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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.

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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.

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

Tesla’s Robotaxi dreams just took a massive step toward reality

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Credit: Tesla

Tesla’s dreams of operating a fully autonomous ride-hailing platform just took a massive step toward reality, as two separate events have indicated the company is perhaps closer than ever to achieving self-driving as a product.

On Thursday, Tesla was granted authorization by the State of Texas to operate driverless vehicles in a commercial manner. On May 28, Senate Bill 2807, passed by the 89th Texas Legislature, took effect after being passed back on September 1, 2025.

The bill establishes a statewide regulatory framework requiring authorization from the Texas Department of Motor Vehicles for companies to operate automated vehicles commercially on Texas roads.

This covers driverless, or SAE Level 4+, operations for passenger transport, meaning Robotaxi, or freight.

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Tesla and other companies can self-certify their vehicles and tech as long as they:

  • Operate in compliance with Texas traffic laws
  • Maintain proper registration, title, and insurance
  • Use compliant automated driving systems
  • Record onboard activity and handle system failures and glitches safely.

The new authorization, which was first reported by James Stephenson on X, allows companies to utilize their own processes to determine if their vehicles are ready to operate without drivers.

It is a rule that expedites the entire approval process, keeping agencies out of a usually long, lengthy, and frustrating task that is essential to technological advancements. It essentially means Tesla can launch commercial Robotaxi operations at this point.

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On the very same day, Tesla continued the momentum as CEO Elon Musk shared a video of Cybercab units autonomously driving off the property at Gigafactory Texas. This is a major step in the story of the Cybercab.

Mass production of the Cybercab started at Giga Texas in April, and it is already heading out of the factory on its own.

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These two major events mark a drastic step forward in Tesla’s progress toward Cybercab and the permissions it needs to operate a self-driving ride-hailing service. Tesla is now able to operate autonomously under Texas law by self-certifying, and with the potentially imminent rollout of Cybercab, Tesla’s autonomous dreams are starting to take serious shape.

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Elon Musk

The Tesla and SpaceX merger everyone is talking about is quietly building

Tesla and SpaceX may be closer to merging than Wall Street or either company is admitting.

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Elon Musk has reportedly discussed merging Tesla and SpaceX with people close to him, according to CNBC, which cited sources familiar with the conversation. Tesla employees have long expected such a transaction and the topic is openly discussed internally, according to internal sources. With SpaceX is days away from kicking off its Wall Street roadshow for what could be the largest IPO in market history, this would be the first time the company will have public market currency to execute a stock-for-stock deal with Tesla.

The financial logic for a merger would make sense. A combined SpaceX and Tesla would create a conglomerate spanning rockets, satellites, electric vehicles, AI infrastructure, and energy storage valued at roughly $3.35 trillion to $3.6 trillion based on SpaceX’s IPO target range and Tesla’s current market capitalization. The two companies are already more intertwined than most people realize. SpaceX bought $697 million worth of Tesla Megapack systems for xAI data centers and $131 million worth of Cybertrucks. Tesla invested $2 billion in xAI, which subsequently merged with SpaceX. Past transactions also include Tesla selling solar equipment and parts to SpaceX, and SpaceX helping with Cybertruck materials.

Will Tesla join the fold? Predicting a triple merger with SpaceX and xAI

Musk himself signaled where this was heading in November 2025 when he posted on X, “My companies are, surprisingly in some ways, trending towards convergence.” Tesla and SpaceX announced a joint semiconductor fabrication facility in Austin called Terafab on the Gigafactory Texas campus, covering two advanced chip factories, with one serving Tesla’s AI needs for vehicles and Optimus robots, the other targeting space-based data centers under SpaceX’s infrastructure vision.

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Wedbush analyst Dan Ives places the probability of a merger at 80% to 90% with a target completion in the first half of 2027. The mechanics of a deal became possible the moment SpaceX filed its S-1. Legal experts said a merger likely would not spark antitrust issues but would raise concerns among shareholders in each company, with questions around which company would be the parent, how a stock swap would take place, and who determines the appropriate price. Musk holds about 20% of Tesla’s equity but controls 85.1% of SpaceX’s voting power through a super-voting share class, meaning he would largely be negotiating the terms with himself.

Elon Musk explains why he cannot be fired from SpaceX

Not everyone is convinced the timing is imminent. Traders on Kalshi place only 33% odds that a merger will happen before May 2027. The more immediate concern for Tesla shareholders is whether the SpaceX IPO pulls capital and Musk’s attention away from Tesla before any merger consolidates the upside for both.

What is clear is that the structural groundwork is already being laid. The Terafab announcement, the xAI merger, the shared supply chain, the cross-company balance sheet transactions, and now the IPO all point in the same direction. Whether the merger follows in 2027 or later, the two companies are already operating more like divisions of a single entity than independent competitors.

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Elon Musk

SpaceX to become America’s Military data backbone for missiles, drones, and warfighters

The Space Force just handed SpaceX $2.29 billion to build the military’s space internet backbone.

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US Golden Dome space defense system (Concept render by Grok)

The U.S. Space Force awarded SpaceX a $2.29 billion contract on May 26, 2026 to build the backbone of its Space Data Network, a satellite-based communications system designed to keep American military forces connected anywhere on Earth in real time. The contract is firm-fixed-price and requires SpaceX to deliver a fully operational prototype by the end of 2027.

In plain terms, the SDN Backbone is the plumbing behind the military’s space-based internet. It functions as a low Earth orbit satellite constellation providing robust, high-capacity, and low-latency data transport for the Joint Force, connecting sensors and weapons systems continuously, globally, and securely. Think of it as a private, hardened version of Starlink built specifically for battlefield communications, one that soldiers, ships, and aircraft can rely on even in contested environments where ground-based networks have been disrupted.

SpaceX is quietly becoming the U.S. Military’s only reliable rocket

The Space Force was direct about why SpaceX was selected. “The SDN Backbone leverages the best of commercial innovation and delivers a strong foundation for the SDN mission set — a huge benefit and enabler for our warfighters,” said USSF Col. Ryan Frazier.

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“We aren’t trading speed for scale; we are demanding both. By using rapid prototyping and Other Transaction Authorities, we are ensuring our advanced solutions are integrated and delivered to the warfighter as fast as possible,” added USSF Lt. Col. Fry, SDN Backbone system program manager.

The SDN Backbone will work alongside the Space Development Agency’s Transport Layer, with the two systems forming a unified open architecture to provide critical data transport for current and future Department of War missions.

As Teslarati has reported, this is not SpaceX’s first Space Force contract of 2026. In April, the Space Force awarded SpaceX $178.5 million to launch missile tracking satellites, and SpaceX is already embedded in the Golden Dome missile defense software group. The $2.29 billion SDN Backbone award puts SpaceX at the center of how the American military communicates in space, a position with direct implications for its reported $1.75 trillion IPO valuation as the company heads toward a public offering as early as June 2026.

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