Much excitement surrounding Tesla’s Dojo supercomputing cluster has been swirling in recent months since the system went online, and the automaker already expects it to be one of the world’s most powerful supercomputers by early next year. But one reporter recently noted that Dojo could someday have additional uses beyond processing vast amounts of data for Tesla’s Full Self-Driving (FSD) system and humanoid robot.
Dojo can process millions of terabytes of video data per second from the company’s vehicles, training its neural network at an incredible rate. The company has said that the video foundation models input to Dojo would effectively serve as the brain of its vehicles and its Optimus robot.
In a recent video segment about how Dojo is expected to revolutionize self-driving, however, Yahoo Finance reporter Pras Subramanian also talked about the supercomputing cluster’s potential applications beyond FSD and Optimus.
The short discussion, hosted by Seana Smith, details how the Dojo system will use Tesla’s AI model to train FSD. However, Subramanian also says the supercomputer could someday be used for vessels other than cars, including motorcycles, bicycles and boats. The conversation also touched on how Dojo works, the complexity of training AI to handle roads and Ford and Volkswagen’s decision to end Argo AI operations, among other topics.
You can watch a short clip from the video segment below or see the full conversation here.
As for cars, Musk has previously talked about the potential of using Dojo to perform traffic control simply with the system’s inputs for things like accidents, potholes, road closures or other data that would be useful for a Tesla to access in real-time. Musk said in June that Dojo had been “online and running useful tasks for a few months,” helping out with production workloads and spurring on the current round of excitement surrounding the computing cluster.
In June, Tesla posted about Dojo on X, detailing how its neural networks were already being accessed in its cars and adding that the company is “building the foundation models for autonomous robots.” Below is an excerpt from the thread:
“Our multi-modal neural networks are already in customer vehicles—these networks take in arbitrary modalities such as camera videos, maps, navigation, IMU (Inertial Measurement Unit), GPS etc.
Tasks such as Occupancy prediction are already quite general in what they represent—in some ways, they are ontology-free & simply predict the probability that some 3D position is occupied.
Such occupancy can be used for collision avoidance by any robot.
All of this is enabled by fleet scale auto-labelling. By using video data from multiple trips in the same location, we can reconstruct the entire scene
In addition, we’re building off state-of-the-art generative modeling techniques—enabling us to predict possible outcomes given past observations, in a jointly consistent manner across multiple camera views”
These imagined futures can be action-conditioned to produce different outcomes.
For example, the videos below are generated entirely by the neural network by simply using different prompts pic.twitter.com/ZuJEYcLuZK
— Tesla AI (@Tesla_AI) June 21, 2023
In 2021, Musk said that Dojo could likely someday reduce traffic fatalities by 90 percent and eventually it may be able to reduce them by more than 99 percent.
Last month, a report showed that Tesla had doubled its order of D1 Dojo chips for next year from Taiwan Semiconductor Manufacturing Company (TSMC), now totaling 10,000 units. According to the report, the company also plans to increase its order in 2025. Morgan Stanley also said last month that Dojo could add $500 billion to Tesla’s enterprise value.
Tesla Dojo trade secrets lawsuit officially settles out of court
What are your thoughts? Let me know at zach@teslarati.com, find me on X at @zacharyvisconti, or send your tips to us at tips@teslarati.com.
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.
News
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
