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Tesla’s damage monitoring patent hints at cars driving to repair centers autonomously
Despite being cutting-edge machines that could be described as “the most fun thing” that anyone can possibly buy, Tesla’s electric cars are still subjected to a great deal of stress during operation. Electric cars have fewer moving parts than their fossil fuel-powered counterparts, but nevertheless, the components that move, such as their electric motors and suspension, are still subject to different types of stress.
One of Tesla’s recently published patent applications, titled “System and Method for Monitoring Stress Cycles,” discusses this particular issue. As noted by the electric car maker, machines may heat up or cool down, or speed up and slow down at different times during operation, resulting in thermal and mechanical stress. Over time, such stress could result in decreased performance, which is referred to as damage.
Damages are costly and hazardous. Stress-related damage results in equipment downtime, performance degradation, safety hazards, and maintenance expenses, to name a few. In the case of Tesla’s electric cars, these damages can cause breakdowns, or worse, accidents. To prevent this, strategies are usually employed to detect and address stress-related damage, such as repairing damaged parts or replacing components at set intervals. Tesla notes in its patent application that both practices are time-consuming and costly.
“Even regular inspections may not provide adequate protection against stress-related damage. For example, the inspections may not provide sufficient insight into the characteristics of the stresses imposed on a given component to accurately assess its condition. Moreover, the inspections themselves may be burdensome and costly,” the company wrote.
With this in mind, there is a need for a system that can detect and address stress-related damage in a more efficient and cost-effective manner.
Tesla’s recently published patent application outlines a system involving a processor configured to monitor stress imposed on subsystems while determining the cumulative damage to a vehicle’s systems. Tesla notes that a stress monitoring system would work optimally if the processor is configured to monitor stress cycles in real-time, allowing the system to avoid using too much memory in the process. Tesla describes the concept in the following discussion.
“To address these challenges, processor 140 may be configured to monitor stress cycles in real-time. For example, processor 140 may identify and record stress cycles concurrently while receiving the series of stress values from stress sensors 131-139. In some embodiments, for each received stress value in the series of stress values, processor 140 may perform one or more operations to determine whether a stress cycle has been completed. When processor 140 detects the end of a stress cycle, processor 140 may record the stress cycle immediately, such that the cumulative damage model can be continuously updated to reflect the latest recorded stress cycle.
“In some examples, real-time monitoring of stress cycles may be performed without storing the series of stress values in memory 150. For example, rather than storing a complete series of stress values for later data processing, a comparatively small number of stress values may be stored temporarily to track in-progress stress cycles, but other stress values may be discarded as soon as they are received. Accordingly, the amount of memory used during real-time monitoring of stress cycles may be reduced in comparison to alternative approaches.”
Adopting such a system gives notable benefits to electric car owners. By using a real-time monitoring model, for one, drivers would be notified by their vehicles once a component needs maintenance. In some instances, the car could immediately send stress and damage data to the company. Taking the concept even further, Tesla notes that a vehicle equipped with autonomous driving features would be able to drive itself to a service center when it needs repairs.
“In some embodiments, an operator of vehicle 110 may be notified when damage to subsystems 121-129 is detected. For example, the operator may be alerted when the level of damage reaches a predetermined threshold, such that the operator may take an appropriate remedial action (e.g., bringing vehicle 110 in for maintenance). In one illustrative example, when the level of damage is represented as a damage fraction, the operator may be alerted when the fractional damage to a given subsystem reaches 70%. In some examples, the alert may be communicated to the operator via a dashboard 160 (and/or another suitable control/monitoring interface) of vehicle 110.
“In some examples, processor 140 may be coupled to one or more external entities over a network 170. Accordingly, processor 140 may be configured to send stress cycle and/or damage data over network 170 to various recipients. For example, processor 140 may send stress cycle and/or damage data to a service center, such that service center may contact the operator to schedule a maintenance appointment when a damaged subsystem is identified. Additionally or alternately, when vehicle 1 10 is an autonomous vehicle, vehicle 110 may be instructed to drive autonomously to service center for repairs.”
Tesla is arguably one of the most proactive companies in the auto industry. For example, automotive teardown expert Sandy Munro has already dubbed the company’s batteries as the best in the market today, but Tesla’s Automotive President Jerome Guillen has stated that the company is still constantly making its batteries even better. In an interview with CNBC, Guillen pointed out that the design of Tesla’s battery cells is “not frozen.” With this in mind, it is not very surprising to see Tesla exploring proactive new ways to figure out more effective ways to monitor damages on its electric vehicles.
Tesla’s constant initiative to improve is teased somewhat in the patent applications from the company that has been published over the past few months. Among these include an automatic tire inflation system that teases off-road capabilities for the company’s vehicles, a system that addresses panel gaps during vehicle assembly, a way to create colored solar roof tiles, and even a system that uses electric cars as a way to improve vehicle positioning.
The full text of Tesla’s recently published patent application could be accessed here.
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
