, yet the smoother launch is a meaningful step toward a broader lounge while charging.

Tesla Theater arrived with software version 10 in September 2019. The first video services were Netflix, YouTube, and Hulu, available only while parked and originally tied to WiFi. Spotify arrived in the same era as music rather than Theater video. Disney+ joined officially in July 2021 with the 2021.24 update, giving owners another major catalog on the center screen. Twitch and TikTok later appeared among the default Theater tiles, and Tesla Tutorials remained a persistent educational tile.

Not every addition stayed put. In December 2023, a Holiday software build removed the Disney+ tile for many United States owners after a public dispute involving advertising on X. Hulu stayed visible even though Disney owned it. Visiting disneyplus.com in the browser often restored the tile, which suggested the removal was a recognition list change rather than a complete block. Owners have also reported occasional blank Theater grids after updates, usually fixed by language toggles, resets, or later firmware.

Tesla axes Disney+ from vehicles with Musk-Iger rivalry, but there’s a workaround

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Code archives from 2024 listed many unused source names, including Apple TV and Prime Video, that never became official icons, which now looks like groundwork for the current fullscreen browser behavior.

Now that this hint toward an expanded Theater experience has been recognized, Tesla could follow through with these additional shortcuts as a sign that more streaming platforms are available in Teslas than ever before.

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Tesla Semi’s biggest adoptee gives an update on production timeline

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Credit: Tesla

Tesla recently received its largest order for the all-electric Semi from Einride, a Swedish transport service, for 500 units, a groundbreaking invoice to receive before the first deliveries begin.

Even more remarkable, Einride CEO Roozbeh Charli said in a recent interview that he expects his company to take delivery of all 500 — the entire order — before the end of 2027. He even expects to have 75 Tesla Semi units in the Einride fleet before the end of this year.

Charli said the Tesla partnership was part of a broader push, along with its earlier partnership with Amazon. Einride is assisting Amazon with the use of its Saga AI platform, which helps eliminate questions about budgeting and forecasting for logistics companies.

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The Semi, as well as Tesla’s production and subsequent delivery of the units to Einride, will help the company “to have a good supply of vehicles that we can deploy on the [Saga AI] platform,” Charli said. “Tesla is also a relationship we’ve had for a while, and as the Tesla Semi deliveries are firming up, we decided to do a larger commitment to that and deploy that on our platform.”

In its initial announcement, Einride said it anticipated taking delivery of the trucks over the next two years, but now it appears the company is expecting all 500 units within the next 16 months.

Tesla Semi gets its largest order yet

Built at a dedicated factory in Sparks, Nevada, the Tesla Semi has been perhaps the biggest and most intensive testing process the company has ever had for a single vehicle model. For the past several years, Tesla has been working with many companies, most notably Frito-Lay and PepsiCo, to gain knowledge on the performance on regional routes.

Tesla plans to launch the Semi officially on September 24, five months after production started ramping.

Additionally, drivers have said they are happy about the Semi’s performance and that its numerous safety and productivity features have made their jobs and routes much easier.

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