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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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Tesla Model Y is still China’s best-selling premium EV through October
The premium-priced SUV outpaced rivals despite a competitive field, while the Model 3 also secured an impressive position.
The Tesla Model Y led China’s top-selling pure electric vehicles in the 200,000–300,000 RMB segment through October 2025, as per Yiche data compiled from China Passenger Car Association (CPCA) figures.
The premium-priced SUV outpaced rivals despite a competitive field, while the Model 3 also secured an impressive position.
The Model Y is still unrivaled
The Model Y’s dominance shines in Yiche’s October report, topping the chart for vehicles priced between 200,000 and 300,000 RMB. With 312,331 units retailed from January through October, the all-electric crossover was China’s best-selling EV in the 200,000–300,000 RMB segment.
The Xiaomi SU7 is a strong challenger at No. 2 with 234,521 units, followed by the Tesla Model 3, which achieved 146,379 retail sales through October. The Model Y’s potentially biggest rival, the Xiaomi YU7, is currently at No. 4 with 80,855 retail units sold.


Efficiency kings
The Model 3 and Model Y recently claimed the top two spots in Autohome’s latest real-world energy-consumption test, outperforming a broad field of Chinese-market EVs under identical 120 km/h cruising conditions with 375 kg payload and fixed 24 °C cabin temperature. The Model 3 achieved 20.8 kWh/100 km while the Model Y recorded 21.8 kWh/100 km, reaffirming Tesla’s efficiency lead.
The results drew immediate attention from Xiaomi CEO Lei Jun, who publicly recognized Tesla’s advantage while pledging continued refinement for his brand’s lineup.
“The Xiaomi SU7’s energy consumption performance is also very good; you can take a closer look. The fact that its test results are weaker than Tesla’s is partly due to objective reasons: the Xiaomi SU7 is a C-segment car, larger and with higher specifications, making it heavier and naturally increasing energy consumption. Of course, we will continue to learn from Tesla and further optimize its energy consumption performance!” Lei Jun wrote in a post on Weibo.
Elon Musk
SpaceX’s Starship program is already bouncing back from Booster 18 fiasco
Just over a week since Booster 18 met its untimely end, SpaceX is now busy stacking Booster 19, and at a very rapid pace, too.
SpaceX is already bouncing back from the fiasco that it experienced during Starship Booster 18’s initial tests earlier this month.
Just over a week since Booster 18 met its untimely end, SpaceX is now busy stacking Booster 19, and at a very rapid pace, too.
Starship V3 Booster 19 is rising
As per Starbase watchers on X, SpaceX rolled out the fourth aft section of Booster 19 to Starbase’s MegaBay this weekend, stacking it to reach 15 rings tall with just a few sections remaining. This marks the fastest booster assembly to date at four sections in five days. This is quite impressive, and it bodes well for SpaceX’s Starship V3 program, which is expected to be a notable step up from the V2 program, which was retired after a flawless Flight 11.
Starship watcher TankWatchers noted the tempo on X, stating, “During the night the A4 section of Booster 19 rolled out to the MegaBay. With 4 sections in just 5 days, this is shaping up to be the fastest booster stack ever.” Fellow Starbase watcher TestFlight echoed the same sentiments. “Booster 19 is now 15 rings tall, with 3 aft sections remaining!” the space enthusiast wrote.
Aggressive targets despite Booster 18 fiasco
SpaceX’s V3 program encountered a speed bump earlier this month when Booster 18, just one day after rolling out into the factory, experienced a major anomaly during gas system pressure testing at SpaceX’s Massey facility in Starbase, Texas. While no propellant was loaded, no engines were installed, and no one was injured in the incident, the unexpected end of Booster 18 sparked speculation that the Starship V3 program could face delays.
Despite the Booster 18 fiasco, however, SpaceX announced that “Starship’s twelfth flight test remains targeted for the first quarter of 2026.” Elon Musk shared a similar timeline on X earlier this year, with the CEO stating that “ V3 is a massive upgrade from the current V2 and should be through production and testing by end of year, with heavy flight activity next year.”
Considering that Booster 19 seems to be moving through its production phases quickly, perhaps SpaceX’s Q1 2026 target for Flight 12 might indeed be more than feasible.
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Elon Musk makes a key Tesla Optimus detail official
“Since we are naming the singular, we will also name the plural, so Optimi it is,” Musk wrote on X.
Tesla CEO Elon Musk just made a key detail about Optimus official. In a post on X, the CEO clarified some key wording about Optimus, which should help the media and the public become more familiar with the humanoid robot.
Elon Musk makes Optimus’ plural term official
Elon Musk posted a number of Optimus-related posts on X this weekend. On Saturday, he stated that Optimus would be the Von Neumann probe, a machine that could eventually be capable of replicating itself. This capability, it seems, would be the key to Tesla achieving Elon Musk’s ambitious Optimus production targets.
Amidst the conversations about Optimus on X, a user of the social media platform asked the CEO what the plural term for the humanoid robot will be. As per Musk, Tesla will be setting the plural term for Optimus since the company also decided on the robot’s singular term. “Since we are naming the singular, we will also name the plural, so Optimi it is,” Musk wrote in his reply on X.
This makes it official. For media outlets such as Teslarati, numerous Optimus bots are now called Optimi. It rolls off the tongue pretty well, too.
Optimi will be a common sight worldwide
While Musk’s comment may seem pretty mundane to some, it is actually very important. Optimus is intended to be Tesla’s highest volume product, with the CEO estimating that the humanoid robot could eventually see annual production rates in the hundreds of millions, perhaps even more. Since Optimi will be a very common sight worldwide, it is good that people can now get used to terms describing the humanoid robot.
During the Tesla 2025 Annual Shareholder Meeting, Musk stated that the humanoid robot will see “the fastest production ramp of any product of any large complex manufactured product ever,” starting with a one-million-Optimi-per-year production line at the Fremont Factory. Giga Texas would get an even bigger Optimus production line, which should be capable of producing tens of millions of Optimi per year.
