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.
SpaceX has disclosed the full financial details of its groundbreaking agreement with Anthropic, confirming that the AI company will pay $1.25 billion per month for dedicated high-performance computing resources.
The revelation came through SpaceX’s latest securities filing in preparation for its initial public offering, shedding light on one of the largest compute deals in the artificial intelligence sector to date. The prospectus was released last night, as SpaceX is heading toward its IPO.
This arrangement underscores the fierce demand for specialized infrastructure as frontier AI models require unprecedented levels of processing power to train and operate effectively. Industry analysts see the disclosure as a significant milestone, highlighting how top AI labs are locking in massive capacity to stay ahead in a rapidly accelerating field.
For SpaceX, it feels like a massive move that pushes its perception as a company from space exploration to artificial intelligence.
SpaceX is following in Tesla’s footsteps in a way nobody expected
The comprehensive deal grants Anthropic exclusive access to SpaceX’s Colossus clusters, encompassing Colossus I and the substantially expanded Colossus II, which together deliver hundreds of megawatts of power along with more than 200,000 NVIDIA GPUs.
Payments extend through May 2029, totaling nearly $45 billion overall; capacity is scheduled to ramp up during May and June 2026 at an initial discounted rate to facilitate seamless integration. Both companies retain the option to terminate the agreement with ninety days’ notice, so there is definitely some flexibility for both.
This pact not only enhances Anthropic’s ability to scale usage limits for Claude users but also injects substantial recurring revenue into SpaceX, bolstering its expansion into advanced data center operations and future orbital computing initiatives.
Observers describe the collaboration between the two companies as strategically advantageous because it gives Anthropic cutting-edge AI development the opportunity to collaborate with SpaceX’s expertise in rapid, large-scale infrastructure deployment.
This disclosure arrives at a pivotal moment when computing resources have become the primary bottleneck for AI progress.
As leading organizations compete to build more powerful systems, securing reliable, high-density facilities has emerged as a key differentiator.
SpaceX’s sites, such as those in Memphis, offer superior power availability and advanced cooling solutions that set them apart from conventional providers. For Anthropic, the added capacity is expected to deliver tangible improvements, including extended context windows, quicker inference times, and innovative features that appeal to both enterprise clients and individual users.
Looking ahead, the partnership paves the way for ambitious joint projects, including potential space-based AI compute platforms designed to overcome terrestrial limitations on energy and thermal management. Such efforts could redefine sustainable computing at massive scales.
Financially, the deal solidifies SpaceX’s diverse revenue profile ahead of its public market debut, extending beyond traditional aerospace activities. The massive check SpaceX will cash each month opens up the idea that additional
While some experts question the sustainability of these enormous expenditures given ongoing efficiency gains in AI architectures, the commitment reflects a strong belief in sustained demand growth.
The agreement also exemplifies productive synergies across sectors, with aerospace engineering insights optimizing AI hardware performance. As global attention on technology concentration increases, arrangements of this nature may help shape equitable access to critical resources.
Elon Musk
SpaceX just filed for the IPO everyone was waiting for
SpaceX filed its public S-1, revealing $18.7 billion in revenue and billions in losses.
SpaceX publicly filed its S-1 registration statement with the Securities and Exchange Commission on May 20, 2026, making its financial details available to the public for the first time ahead of what could be the largest IPO in history.
An S-1 is the formal document a company must submit to the SEC before going public. It includes audited financials, risk factors, business descriptions, and how the company plans to use the money it raises. Companies are required to file one before selling shares to the public, and it must be published at least 15 days before the investor roadshow begins. SpaceX had already submitted a confidential draft to the SEC in April, which allowed regulators to review the filing privately before it went public.
The S-1 reveals that SpaceX generated $18.7 billion in consolidated revenue in 2025, driven largely by its Starlink satellite internet division, which posted $11.4 billion in revenue, growing nearly 50% year over year. Despite that growth, the company lost about $4.9 billion in 2025 and has burned through more than $37 billion since its founding.
SpaceX just forced Verizon, AT&T and T-Mobile to team up for the first time in history
A significant portion of those losses trace back to xAI, Elon Musk’s artificial intelligence company, which was recently merged into SpaceX. SpaceX directed roughly 60% of its capital spending in 2025 to its AI division, totaling around $20 billion, yet that division lost billions and grew revenue by only about 22%.
SpaceX plans to list its Class A common stock on Nasdaq under the ticker SPCX, with Goldman Sachs, Morgan Stanley, and Bank of America leading the offering. The dual-class share structure means going public will not meaningfully reduce Musk’s control, as Class B shares he holds carry 10 votes per share compared to one vote for public Class A shares.
The company is targeting a raise of around $75 billion at a valuation of roughly $1.75 trillion, which would make it the largest IPO ever. The investor roadshow is reportedly planned for June 5.
Tesla has scaled back driver monitoring to be less naggy with the latest version of the Full Self-Driving (Supervised) suite, which is version 14.3.3.
The latest version is already earning praise from owners, who are reporting that the suite is far less invasive when it comes to keeping drivers from taking their eyes off the road. The first to mention it was notable Tesla community member on X known as Zack, or BLKMDL3.
14.3.3 nags less too https://t.co/IuiWzuYO6O
— Elon Musk (@elonmusk) May 18, 2026
Musk confirmed that v14.3.3 was made to nag drivers significantly less, something that Tesla has worked toward in the past and has said with previous versions that it is less likely to push drivers to look ahead, at least after looking away for a few seconds.
This refinement aligns with Tesla’s ongoing push toward unsupervised FSD. The update also brings faster Actual Smart Summon (now up to 8 mph), reliable “Hey Grok” voice commands, richer visualizations, smoother Mad Max acceleration, and an intervention streak counter that rewards consistent use. Reviewers describe the drive as more human-like and confident, with fewer twitches or unnecessary maneuvers.
Musk has repeatedly signaled this direction. In late 2025, he stated that FSD would allow phone use “depending on context of surrounding traffic,” noting safety data would justify relaxing rules so drivers could text in low-risk scenarios like stop-and-go traffic.
We tested this, and even still, the cell phone monitoring really seems to be less active in terms of alerting drivers:
Tesla Full Self-Driving v14.2.1 texting and driving: we tested it
Earlier, ahead of v14, Musk promised the system would “nag the driver much less” once safety metrics improved.
In 2023, he confirmed the steering wheel torque nag would be “gradually reduced, proportionate to improved safety,” shifting reliance to the cabin camera. Subsequent updates like v13.2.9 and v12.4 further loosened monitoring, cracking down on workarounds while easing legitimate distractions.
These steps reflect Tesla’s data-driven approach: FSD’s safety record—reportedly averaging millions of miles per crash—now outpaces human drivers in many scenarios, giving the company confidence to dial back interventions. Reduced nags improve usability and trust, encouraging more drivers to rely on the system rather than disengaging out of frustration.
However, there are certainly still some concerns. In many states, it is illegal to handle a cell phone in any way, requiring the use of hands-free devices. In Pennsylvania, it is illegal to use your cell phone at stop lights, which is definitely a step further than using it while the car is actively in motion.
v14.3.3 represents tangible progress. Making FSD less adversarial and more seamless is definitely a step forward, but drivers need to be aware of the dangers of distracted driving. FSD is extremely capable, but it is in no way fully autonomous, nor does its performance warrant owners to take their attention off the road.
SpaceX reveals what Anthropic will pay for massive compute deal
SpaceX just filed for the IPO everyone was waiting for
