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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.
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Tesla Robotaxi app update now tells riders if Cybercab is the better choice
Tesla’s Robotaxi app now shows ETAs, wait times and availability for Cybercab and Model Y.
Tesla has rolled out a new vehicle selection screen in its Robotaxi app, and it puts the numbers riders care about most in front of them before they book.
Version 26.11.0 of the app shows the estimated arrival time, the expected wait and current availability for each vehicle option on a single screen, according to a video shared by @gheeunit on X on November 7. Riders deciding between a Cybercab and a Model Y Robotaxi can now compare those figures side by side instead of picking a car first and learning how long it will take afterward.
Tesla first gave riders that choice on September 3, the day paid Cybercab rides began in Austin. The original version of the screen listed the Cybercab, which seats two, next to the Model Y, which seats four. A later build, 26.8.2, added a seating capacity indicator so groups knew which car would fit them. What it did not show was whether choosing the Cybercab meant standing on the curb a few extra minutes.
Newest version of @robotaxi app has a new vehicle selector UI for choosing between Cybercab and Model Y and shows you the fare for both simultaneously! https://t.co/7qoDQ0vACX — mantequilla 🧈 (@gheeunit) November 7, 2026
That question matters more now than it did two months ago. Tesla had 45 Cybercabs on the Texas DMV roster when rides started. By late October the state listed 573, alongside 631 Model Ys, and community trackers logged a record 1,576 Cybercab sightings across Austin on Halloween alone. With two large fleets sharing one service area, the closest car and the quickest pickup are not always the same vehicle.
Inline availability also changes what happens when demand spikes. If no Cybercab is free nearby, the rider sees that on the selection screen rather than after trying to book one.
For now the comparison is mostly an Austin feature. Riders in Dallas, Houston, Fort Worth and the Florida markets are still matched with Model Y vehicles, though Tesla said on its third quarter earnings call that Cybercab rides would launch in Dallas this month.
The update follows a steady run of smaller changes to the rider experience. Late last month Tesla brought a quiet mode that blacks out the cabin screen to Model Y Robotaxis after first testing it in the Cybercab, and it has stretched Austin service to run from 6 a.m. to 2 a.m.
The Cybercab side of that selection screen is about to get much busier. Elon Musk said this week that Tesla will wind down Cybertruck production at Gigafactory Texas around the middle of 2027 to make room for more Cybercab output, and Tesla has said it is aiming to get Cybercabs to customers by the end of this year.
Tesla has not published official release notes for version 26.11.0.
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.
Tesla will be winding down production of the Cybertruck at Gigafactory Texas around the middle of next year to make room for increased Cybercab production
— Elon Musk (@elonmusk) November 6, 2026
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.
“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.
Elon Musk
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.
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.
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.
Tesla Robotaxi app update now tells riders if Cybercab is the better choice
Tesla is ending Cybertruck production
