A recently published Tesla patent application titled “Autonomous Driving System Emergency Signaling” describes a method of quickly communicating emergency information from vehicle sensors feeding into autonomous driving software. The new communication method will improve Autopilot’s response in emergency situations, thereby reducing the probability of accidents.
Tesla’s invention takes latency in data transmission into account as an area of improvement. In general, critical information can get stuck waiting to be processed by a computer after non-critical information that’s ahead of it. Under Tesla’s US Patent Application No. 2019/0138018, critical emergency situations detected by sensors are moved to the front of the line for priority processing and response. Tesla’s invention achieves this using two main approaches.
- Tesla’s self-driving patent hints at faster collision response times. | Image: Tesla/USPTO
- Tesla’s self-driving patent hints at faster collision response times. | Image: Tesla/USPTO
- Tesla’s self-driving patent hints at faster collision response times. | Image: Tesla/USPTO
First, the transmission from sensors that detect an emergency sends their findings to the main computer at a higher transmit power than other messages. Other signals at lower power transmissions are then interpreted as ‘background noise’ compared to the emergency signal. This process is described in the patent application as follows:
“When an autonomous driving emergency event is detected by an autonomous driving sensor…the [sensor] transmits the autonomous driving emergency message in a non-assigned time slot at a higher transmit power level than a transmit power level of an autonomous driving sensor…Because the autonomous driving emergency message is transmitted at a higher power level than the transmission from the autonomous driving sensor, the transmission from the autonomous driving sensor may be treated as background noise by the autonomous driving controller to thereby receive and decode of the autonomous driving emergency message.”
- Tesla’s self-driving patent hints at faster collision response times. | Image: Tesla/USPTO
- Tesla’s self-driving patent hints at faster collision response times. | Image: Tesla/USPTO
- Tesla’s self-driving patent hints at faster collision response times. | Image: Tesla/USPTO
In a second approach, the autonomous driving sensors that encounter an emergency message are programmed to stop sending signals, and the vehicle’s main computer will direct them to resume communications after receiving the emergency message. This process is described in the patent as follows:
“…if an emergency transmission is detected…the autonomous driving sensor ceases transmitting autonomous driving data. Such cessation may continue for one assigned time slot, for more than one assigned slots, and/or until the autonomous driving sensor receives direction from the autonomous driving controller to continue transmitting autonomous driving data or receives a new…bus time slot assignment from the autonomous driving controller. During this time period…the autonomous driving sensor continues to collect and buffer autonomous driving data.”
Several variations of achieving these two main concepts are also described in the application and invention claims, including managing the specifics of the transmit power level differences and reassigning time slots for sensors to communicate on the data bus. Overall, this recent patent application is yet another indicator of Tesla’s continued improvement of its autonomous driving capabilities.
Tesla’s advances in the autonomous driving arena have been touted by CEO Elon Musk and industry experts alike. ARK Invest analyst James Wang recently estimated that the all-electric car maker’s decision to develop its Full Self-Driving computer chip in-house put the company four years ahead of the competition. Musk, for his part, declared the chip the best in the world at Tesla’s Investor Autonomy Day. “It seems improbable. How could it be that Tesla, who has never designed a chip before, would design the best chip in the world? But that is objectively what has occurred,” Elon touted.
While Tesla has yet to roll out the total capabilities of its Full Self-Driving suite, Musk has said on several occasions that the software will be “feature complete” by the end of 2019 with only regulatory hurdles left for full release.
Elon Musk
Elon Musk’s xAI brings 1GW Colossus 2 AI training cluster online
Elon Musk shared his update in a recent post on social media platform X.
xAI has brought its Colossus 2 supercomputer online, making it the first gigawatt-scale AI training cluster in the world, and it’s about to get even bigger in a few months.
Elon Musk shared his update in a recent post on social media platform X.
Colossus 2 goes live
The Colossus 2 supercomputer, together with its predecessor, Colossus 1, are used by xAI to primarily train and refine the company’s Grok large language model. In a post on X, Musk stated that Colossus 2 is already operational, making it the first gigawatt training cluster in the world.
But what’s even more remarkable is that it would be upgraded to 1.5 GW of power in April. Even in its current iteration, however, the Colossus 2 supercomputer already exceeds the peak demand of San Francisco.
Commentary from users of the social media platform highlighted the speed of execution behind the project. Colossus 1 went from site preparation to full operation in 122 days, while Colossus 2 went live by crossing the 1-GW barrier and is targeting a total capacity of roughly 2 GW. This far exceeds the speed of xAI’s primary rivals.
Funding fuels rapid expansion
xAI’s Colossus 2 launch follows xAI’s recently closed, upsized $20 billion Series E funding round, which exceeded its initial $15 billion target. The company said the capital will be used to accelerate infrastructure scaling and AI product development.
The round attracted a broad group of investors, including Valor Equity Partners, Stepstone Group, Fidelity Management & Research Company, Qatar Investment Authority, MGX, and Baron Capital Group. Strategic partners NVIDIA and Cisco also continued their support, helping xAI build what it describes as the world’s largest GPU clusters.
xAI said the funding will accelerate its infrastructure buildout, enable rapid deployment of AI products to billions of users, and support research tied to its mission of understanding the universe. The company noted that its Colossus 1 and 2 systems now represent more than one million H100 GPU equivalents, alongside recent releases including the Grok 4 series, Grok Voice, and Grok Imagine. Training is also already underway for its next flagship model, Grok 5.
Elon Musk
Tesla AI5 chip nears completion, Elon Musk teases 9-month development cadence
The Tesla CEO shared his recent insights in a post on social media platform X.
Tesla’s next-generation AI5 chip is nearly complete, and work on its successor is already underway, as per a recent update from Elon Musk.
The Tesla CEO shared his recent insights in a post on social media platform X.
Musk details AI chip roadmap
In his post, Elon Musk stated that Tesla’s AI5 chip design is “almost done,” while AI6 has already entered early development. Musk added that Tesla plans to continue iterating rapidly, with AI7, AI8, AI9, and future generations targeting a nine-month design cycle.
He also noted that Tesla’s in-house chips could become the highest-volume AI processors in the world. Musk framed his update as a recruiting message, encouraging engineers to join Tesla’s AI and chip development teams.
Tesla community member Herbert Ong highlighted the strategic importance of the timeline, noting that faster chip cycles enable quicker learning, faster iteration, and a compounding advantage in AI and autonomy that becomes increasingly difficult for competitors to close.
AI5 manufacturing takes shape
Musk’s comments align with earlier reporting on AI5’s production plans. In December, it was reported that Samsung is preparing to manufacture Tesla’s AI5 chip, accelerating hiring for experienced engineers to support U.S. production and address complex foundry challenges.
Samsung is one of two suppliers selected for AI5, alongside TSMC. The companies are expected to produce different versions of the AI5 chip, with TSMC reportedly using a 3nm process and Samsung using a 2nm process.
Musk has previously stated that while different foundries translate chip designs into physical silicon in different ways, the goal is for both versions of the Tesla AI5 chip to operate identically. AI5 will succeed Tesla’s current AI4 hardware, formerly known as Hardware 4, and is expected to support the company’s Full Self-Driving system as well as other AI-driven efforts, including Optimus.
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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.
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.
“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.





