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Tesla’s Neural Network adaptability to hardware highlighted in new patent application

(Credit: Tesla Driver/YouTube)

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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.

Credit: Tesla/USPTO

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.

Credit: Tesla/USPTO

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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Accidental computer geek, fascinated by most history and the multiplanetary future on its way. Quite keen on the democratization of space. | It's pronounced day-sha, but I answer to almost any variation thereof.

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Tesla Model Y and Model 3 named safest vehicles tested by ANCAP in 2025

According to ANCAP in a press release, the Tesla Model Y achieved the highest overall weighted score of any vehicle assessed in 2025.

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Credit: ANCAP

The Tesla Model Y recorded the highest overall safety score of any vehicle tested by ANCAP in 2025. The Tesla Model 3 also delivered strong results, reinforcing the automaker’s safety leadership in Australia and New Zealand.

According to ANCAP in a press release, the Tesla Model Y achieved the highest overall weighted score of any vehicle assessed in 2025. ANCAP’s 2025 tests evaluated vehicles across four key pillars: Adult Occupant Protection, Child Occupant Protection, Vulnerable Road User Protection, and Safety Assist technologies.

The Model Y posted consistently strong results in all four categories, distinguishing itself through a system-based safety approach that combines structural crash protection with advanced driver-assistance features such as autonomous emergency braking, lane support, and driver monitoring. 

This marked the second time the Model Y has topped ANCAP’s annual safety rankings. The Model Y’s previous version was also ANCAP’s top performer in 2022.

The Tesla Model 3 also delivered a strong performance in ANCAP’s 2025 tests, contributing to Tesla’s broader safety presence across segments. Similar to the Model Y, the Model 3 also earned impressive scores across the ANCAP’s four pillars. This made the vehicle the top performer in the Medium Car category.  

ANCAP Chief Executive Officer Carla Hoorweg stated that the results highlight a growing industry shift toward integrated safety design, with improvements in technologies such as autonomous emergency braking and lane support translating into meaningful real-world protection.

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“ANCAP’s testing continues to reinforce a clear message: the safest vehicles are those designed with safety as a system, not a checklist. The top performers this year delivered consistent results across physical crash protection, crash avoidance and vulnerable road user safety, rather than relying on strength in a single area.

“We are also seeing increasing alignment between ANCAP’s test requirements and the safety technologies that genuinely matter on Australian and New Zealand roads. Improvements in autonomous emergency braking, lane support, and driver monitoring systems are translating into more robust protection,” Hoorweg said.

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Tesla Sweden uses Megapack battery to bypass unions’ Supercharger blockade

Just before Christmas, Tesla went live with a new charging station in Arlandastad, outside Stockholm, by powering it with a Tesla Megapack battery.

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Credit: Tesla Charging/X

Tesla Sweden has successfully launched a new Supercharger station despite an ongoing blockade by Swedish unions, using on-site Megapack batteries instead of traditional grid connections. The workaround has allowed the Supercharger to operate without direct access to Sweden’s electricity network, which has been effectively frozen by labor action.

Tesla has experienced notable challenges connecting its new charging stations to Sweden’s power grid due to industrial action led by Seko, a major Swedish trade union, which has blocked all new electrical connections for new Superchargers. On paper, this made the opening of new Supercharger sites almost impossible.

Despite the blockade, Tesla has continued to bring stations online. In Malmö and Södertälje, new Supercharger locations opened after grid operators E.ON and Telge Nät activated the sites. The operators later stated that the connections had been made in error. 

More recently, however, Tesla adopted a different strategy altogether. Just before Christmas, Tesla went live with a new charging station in Arlandastad, outside Stockholm, by powering it with a Tesla Megapack battery, as noted in a Dagens Arbete (DA) report. 

Because the Supercharger station does not rely on a permanent grid connection, Tesla was able to bypass the blocked application process, as noted by Swedish car journalist and YouTuber Peter Esse. He noted that the Arlandastad Supercharger is likely dependent on nearby companies to recharge the batteries, likely through private arrangements.

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Eight new charging stalls have been launched in the Arlandastad site so far, which is a fraction of the originally planned 40 chargers for the location. Still, the fact that Tesla Sweden was able to work around the unions’ efforts once more is impressive, especially since Superchargers are used even by non-Tesla EVs.

Esse noted that Tesla’s Megapack workaround is not as easily replicated in other locations. Arlandastad is unique because neighboring operators already have access to grid power, making it possible for Tesla to source electricity indirectly. Still, Esse noted that the unions’ blockades have not affected sales as much.

“Many want Tesla to lose sales due to the union blockades. But you have to remember that sales are falling from 2024, when Tesla sold a record number of cars in Sweden. That year, the unions also had blockades against Tesla. So for Tesla as a charging operator, it is devastating. But for Tesla as a car company, it does not matter in terms of sales volumes. People charge their cars where there is an opportunity, usually at home,” Esse noted. 

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Elon Musk’s X goes down as users report major outage Friday morning

Error messages and stalled loading screens quickly spread across the service, while outage trackers recorded a sharp spike in user reports.

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Credit: Linda Yaccarino/X

Elon Musk’s X experienced an outage Friday morning, leaving large numbers of users unable to access the social media platform.

Error messages and stalled loading screens quickly spread across the service, while outage trackers recorded a sharp spike in user reports.

Downdetector reports

Users attempting to open X were met with messages such as “Something went wrong. Try reloading,” often followed by an endless spinning icon that prevented access, according to a report from Variety. Downdetector data showed that reports of problems surged rapidly throughout the morning.

As of 10:52 a.m. ET, more than 100,000 users had reported issues with X. The data indicated that 56% of complaints were tied to the mobile app, while 33% were related to the website and roughly 10% cited server connection problems. The disruption appeared to begin around 10:10 a.m. ET, briefly eased around 10:35 a.m., and then returned minutes later.

Credit: Downdetector

Previous disruptions

Friday’s outage was not an isolated incident. X has experienced multiple high-profile service interruptions over the past two years. In November, tens of thousands of users reported widespread errors, including “Internal server error / Error code 500” messages. Cloudflare-related error messages were also reported.

In March 2025, the platform endured several brief outages spanning roughly 45 minutes, with more than 21,000 reports in the U.S. and 10,800 in the U.K., according to Downdetector. Earlier disruptions included an outage in August 2024 and impairments to key platform features in July 2023.

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