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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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Tesla is ending Cybertruck production

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Credit: diagnosticdennis/Instagram and @smile__no via Tesla Owners of Santa Clarita Valley/X

Tesla is ending Cybertruck production sometime in mid-2027, according to CEO Elon Musk.

Musk made the announcement on X last night, which came as a shock to many. He said that the Cybertruck will end production “to make room for increased Cybercab production” at Gigafactory Texas.

It is a huge blow to the fans of Tesla who have come to love the Cybertruck and identify with it as a symbol of their fandom. It has been the best-selling electric pickup, but it has had an underwhelming sales performance in terms of what was expected. This is mostly due to Tesla not meeting the prices it planned to offer the Cybertruck, as its unveiling and actual release were four years apart.

Overall, the responses were mixed. Some fans understood the move toward Cybercab production, especially as Tesla is truly pushing the autonomous future through its Robotaxi platform. However, others did not understand it.

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“Damn, how many Cybercabs do you guys need?” one response read. Another said it was “Sad but understandable.”Even analyst Gary Black had responded to the news, stating he hoped Tesla planned to replace it with a traditional pickup design.

It doesn’t seem like that will be the case.

Tesla is so hell-bent on delivering autonomy and eventually providing a driverless service that owning a car seems like an arbitrary idea, according to their thesis. Instead, Cybercabs will be available to pick you up and drop you off on demand, safely, without any human help.

As a result, Tesla has thinned its lineup considerably, and one can only ask where the vehicle lineup goes from here. Eventually, it seems like Cybercab could be the only vehicle that Tesla will sell.

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SpaceX’s next Starship flight set to make history on Friday the 13th

SpaceX is targeting Friday, November 13 for Starship Flight 15 and its first ship catch.

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SpaceX is targeting Friday, November 13 for Starship Flight 15, the mission the company plans to use for its first attempt at catching the ship itself with the launch tower.

SpaceX Vice President of Launch Kiko Dontchev shared the date on stage at the UP.Summit on Thursday, according to Ars Technica’s Eric Berger, who was in attendance. It is the first launch target to come directly from a SpaceX executive. Until now, the public schedule had relied on FAA air traffic planning slides, which listed Flight 15 for no earlier than November 8 and later November 12. SpaceX has not posted an official mission page yet, and no launch time has been shared.

The date lands inside the window Elon Musk sketched out last month. Speaking at Giga Texas on October 10, Musk said the flight would “probably launch a little bit before Thanksgiving,” as Teslarati reported. On SpaceX’s third quarter earnings call ten days later, he confirmed that Flight 15 would try to catch both the Super Heavy booster and the ship, and put the odds of a successful ship catch at “more likely than not.” SpaceX also aired an animation of the maneuver during that webcast, showing the ship swinging vertical over Starbase before dropping into the tower’s chopsticks.

The hardware is ready. Booster 22 fired all 33 of its Raptor engines for a full duration static fire at Pad 2 on October 25. Ship 42 followed with a single engine burn simulating a deorbit maneuver on October 26 and a 60 second firing of all six engines the next day, according to NASASpaceflight. Ship 42 had already rehearsed the catch in September, when the Pad 2 arms lifted it into position and crews connected the quick disconnect arm while the vehicle hung from the tower.

The remaining hurdle is regulatory. The FAA’s Starship page does not yet list a Flight 15 license. SpaceX President Gwynne Shotwell said in October that, after “significant constructive engagement with the FAA,” she expects the license to cover a return to the launch site and a tower catch for both stages. Bringing the ship home means a reentry path that heads toward land, rather than ending over open ocean as every Starship flight so far has.

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SpaceX has caught Super Heavy three times, on Flights 5, 7 and 8, but the ship comes back from orbital velocity and has never been caught. Flight 14 on September 28 was the first Starship to reach orbit, deploying 26 Starlink V3 satellites before splashing down despite an early engine shutdown that Musk blamed on engine computer software.

Musk has called a successful ship catch “the first time that there’s been full recovery of an orbital class rocket,” and he has already named the step after it: a Flight 16 where both the booster and the ship fly again. NASASpaceflight reports that Ship 43, the next vehicle in line, is set for static fire testing in December.

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EVgo taps Tesla Superchargers for mass charging expansion

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Credit: EVgo

EVgo has tapped Tesla Superchargers for its most recent efforts to expand its charging presence in the United States, a move that seems logical based on the effectiveness of the automaker’s own infrastructure.

EVgo opened its first Supercharger site in Illinois, a 12-stall station near downtown Chicago at 3145 South Ashland Avenue in the Riverside Square & River’s Edge center, right beside a grocery store. This marks the start of the company’s plan to deploy hundreds of Supercharger stalls across the United States, primarily at grocery-anchored Regency Centers properties where drivers can shop, eat, or run errands while they charge.

The new location uses Tesla’s Magic Dock technology so both NACS and CCS vehicles can plug in natively without drivers needing to carry their own adapters. Peak power reaches 325 kW at this site, with pricing set between $0.25 and $0.35 per kWh depending on the hour—the same rate for Tesla and non-Tesla drivers.

The stalls also appear in Tesla’s in-car navigation and Trip Planner, making them easy for Tesla owners to find and route to. Illinois has seen EV registrations rise nearly 60 percent over the past two years, and EVgo’s broader network has experienced more than 700 percent growth in charging demand over three years, so the timing fits the market’s trajectory.

Choosing Tesla hardware through the Supercharger for Business program turns out to have been a smart, practical move.

Tesla’s V4 stalls and cabinets deliver high, reliable power with a proven track record of strong uptime, while Magic Dock delivers true dual-standard compatibility in one package. Because the sites show up in Tesla’s navigation tools, EVgo instantly gains visibility among millions of existing Tesla drivers, which should raise utilization and help the company double its addressable market as more vehicles adopt NACS. EVgo still owns the stations and sets pricing, yet benefits from Tesla’s established hardware, longer cables, and operational support.

The result is faster, lower-risk infrastructure expansion that serves every EV driver—Tesla or otherwise—with convenient, high-power charging at everyday retail locations. For drivers, that means fewer adapters, more predictable stops, and a denser network just as electric vehicles become everyday transportation.

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