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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.
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Man credits Grok AI with saving his life after ER missed near-ruptured appendix
The AI flagged some of the man’s symptoms and urged him to return to the ER immediately and demand a CT scan.
A 49-year-old man has stated that xAI’s Grok ended up saving his life when the large language model identified a near-ruptured appendix that his first ER visit dismissed as acid reflux.
After being sent home from the ER, the man asked Grok to analyze his symptoms. The AI flagged some of the man’s symptoms and urged him to return immediately and demand a CT scan. The scan confirmed that something far worse than acid reflux was indeed going on.
Grok spotted what a doctor missed
In a post on Reddit, u/Tykjen noted that for 24 hours straight, he had a constant “razor-blade-level” abdominal pain that forced him into a fetal position. He had no fever or visible signs. He went to the ER, where a doctor pressed his soft belly, prescribed acid blockers, and sent him home.
The acid blockers didn’t work, and the man’s pain remained intense. He then decided to open a year-long chat he had with Grok and listed every detail that he was experiencing. The AI responded quickly. “Grok immediately flagged perforated ulcer or atypical appendicitis, told me the exact red-flag pattern I was describing, and basically said “go back right now and ask for a CT,” the man wrote in his post.
He copied Grok’s reasoning, returned to the ER, and insisted on the scan. The CT scan ultimately showed an inflamed appendix on the verge of rupture. Six hours later, the appendix was out. The man said the pain has completely vanished, and he woke up laughing under anesthesia. He was discharged the next day.
How a late-night conversation with Grok got me to demand the CT scan that saved my life from a ruptured appendix (December 2025)
byu/Tykjen ingrok
AI doctors could very well be welcomed
In the replies to his Reddit post, u/Tykjen further explained that he specifically avoided telling doctors that Grok, an AI, suggested he get a CT scan. “I did not tell them on the second visit that Grok recommended the CT scan. I had to lie. I told them my sister who’s a nurse told me to ask for the scan,” the man wrote.
One commenter noted that the use of AI in medicine will likely be welcomed, stating that “If AI could take doctors’ jobs one day, I will be happy. Doctors just don’t care anymore. It’s all a paycheck.” The Redditor replied with, “Sadly yes. That is what it felt like after the first visit. And the following night could have been my last.”
Elon Musk has been very optimistic about the potential of robots like Tesla Optimus in the medical field. Provided that they are able to achieve human-level articulation in their hands, and Tesla is able to bring down their cost through mass manufacturing, the era of AI-powered medical care could very well be closer than expected.
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Tesla expands Model 3 lineup in Europe with most affordable variant yet
The Model 3 Standard still delivers more than 300 miles of range, potentially making it an attractive option for budget-conscious buyers.
Tesla has introduced a lower-priced Model 3 variant in Europe, expanding the lineup just two months after the vehicle’s U.S. debut. The Model 3 Standard still delivers more than 300 miles (480 km) of range, potentially making it an attractive option for budget-conscious buyers.
Tesla’s pricing strategy
The Model 3 Standard arrives as Tesla contends with declining registrations in several countries across Europe, where sales have not fully offset shifting consumer preferences. Many buyers have turned to options such as Volkswagen’s ID.3 and BYD’s Atto 3, both of which have benefited from aggressive pricing.
By removing select premium finishes and features, Tesla positioned the new Model 3 Standard as an “ultra-low cost of ownership” option of its all-electric sedan. Pricing comes in at €37,970 in Germany, NOK 330,056 in Norway, and SEK 449,990 in Sweden, depending on market. This places the Model 3 Standard well below the “premium” Model 3 trim, which starts at €45,970 in Germany.
Deliveries for the Standard model are expected to begin in the first quarter of 2026, giving Tesla an entry-level foothold in a segment that’s increasingly defined by sub-€40,000 offerings.
Tesla’s affordable vehicle push
The low-cost Model 3 follows October’s launch of a similarly positioned Model Y variant, signaling a broader shift in Tesla’s product strategy. While CEO Elon Musk has moved the company toward AI-driven initiatives such as robotaxis and humanoid robots, lower-priced vehicles remain necessary to support the company’s revenue in the near term.
Reports have indicated that Tesla previously abandoned plans for an all-new $25,000 EV, with the company opting to create cheaper versions of existing platforms instead. Analysts have flagged possible cannibalization of higher-margin models, but the move aims to counter an influx of aggressively priced entrants from China and Europe, many of which sell below $30,000. With the new Model 3 Standard, Tesla is reinforcing its volume strategy in Europe’s increasingly competitive EV landscape.
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Tesla FSD (Supervised) stuns Germany’s biggest car magazine
FSD Supervised recognized construction zones, braked early for pedestrians, and yielded politely on narrow streets.
Tesla’s upcoming FSD Supervised system, set for a European debut pending regulatory approval, is showing notably refined behavior in real-world testing, including construction zones, pedestrian detection, and lane changes, as per a recent demonstration ride in Berlin.
While the system still required driver oversight, its smooth braking, steering, and decision-making illustrated how far Tesla’s driver-assistance technology has advanced ahead of a potential 2026 rollout.
FSD’s maturity in dense city driving
During the Berlin test ride with Auto Bild, Germany’s largest automotive publication, a Tesla Model 3 running FSD handled complex traffic with minimal intervention, autonomously managing braking, acceleration, steering, and overtaking up to 140 km/h. It recognized construction zones, braked early for pedestrians, and yielded politely on narrow streets.
Only one manual override was required when the system misread a converted one-way route, an example, Tesla stated, of the continuous learning baked into its vision-based architecture.
Robin Hornig of Auto Bild summed up his experience with FSD Supervised with a glowing review of the system. As per the reporter, FSD Supervised already exceeds humans with its all-around vision. “Tesla FSD Supervised sees more than I do. It doesn’t get distracted and never gets tired. I like to think I’m a good driver, but I can’t match this system’s all-around vision. It’s at its best when both work together: my experience and the Tesla’s constant attention,” the journalist wrote.
Tesla FSD in Europe
FSD Supervised is still a driver-assistance system rather than autonomous driving. Still, Auto Bild noted that Tesla’s 360-degree camera suite, constant monitoring, and high computing power mark a sizable leap from earlier iterations. Already active in the U.S., China, and several other regions, the system is currently navigating Europe’s approval pipeline. Tesla has applied for an exemption in the Netherlands, aiming to launch the feature through a free software update as early as February 2026.
What Tesla demonstrated in Berlin mirrors capabilities already common in China and the U.S., where rival automakers have rolled out hands-free or city-navigation systems. Europe, however, remains behind due to a stricter certification environment, though Tesla is currently hard at work pushing for FSD Supervised’s approval in several countries in the region.
Man credits Grok AI with saving his life after ER missed near-ruptured appendix
Tesla expands Model 3 lineup in Europe with most affordable variant yet
