You'd have to be pretty brave to bet against the idea that applying more computing power and data to machine learning--a recipe that birthed ChatGPT--won't lead to further advances of some kind in artificial intelligence. Even so, you'd be braver still to bet that combo will produce specific advances or breakthroughs on a specific timeline, no matter how desirable. A report issued last weekend by the investment bank Morgan Stanley predicts that a supercomputer called Dojo, which Tesla is building to boost its work on autonomous driving, could add $500 billion to the company's value by providing a huge advantage in carmaking, robotaxis, and selling software to other businesses. The report juiced Tesla's stock price, adding more than 6 percent, or $70 billion--roughly the value of BMW and much less than Elon Musk paid for Twitter--to the EV-maker's market cap as of September 13. The 66-page Morgan Stanley report is an interesting read.

Tesla has unveiled its latest version of its Dojo supercomputer and it's apparently so powerful that it tripped the power grid in Palo Alto. Dojo is Tesla's own custom supercomputer platform built from the ground up for AI machine learning and more specifically for video training using the video data coming from its fleet of vehicles. The automaker already has a large NVIDIA GPU-based supercomputer that is one of the most powerful in the world, but the new Dojo custom-built computer is using chips and an entire infrastructure designed by Tesla. The custom-built supercomputer is expected to elevate Tesla's capacity to train neural nets using video data, which is critical to its computer vision technology powering its self-driving effort. Last year, at Tesla's AI Day, the company unveiled its Dojo supercomputer, but the company was still ramping up its effort at the time.

Last year during Tesla's AI Day, the automaker unveiled its Dojo supercomputer. At the time, Tesla claimed the supercomputer was the world's most powerful training machine and would help the automaker teach its vehicles how to drive without any inputs from a human driver. While Tesla officially announced the system last year, the automaker provided more information on its Dojo supercomputer this year at the Hot Chips conference. Dojo's job is to take all of the video Tesla gathers from its fleet of Tesla cars on the road today and process it to learn how cars drive in the real world. The training process is what represents the base for Tesla's Full Self Driving System.

Elon Musk's vision is to change Tesla from an electric car company to a robotics company and the Tesla AI Day shows his commitment towards his vision. Tesla is one of the biggest automobile company and due to their research and implementation of AI in their cars (Self Driving System) they are as much a software company as an automobile company. Tesla as a company is deeply involved with AI in hardware that is used beyond the self-driving systems. Elon Musk wants Tesla to be seen as "much more than an electric car company." On Thursday's Tesla AI Day, the CEO described Tesla as a company with "deep AI activity in hardware on the inference level and on the training level" that can be used down the line for applications beyond self-driving cars, including a humanoid robot that Tesla is apparently building.

At its AI Day, Tesla unveiled its Dojo supercomputer technology while flexing its growing in-house chip design talent. The automaker claims to have developed the fastest AI training machine in the world. For years now, Tesla has been teasing the development of a new supercomputer in-house optimized for neural net video training. Tesla is handling an insane amount of video data from its fleet of over 1 million vehicles, which it uses to train its neural nets. The automaker found itself unsatisfied with current hardware options to train its computer vision neural nets and believed it could do better internally. Over the last two years, CEO Elon Musk has been teasing the development of Tesla's own supercomputer called "Dojo."

Tesla plans to offer machine-learning training as a web service with its new'Dojo' supercomputer, according to new comments from CEO Elon Musk. Project "Dojo" was first announced by Musk at Tesla's Autonomy Day last year: We do have a major program at Tesla which we don't have enough time to talk about today called "Dojo." The goal of Dojo will be to be able to take in vast amounts of data and train at a video level and do unsupervised massive training of vast amounts of video with the Dojo program -- or Dojo computer. Dojo means "place of the Way" in Japanese and the term is often used for a place to practice meditation or martial arts. In this case, the Dojo supercomputer will be a place for Tesla to train its Full Self-Driving AI. Last month, Musk revealed that Tesla's Dojo supercomputer will be capable of an exaFLOP, one quintillion (1018) floating-point operations per second, or 1,000 petaFLOPS.

Tesla may be introducing machine-learning training as a web service with its upcoming'Dojo' supercomputer, CEO Elon Musk said on Twitter. Project Dojo was initially revealed by Musk last year and is a supercomputer which Tesla has been working on. The supercomputer has been designed to ingest massive amounts of video data and perform massive levels of unsupervised training on the visual data. The goal of Dojo will be to be able to take in vast amounts of data and train at a video level and do massive unsupervised training of vast amounts of video data. Dojo uses our own chips & a computer architecture optimized for neural net training, not a GPU cluster. Could be wrong, but I think it will be best in world.

Tesla may be introducing machine-learning training as a web service with its upcoming'Dojo' supercomputer, CEO Elon Musk said on Twitter. Project Dojo was initially revealed by Musk last year and is a supercomputer which Tesla has been working on. The supercomputer has been designed to ingest massive amounts of video data and perform massive levels of unsupervised training on the visual data. The goal of Dojo will be to be able to take in vast amounts of data and train at a video level and do massive unsupervised training of vast amounts of video data. Dojo uses our own chips & a computer architecture optimized for neural net training, not a GPU cluster.