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Tesla MIT study concludes that drivers maintain vigilance when using Autopilot
Tesla owners using Autopilot are highly engaged when driving with the feature despite fears to the contrary, according to a study recently published by scientists at MIT titled Human Side of Tesla Autopilot: Exploration of Functional Vigilance in Real-World Human-Machine Collaboration.
The data used in the study was generated from the over 1 billion miles driven by Tesla owners since its activation in 2015, about 35% of which were determined to be assisted by Autopilot. Of these, 18,928 disengagements of Autopilot were annotated, which indicated instances when drivers took over during challenging driving situations. Overall, the numbers demonstrate a high rate of driver vigilance.
Tesla has provided a unique opportunity to form a baseline for objective, representative analysis of real-world use of Autopilot, as stated in the study:
“Due to its scale of deployment and individual utilization, [Tesla’s] Autopilot serves as perhaps the currently best available opportunity to study and understand human interaction with AI assisted vehicles ‘in the wild’…naturalistic driving research can now begin investigating and identify both promising and concerning trends in drivers’ behavioral patterns in the context of Autopilot.”
As automation has expanded over the last several decades, a pattern of overtrust in reliable automated systems has been shown by human behavior research studies. In the context of driving scenarios where property damage, injury, or death are possible consequences, the concern with the transition to semi-autonomous systems relying on driver input to function safely is obviously significant. The results of the MIT study are therefore promising, initially showing an approach to automation in driving systems that’s more careful than other areas.
“The two main results of this work are that (1) drivers elect to use Autopilot for a significant percent of their driven miles and (2) drivers do not appear to over-trust the system to a degree that results in significant functional vigilance degradation in their supervisory role of system operation,” the MIT scientists concluded.
The study further notes that more research will be needed as more data becomes available and more familiarity grows with Autopilot’s features.
Tesla has received a fair amount of criticism and attention whenever an accident involves one of its cars, especially if Autopilot was engaged around the time of the event. However, Tesla consistently maintains its position that the feature is not yet fully autonomous and requires drivers to both pay attention and intervene when necessary while Autopilot is in operation. The program is additionally equipped with several alerts which give drivers audio and visual warnings if hands are not detected on the steering wheel, something found to have been ignored in some prior crash events, playing into concerns the MIT study sought to address.
Beginning in Q3 2018, Tesla has been releasing quarterly Vehicle Safety Reports providing updated numbers for vehicle incidents occurring both when Autopilot was engaged and when the driver-assist feature was deactivated. For Q3, the company reported one accident or crash-like event for every 3.34 million miles driven with Autopilot active and one event for every 1.92 million miles driven with Autopilot disengaged. In Q4 2018, those numbers dropped slightly, possibly due to winter conditions, to one accident for every 2.91 million miles driven with Autopilot engaged and one accident for every 1.58 million miles driven without.
By comparison, the National Highway Traffic Safety Administration’s (NHTSA) most recent data at the time showed a crash event every 436,000 miles, a figure which includes all vehicles in the US whether or not the cars are equipped with driving enhancement software. Tesla’s numbers further include both accidents that have occurred and “near-misses”, and the NHTSA’s figures only include accidents that actually transpired.
Along with touting a correlation between lower accident rates and Autopilot being engaged, Tesla also maintains its title of producing the safest cars in the world based on NHTSA test results.
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.
Elon Musk’s xAI brings 1GW Colossus 2 AI training cluster online
Tesla AI5 chip nears completion, Elon Musk teases 9-month development cadence
