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.
Elon Musk
Elon Musk’s Boring Company opens Vegas Loop’s newest station
The Fontainebleau is the latest resort on the Las Vegas Strip to embrace the tunneling startup’s underground transportation system.
Elon Musk’s tunneling startup, The Boring Company, has welcomed its newest Vegas Loop station at the Fontainebleau Las Vegas.
The Fontainebleau is the latest resort on the Las Vegas Strip to embrace the tunneling startup’s underground transportation system.
Fontainebleau Loop station
The new Vegas Loop station is located on level V-1 of the Fontainebleau’s south valet area, as noted in a report from the Las Vegas Review-Journal. According to the resort, guests will be able to travel free of charge to the stations serving the Las Vegas Convention Center, as well as to Loop stations in Encore and Westgate.
The Fontainebleau station connects to the Riviera Station, which is located in the northwest parking lot of the convention center’s West Hall. From there, passengers will be able to access the greater Vegas Loop.
Vegas Loop expansion
In December, The Boring Company began offering Vegas Loop rides to and from Harry Reid International Airport. Those trips include a limited above-ground segment, following approval from the Nevada Transportation Authority to allow surface street travel tied to Loop operations.
Under the approval, airport rides are limited to no more than four miles of surface street travel, and each trip must include a tunnel segment. The Vegas Loop currently includes more than 10 miles of tunnels. From this number, about four miles of tunnels are operational.
The Boring Company President Steve Davis previously told the Review-Journal that the University Center Loop segment, which is currently under construction, is expected to open in the first quarter of 2026. That extension would allow Loop vehicles to travel beneath Paradise Road between the convention center and the airport, with a planned station located just north of Tropicana Avenue.
News
Tesla leases new 108k-sq ft R&D facility near Fremont Factory
The lease adds to Tesla’s presence near its primary California manufacturing hub as the company continues investing in autonomy and artificial intelligence.
Tesla has expanded its footprint near its Fremont Factory by leasing a 108,000-square-foot R&D facility in the East Bay.
The lease adds to Tesla’s presence near its primary California manufacturing hub as the company continues investing in autonomy and artificial intelligence.
A new Fremont lease
Tesla will occupy the entire building at 45401 Research Ave. in Fremont, as per real estate services firm Colliers. The transaction stands as the second-largest R&D lease of the fourth quarter, trailing only a roughly 115,000-square-foot transaction by Figure AI in San Jose.
As noted in a Silicon Valley Business Journal report, Tesla’s new Fremont lease was completed with landlord Lincoln Property Co., which owns the facility. Colliers stated that Tesla’s Fremont expansion reflects continued demand from established technology companies that are seeking space for engineering, testing, and specialized manufacturing.
Tesla has not disclosed which of its business units will be occupying the building, though Colliers has described the property as suitable for office and R&D functions. Tesla has not issued a comment about its new Fremont lease as of writing.
AI investments
Silicon Valley remains a key region for automakers as vehicles increasingly rely on software, artificial intelligence, and advanced electronics. Erin Keating, senior director of economics and industry insights at Cox Automotive, has stated that Tesla is among the most aggressive auto companies when it comes to software-driven vehicle development.
Other automakers have also expanded their presence in the area. Rivian operates an autonomy and core technology hub in Palo Alto, while GM maintains an AI center of excellence in Mountain View. Toyota is also relocating its software and autonomy unit to a newly upgraded property in Santa Clara.
Despite these expansions, Colliers has noted that Silicon Valley posted nearly 444,000 square feet of net occupancy losses in Q4 2025, pushing overall vacancy to 11.2%.
In Pennsylvania, we got between 10 and 12 inches of snow over the weekend as a nasty Winter storm ripped through a large portion of the country, bringing snow to some areas and nasty ice storms to others.
I have had a Model Y Performance for the week courtesy of Tesla, which got the car to me last Monday. Today was my last full day with it before I take it back to my local showroom, and with all the accumulation on it, I decided to run a cool little experiment: How long would it take for Tesla’s Defrost feature to melt 8 inches of snow?
Tesla’s Defrost feature is one of the best and most underrated that the car has in its arsenal. While every car out there has a defrost setting, Tesla’s can be activated through the Smartphone App and is one of the better-performing systems in my opinion.
It has come in handy a lot through the Fall and Winter, helping clear up my windshield more efficiently while also clearing up more of the front glass than other cars I’ve owned.
The test was simple: don’t touch any of the ice or snow with my ice scraper, and let the car do all the work, no matter how long it took. Of course, it would be quicker to just clear the ice off manually, but I really wanted to see how long it would take.
Tesla Model Y heat pump takes on Model S resistive heating in defrosting showdown
Observations
I started this test at around 10:30 a.m. It was still pretty cloudy and cold out, and I knew the latter portion of the test would get some help from the Sun as it was expected to come out around noon, maybe a little bit after.
I cranked it up and set my iPhone up on a tripod, and activated the Time Lapse feature in the Camera settings.
The rest of the test was sitting and waiting.
It didn’t take long to see some difference. In fact, by the 20-minute mark, there was some notable melting of snow and ice along the sides of the windshield near the A Pillar.
However, this test was not one that was “efficient” in any manner; it took about three hours and 40 minutes to get the snow to a point where I would feel comfortable driving out in public. In no way would I do this normally; I simply wanted to see how it would do with a massive accumulation of snow.
It did well, but in the future, I’ll stick to clearing it off manually and using the Defrost setting for clearing up some ice before the gym in the morning.
Check out the video of the test below:
❄️ How long will it take for the Tesla Model Y Performance to defrost and melt ONE FOOT of snow after a blizzard?
Let’s find out: pic.twitter.com/Zmfeveap1x
— TESLARATI (@Teslarati) January 26, 2026
Elon Musk’s Boring Company opens Vegas Loop’s newest station
Tesla leases new 108k-sq ft R&D facility near Fremont Factory
