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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.
Tesla teased its entrance into a new market with a confusing and what appeared to be cryptic message on the social media platform X.
The company has been teasing its entrance into several markets, including Africa, which would be a first, and South America, where it only operates in Chile.
In September, Tesla started creating active job postings for the Colombian market, hinting it would expand its presence in South America and launch in a new country for the first time in two years.
The jobs were related to various roles, including Associate Sales Manager, Advisors in Sales and Delivery, and Service Technicians. These are all roles that would indicate Tesla is planning to launch a wide-scale effort to sell, manage, and repair vehicles in the market.
Last night, Tesla posted its latest hint, a cryptic video that seems to show the outline of Colombia, teasing its closer than ever to market entry:
— Tesla North America (@tesla_na) November 12, 2025
This would be the next expansion into a continent where it does not have much of a presence for Tesla. Currently, there are only two Supercharger locations on the entire continent, and they’re both in Chile.
Tesla will obviously need to expand upon this crucial part of the ownership experience to enable a more confident consumer base in South America as a whole. However, it is not impossible, as many other EV charging infrastructures are available, and home charging is always a suitable option for those who have access to it.
Surprisingly, Tesla seems to be more concerned about these middle-market countries as opposed to the larger markets in South America, but that could be by design.
If Tesla were to launch in Brazil initially, it may not be able to handle the uptick in demand, and infrastructure expansion could be more difficult. Brazil may be on its list in the upcoming years, but not as of right now.
News
Tesla expands crucial Supercharging feature for easier access
It is a useful tool, especially during hours of congestion. However, it has not been super effective for those who drive non-Tesla EVs, as other OEMs use UI platforms like Google’s Android Auto or Apple’s iOS.
Tesla has expanded a crucial Supercharging feature that helps owners identify stall availability at nearby locations.
Tesla said on Tuesday night that its “Live Availability” feature, which shows EV owners how many stalls are available at a Supercharger station, to Google Maps, a third-party app:
Live availability of Superchargers now in Google Maps pic.twitter.com/DJvS83wVxm
— Tesla Charging (@TeslaCharging) November 11, 2025
Already offering it in its own vehicles, the Live Availability feature that Teslas have is a helpful feature that helps you choose an appropriate station with plugs that are immediately available.
A number on an icon where the Supercharger is located lets EV drivers know how many stalls are available.
It is a useful tool, especially during hours of congestion. However, it has not been super effective for those who drive non-Tesla EVs, as other OEMs use UI platforms like Google’s Android Auto or Apple’s iOS.
Essentially, when those drivers needed to charge at a Supercharger that enables non-Tesla EVs to plug in, there was a bit more of a gamble. There was no guarantee that a plug would be available, and with no way to see how many are open, it was a risk.
Tesla adding this feature allows people to have a more convenient and easier-to-use experience if they are in a non-Tesla EV. With the already expansive Supercharger Network being available to so many EV owners, there is more congestion than ever.
This new feature makes the entire experience better for all owners, especially as there is more transparency regarding the availability of plugs at Supercharger stalls.
It will be interesting to see if Tesla is able to expand on this new move, as Apple Maps compatibility is an obvious goal of the company’s in the future, we could imagine. In fact, this is one of the first times an Android Auto feature is available to those owners before it became an option for iOS users.
Apple owners tend to get priority with new features within the Tesla App itself.
Elon Musk
Elon Musk’s Boring Co goes extra hard in Nashville with first rock-crushing TBM
The Boring Company’s machine for the project is now in final testing.
The Boring Company is gearing up to tackle one of its toughest projects yet, a new tunnel system beneath Nashville’s notoriously tough limestone terrain. Unlike the soft-soil conditions of Las Vegas and Austin, the Music City Loop will require a “hard-rock” boring machine capable of drilling through dense, erosion-resistant bedrock.
The Boring Company’s machine for the project is now in final testing.
A boring hard-rock tunneling machine
The Boring Company revealed on X that its new hard-rock TBM can generate up to 4 million pounds of grip force and 1.5 million pounds of maximum thrust load. It also features a 15-filter dust removal system designed to keep operations clean and efficient during excavation even in places where hard rock is present.
Previous Boring Co. projects, including its Loop tunnels in Las Vegas, Austin, and Bastrop, were dug primarily through soft soils. Nashville’s geology, however, poses a different challenge. Boring Company CEO and President Steve Davis mentioned this challenge during the project’s announcement in late July.
“It’s a tough place to tunnel, Nashville. If we were optimizing for the easiest places to tunnel, it would not be here. You have extremely hard rock, like way harder than it should be. It’s an engineering problem that’s fairly easy and straightforward to solve,” Davis said.
Nashville’s limestone terrain
Experts have stated that the city’s subsurface conditions make it one of the more complex tunneling environments in the U.S. The Outer Nashville Basin is composed of cherty Mississippian-age limestone, a strong yet soluble rock that can dissolve over time, creating underground voids and caves, as noted in a report from The Tennessean.
Jakob Walter, the founder and principal engineer of Haushepherd, shared his thoughts on these challenges. “Limestone is generally a stable sedimentary bedrock material with strength parameters that are favorable for tunneling. Limestone is however fairly soluble when compared to other rack materials, and can dissolve over long periods of time when exposed to water.
“Unexpected encounters with these features while tunneling can result in significant construction delays and potential instability of the excavation. In urban locations, structures at the ground surface should also be constantly monitored with robotic total stations or similar surveying equipment to identify any early signs of movement or distress,” he said.
Tesla teases new market entrance with confusing and cryptic message
Tesla expands crucial Supercharging feature for easier access
Elon Musk’s Boring Co goes extra hard in Nashville with first rock-crushing TBM
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