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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

SpaceX just combined Grok, Cursor, and X into one mega plan

SpaceXSI merges Grok, Cursor, and X Premium into one plan, raising questions for Tesla owners.

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SpaceX Super Intelligence has rolled out The X Subscription, a single plan that combines Grok, Grok Bot, Cursor, and X Premium.

There are five levels, including a free plan that includes daily Grok access and a starter allowance for Cursor’s coding agents. Plus is $8 per month, Premium is $30, Super is $100, and Ultra is $200. Usage scales as you move up, with Premium offering four times the Plus allowance, Super 15 times, and Ultra 50 times. Annual billing brings the prices down a bit further, with Premium at $300 per year.

The $30 Premium tier is where SpaceXSI says it packs the benefits of SuperGrok, Cursor Pro, and X Premium+, which previously added up to $90 per month. Grok Bot, the agent that handles tasks like ordering food or managing a calendar, is included from Premium upward but not on Plus. Paid plans share one weekly usage pool across Grok and Cursor, and each plan includes at least twice the coding usage of the comparable Cursor plan. Third party models in Cursor remain available on Premium and above, but they are billed separately at API list prices.

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That last detail matters because of what has happened around Cursor this year. SpaceX exercised its option to buy the company for $60 billion in June, and the deal closed in August. Weeks later, OpenAI said it will cut Cursor’s access to its models on November 12. Bundling Cursor with Grok usage gives SpaceXSI a reason to steer developers toward its own models.

Tesla integrates Grok Bot into its vehicles for the ultimate personal assistant

For Tesla owners, the connection is Grok Bot. Tesla brought it into its vehicles last month, and at that point access inside the car was limited to SuperGrok Heavy subscribers. Grok Bot is now enabled across every Cybercab and the rest of the Model Y Robotaxi fleet. Neither SpaceXSI nor Tesla has said how the new plans change inside the car access for owners, or whether a $30 Premium subscription now covers Grok Bot in a personal Tesla. That is the question owners will want answered first.

The company is also changing its name along the way. The rollout follows the rebrand Musk announced on October 4, when he said SpaceXAI would become SpaceXSI, and the plan page now carries that branding.

The X Subscription is available to new customers starting now, and SpaceXSI says it will reach everyone globally over the next few days. Existing SuperGrok, Cursor, and X Premium subscribers do not have to switch. The option to move will appear gradually in billing settings, with a prorated refund for the unused time on the old plan. Switching is permanent once the accounts are unified, and old plans are closed to new sign ups.

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Energy

Taiwan power firm bets big on Tesla Megapacks as AI data center thirst grows

Taiwan’s Apollo Power orders 260 Tesla Megapacks, betting AI data centers will need more electricity.

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Concept render of Tesla Megapack farm supporting an AI Data Center in Taiwan
Concept render of Tesla Megapack farm supporting an AI Data Center in Taiwan

A Taiwanese power company has ordered 260 Tesla Megapack 2XL units, roughly 1GWh of storage, betting that electricity rather than chips will decide how fast AI data centers come online. Apollo Power signed the contract with Tesla’s Taiwan energy arm on October 8, according to the company’s filing with the Taiwan stock exchange.

The filing says the units are meant for behind the meter storage and resilient grid projects, with delivery in batches from the end of 2027 and sites operating in 2028. Apollo and Tesla did not disclose a price, citing a confidentiality agreement. Apollo plans to pay for the equipment through a cash capital increase and bank financing, and it noted the purchase is not revenue and does not mean it holds firm orders from its partners.

Biggo reported that only about 33 units are under signed customer contracts, with roughly 150 more in negotiation. The same report put total project investment near NT$130 billion, but that figure includes installation work, with the equipment itself making up about 40 to 50 percent. In other words, a large share of this order is Apollo reserving supply ahead of demand. Apollo’s chairman told local media global large storage supply is tight, which is why the company locked in the units early, according to Yahoo Taiwan Finance.

Tesla Taiwan partners with Costco to sell vehicles

Apollo also launched an AI data center and grid resilience alliance with Phison, Gigabyte and Shihlin Electric. The pitch rests on a pilot at Phison’s Zhunan plant, where Apollo and Tesla Energy Taiwan installed grid forming Megapack 2XLs in June. Tesla Energy Taiwan general manager Sun Hsiao-Han said the project went from demo to 1GWh in four months, and that Tesla Energy has deployed more than 50GWh worldwide.

Taiwan’s cabinet has approved amendments that would require large energy users to install their own generation and storage, which gives enterprise storage a regulatory tailwind.

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The deal fits a pattern Teslarati has tracked. Tesla’s Megablock targets 1GWh commissioned in 20 business days, a pitch aimed squarely at fast moving data center builds. Megapacks already back xAI’s Colossus in Memphis and a 400MW AI campus in Brazil. Sun Media adds that Megapack 2XL was named among the first products in Nvidia’s DSX Ready qualification for battery storage in AI factories.

Deliveries are more than a year away, so the real test is how much of that 260 unit order turns into signed customer contracts.

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Lifestyle

Tesla Cybercab and Robotaxi’s real advantage won’t be the ride service

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Concept art of a Tesla Cybercab in Las Vegas Strip as rendered via Grok

For a century, the car has asked the same thing of its owner, which is basically to pay attention. Even the best ride-hailing app like Uber or Lyft only moved the problem into someone else’s hands. You stopped driving, but you still sat in a stranger’s car, while half listening, and wondering whether to take a phone call in the car without being rude. The Cybercab has no wheel, no pedals and no driver. With Grok @bot now live inside it, it becomes something else entirely, and I think that matters more than the fleet count that everyone is tracking.

Grok @bot is an agent, not a voice assistant. A rider signs in once, and from then on can say what they need and watch it happen. Order dinner from a favorite restaurant. Fill the grocery cart. Move money, answer email, adjust a calendar, push a work project forward. Tesla engineer Yun-Ta Tsai confirmed it is enabled across every Cybercab and the rest of the Model Y fleet, and Tesla’s own pitch is that Full Self-Driving handles the commute while Grok handles the errands.

Think about what that does to a thirty minute ride. Uber sells you a trip, while Waymo sells you the same trip in a more private setting. Tesla is selling the thirty minutes themselves, returned to you with an assistant attached. Errands that used to eat a Saturday get done between pickup and drop off. The ride stops being dead time between two places and becomes a place of its own.

Tesla integrates Grok Bot into its vehicles for the ultimate personal assistant

Best of all, your Bots follow you into any Cybercab, and presumably your own Tesla, then logs you out automatically when you step out. Anyone can bolt a chatbot onto a screen, but much harder to own the vehicle, the autonomy stack and the assistant at once. It also quietly ties SpaceX’s Super Intelligence business to Tesla’s fleet, after Tesla converted its xAI stake into SpaceX equity. The relationship between those two companies is getting harder to describe as separate.

This is also where the hard questions start, because an agent that can spend your money in a vehicle other people also ride in needs some answers. How does it handle a voice it shouldn’t trust? What gets recorded, who can see it, and for how long? What happens when a rider leaves halfway through a task?

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If Tesla gets those answers right, the scoreboard changes. We have been counting Cybercabs and wait times. The more telling number may be what riders accomplish per trip. That is data almost no one else will ever have, and it is the real reason to watch Grok @bot.

What do you think? Leave me a comment.

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