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.
Tesla has expanded its branded ‘For Business’ Supercharger program that it launched last year, as yet another company is using the platform to attract EV owners to its business and utilize a unique advertising opportunity.
Francis Energy of Oklahoma is launching four Superchargers in Norman, where the University of Oklahoma is located. The Superchargers, which are fitted with branding for Francis Energy, will officially open tomorrow.
It will not be the final Supercharger location that Francis Energy plans to open, the company confirmed to EVWire.
Back in early September, Tesla launched the new “Supercharger for Business” program in an effort to give businesses the ability to offer EV charging at custom rates. It would give their businesses visibility and would also cater to employees or customers.
“Purchase and install Superchargers at your business,” Tesla wrote on a page on its website for the new program. “Superchargers are compatible with all electric vehicles, bringing EV drivers to your business by offering convenient, reliable charging.”
The first site opened in Land O’ Lakes, Florida, which is Northeast of Tampa, as a company called Suncoast launched the Superchargers for local EV owners.
Tesla launches its new branded Supercharger for Business with first active station
The program also does a great job at expanding infrastructure for EV owners, which is something that needs to be done to encourage more people to purchase Teslas and other electric cars.
Francis Energy operates at least 14 EV charging locations in Oklahoma, spanning from Durant to Oklahoma City and nearly everywhere in between. Filings from the company, listed by Supercharge.info, show the company’s plans to convert some of them to Tesla Superchargers, potentially utilizing the new Supercharger for Business program to advertise.
Moving forward, more companies will likely utilize Tesla’s Supercharger for Business program as it presents major advantages in a variety of ways, especially with advertising and creating a place for EV drivers to gain range in their cars.
Tesla Cybercab is perhaps the most highly-anticipated project that the company plans to roll out this year, and as it is undergoing its testing phase in pre-production currently, there are some things to work through with it.
Over the weekend, an image of the Cybercab being loaded onto a tow truck started circulating on the internet, and people began to speculate as to what the issue could be.
Hmmmmmm… https://t.co/L5hWcOXQkb pic.twitter.com/OJBDyHNTMj
— TESLARATI (@Teslarati) January 11, 2026
The Cybercab can clearly be seen with a Police Officer and perhaps the tow truck driver by its side, being loaded onto, or even potentially unloaded from, the truck.
However, it seems unlikely it was being offloaded, as its operation would get it to this point for testing to begin with.
It appears, at first glance, that it needs assistance getting back to wherever it came from; likely Gigafactory Texas or potentially a Bay Area facility.
The Cybercab was also spotted in Buffalo, New York, last week, potentially undergoing cold-weather testing, but it doesn’t appear that’s where this incident took place.
It is important to remember that the Cybercab is currently undergoing some rigorous testing scenarios, which include range tests and routine public road operation. These things help Tesla assess any potential issue the vehicle could run into after it starts routine production and heads to customers, or for the Robotaxi platform operation.
This is not a one-off issue, either. Tesla had some instances with the Semi where it was seen broken down on the side of a highway three years ago. The all-electric Semi has gone on to be successful in its early pilot program, as companies like Frito-Lay and PepsiCo. have had very positive remarks.
The Cybercab’s future is bright, and it is important to note that no vehicle model has ever gone its full life without a breakdown. It happens, it’s a car.
Nevertheless, it is important to note that there has been no official word on what happened with this particular Cybercab unit, but it is crucial to remember that this is the pre-production testing phase, and these things are more constructive than anything.
Tesla analyst Andrew Percoco of Morgan Stanley teased the company’s dominance in its self-driving initiative, stating that its lead over competitors is “not even close.”
Percoco recently overtook coverage of Tesla stock from Adam Jonas, who had covered the company at Morgan Stanley for years. Percoco is handling Tesla now that Jonas is covering embodied AI stocks and no longer automotive.
His first move after grabbing coverage was to adjust the price target from $410 to $425, as well as the rating from ‘Overweight’ to ‘Equal Weight.’
Percoco’s new note regarding Tesla highlights the company’s extensive lead in self-driving and autonomy projects, something that it has plenty of competition in, but has established its prowess over the past few years.
He writes:
“It’s not even close. Tesla continues to lead in autonomous driving, even as Nvidia rolls out new technology aimed at helping other automakers build driverless systems.”
Percoco’s main point regarding Tesla’s advantage is the company’s ability to collect large amounts of training data through its massive fleet, as millions of cars are driving throughout the world and gathering millions of miles of vehicle behavior on the road.
This is the main point that Percoco makes regarding Tesla’s lead in the entire autonomy sector: data is King, and Tesla has the most of it.
One big story that has hit the news over the past week is that of NVIDIA and its own self-driving suite, called Alpamayo. NVIDIA launched this open-source AI program last week, but it differs from Tesla’s in a significant fashion, especially from a hardware perspective, as it plans to use a combination of LiDAR, Radar, and Vision (Cameras) to operate.
Percoco said that NVIDIA’s announcement does not impact Morgan Stanley’s long-term opinions on Tesla and its strength or prowess in self-driving.
NVIDIA CEO Jensen Huang commends Tesla’s Elon Musk for early belief
And, for what it’s worth, NVIDIA CEO Jensen Huang even said some remarkable things about Tesla following the launch of Alpamayo:
“I think the Tesla stack is the most advanced autonomous vehicle stack in the world. I’m fairly certain they were already using end-to-end AI. Whether their AI did reasoning or not is somewhat secondary to that first part.”
Percoco reiterated both the $425 price target and the ‘Equal Weight’ rating on Tesla shares.
Tesla expands its branded ‘For Business’ Superchargers
Tesla Cybercab ‘breakdown’ image likely is not what it seems
