News
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.
Investor's Corner
Elon Musk drops a Thanksgiving hint about Starship’s biggest test yet
Elon Musk says Starship Flight 15 will try to catch the ship itself, a first.
Elon Musk says SpaceX’s next Starship flight will try something nobody has done before, by catching the ship itself. Speaking to roughly 2,000 people at the X Takeover event at Giga Texas on Saturday, Musk said Flight 15 is about four to six weeks away and “probably launches a little bit before Thanksgiving, is my guess.”
That is a slip from earlier reporting, which had pointed to a launch as early as October 19. Musk explained why the date keeps moving. “We’re making a bunch of improvements to the rocket between every flight,” he said, adding that there are often hundreds, sometimes thousands, of small changes. This time the list is short, “but some of them take a fair bit of work and we’ve got to go inside the tank to make some of these changes.”
“We’re going to try to catch the ship, which is a super big deal,” Musk said. “If we do so, that’ll be the first time that there’s been full recovery of an orbital class rocket.” SpaceX has already caught the Super Heavy booster with the tower’s mechanical arms, and has talked about catching the ship since late 2025, but the upper stage has never been caught.
Musk also laid out what comes after. “The next big milestone would be to refly both the booster and the ship,” he said, describing a Flight 16 where “all parts of an orbital rocket are reflown.”
The reason SpaceX wants this comes down to cost and cadence. Every Starship ship so far has ended its flight in the ocean, and SpaceX expects most of those water landings to end in fireballs. A ship that returns to Starbase intact can be inspected and flown again. SpaceX’s IPO filing, says Starship V3 is designed to deliver 100 metric tons to orbit in a fully reusable configuration, that SpaceX aims to cut the cost to reach orbit by 99% or more versus the historical average, and that tower catches should allow “multiple launches per day.”
The payoff goes beyond cheaper launches. The next generation Starlink V3 satellites are too large for Falcon 9 and can only fly on Starship, which can carry up to 60 per flight. Flight 14 on September 28 deployed the first 26 of them after Starship reached orbit despite an early engine shutdown, as Teslarati reported. Musk blamed engine computer software, and said the heat shield “was extremely robust,” which he claimed in August had solved Starship’s biggest challenge.
NASA’s Moon plans depend on the same capability. NASA’s inspector general has described a lander mission that needs a propellant depot in low Earth orbit and more than 10 tanker flights, with SpaceX targeting one tanker launch every six days. That schedule only works if ships and boosters come back fast and fly again. Also, ship to ship propellant transfer has not been attempted yet.
One interesting hurdle yet to be explored is bringing the ship back to the launch site, with reentry over land, which will undoubtedly come with a lot of aviation safety reviews.
Lifestyle
Tesla’s mirrorless Cybercab will give riders a visibility upgrade
Tesla engineer confirms Cybercab update letting riders pull up rear and repeater cameras on demand.
Tesla is working on a Cybercab update that would let passengers pull up the vehicle’s rear and side cameras on demand, and the request came straight from a rider.
The exchange played out on X late Friday. Cybercab rider Dan Burkland shared photos of the two-seater’s cabin screen after an evening ride, praised the UI team’s work, and left one request: let riders open the rear and repeater cameras whenever they want, “especially for peace of mind.” Tesla UI software engineer Evan (@CarCoder) answered with two words: “In development.”
The Tesla UI team absolutely crushed it with the infotainment software. Nicely done @CarCoder!
One feature request: Allow folks to pull up the rear & repeater cameras on demand. This would be great especially for peace of mind. https://t.co/mNAOSLx6pE
— Dan Burkland (@DBurkland) October 10, 2026
The idea fits a pattern Teslarati has tracked since public rides began. Days after paid Cybercab service opened in Austin, Tesla sent riders a survey that asked them to rate the touchscreen, the app and the cabin, and to pick the features they wanted most. We reported on that survey in September, and a camera view is the kind of small software change Tesla can push quickly if riders keep asking.
It also speaks to something unique about the vehicle. With no steering wheel, no pedals and no driver, passengers have no mirror to check and no way to see behind them. The hardware is clearly built for camera awareness, from the repeater cameras to the rear camera. Letting a passenger look through those same cameras would give a nervous first time rider a way to confirm what is around the car.
The timing matters because the fleet is growing fast. Tesla’s Robotaxi account said on Saturday that more than 300 Cybercabs are now serving Austin, an eightfold increase in 30 days, and Tesla AI chief Ashok Elluswamy named Dallas as the next city. More cars and more cities mean more people riding in a driverless vehicle for the first time, which is exactly when small trust features carry weight.
For now, the feature is confirmed only as in development. If Tesla follows its usual pattern with Cybercab software, riders could see it appear in a point release without any announcement, and Teslarati will watch for it.
News
Tesla’s Cybercab fleet jumped 8x in a month, with Dallas up next
Tesla confirms its first official Cybercab fleet number as Austin scales fast and Dallas looms.
Tesla says more than 300 Cybercabs are now serving Austin, the first time the company has put an official number on its active Cybercab fleet. The figure came from the Robotaxi account on X on Saturday, which wrote that one month after launch the service had “scaled to 300+ Cybercabs serving Austin – an 8x increase in 30 days.”
Ashok Elluswamy, Tesla’s head of AI software, quoted the post with a line that carried the bigger news. “Two years since the 10/10 Cybercab WeRobot event, the cabs are everywhere in Austin now. Dallas soon,” he wrote. It is the first time Tesla has named the next city for public Cybercab rides.
One month after launch, we’ve scaled to 300+ Cybercabs serving Austin – an 8x increase in 30 days https://t.co/EagJy2JAsm
— Robotaxi (@robotaxi) October 10, 2026
Tesla opened Cybercab rides to the public in Austin on September 4, as Teslarati reported, a day after an invite only launch event. The ramp since then has been steep. Our September 28 report had the fleet at well over 100 units after availability jumped from 58 to 125 in a single week. On Thursday, Tesla added 150 Cybercabs to the Texas automated vehicle registry, lifting its registered count to 319 from 169. The first seven appeared on the registry on August 31.
RobotaxiTracker, a community site that counts vehicles from sightings and state records, listed 275 vehicles in unsupervised service in Austin on Saturday, 105 of them Cybercabs, which is well below Tesla’s figure. Tracker counts can lag official numbers, though Sawyer Merritt noted that Cybercab wait times in Austin stayed short on Saturday evening even with more than 2,000 fans in town for X Takeover.
Regulators are watching the rollout. NHTSA opened an audit query into Tesla’s certification that the Cybercab meets federal safety standards, and sworn answers are due October 30. Tesla reports third quarter earnings on October 21, which gives the company a natural venue to define its fleet numbers and put a date on Dallas.
Elon Musk drops a Thanksgiving hint about Starship’s biggest test yet
Tesla’s mirrorless Cybercab will give riders a visibility upgrade
Tesla’s Cybercab fleet jumped 8x in a month, with Dallas up next
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