Dojo was unveiled at Tesla’s annual AI Day last year but the project was still in its infancy. At AI Day 2022, Tesla unveiled the progress it has made with Dojo over the course of the year.

The supercomputer has transitioned from just a chip and training tiles into a full cabinet. Tesla claims that it can replace six GPU boxes with a single Dojo tile, which it says is cheaper than one GPU box.

Per tray, there are six Dojo tiles. Tesla claims that each tray is equivalent to “three to four full-loaded supercomputer racks”. Two trays can fit in a single Dojo cabinet with a host assembly.

Such a supercomputer naturally has a large power draw. Dojo requires so much power that it managed to trip the grid in Palo Alto.

“Earlier this year, we started load testing our power and cooling infrastructure. We were able to push it over 2 MW before we tripped our substation and got a call from the city,” said Bill Chang, Tesla’s Principal System Engineer for Dojo.

In order to function, Tesla had to build custom infrastructure for Dojo with its own high-powered cooling and power system.

An ‘ExaPOD’ (consisting of a few Dojo cabinets) has the following specs:

• 1.1 EFLOP
• 1.3TB SRAM
• 13TB DRAM

Seven ExaPODs are currently planned to be housed in Palo Alto.

Dojo is purpose-built for AI and will greatly improve Tesla’s ability to train neural nets using video data from its vehicles. These neural nets will be critical for Tesla’s self-driving efforts and its humanoid robot ‘Optimus’, which also made an appearance during this year’s event.

Optimus

Optimus was also first unveiled last year and was even more in its infancy than Dojo. In fact, all it was at the time was a person in a spandex suit and some PowerPoint slides.

While it’s clear that Optimus still has a long way to go before it can do the shopping and carry out dangerous manual labour tasks, as Tesla envisions, we at least saw a working prototype of the robot at AI Day 2022.

“I do want to set some expectations with respect to our Optimus robot,” said Tesla CEO Elon Musk. “As you know, last year it was just a person in a robot suit. But, we’ve come a long way, and compared to that it’s going to be very impressive.”

Optimus can now walk around and, if attached to apparatus from the ceiling, do some basic tasks like watering plants:

The prototype of Optimus was reportedly developed in the past six months and Tesla is hoping to get a working design within the “next few months… or years”. The price tag is “probably less than $20,000”.

All the details of Optimus are still vague at the moment, but at least there’s more certainty around the Dojo supercomputer.

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Karpathy has spent the past five years at Tesla. Prior to Tesla, he was a research scientist at OpenAI working on computer vision and generative modelling. Go back further still and you’ll find he did his PhD at Stanford as part of leading AI expert Fei-Fei Li’s research team.

The departure of Karparthy will be a major loss for Tesla. While at Tesla, Karparthy led the Autopilot Vision team.

Following rumours, Tesla has begun cutting around 10 percent of its workforce. In an email to executives, Tesla CEO Elon Musk wrote that he has a “super bad feeling” about the economy.

Given the record vacancies and strong demand for talent across the tech industry, but especially in AI, some high-profile employees appear to be leaving early of their own accord.

According to The Information, several other high-profile Tesla execs have left the company:

(Photo by David von Diemar on Unsplash)

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Musk has been one of the most prominent figures to warn that AI is a “danger to the public” and potentially the “biggest risk we face as a civilisation”. In 2017, he even said there was just a “five to 10 percent chance of success [of making AI safe]”.

Speaking about London-based DeepMind in a New York Times interview last year, Musk said: “Just the nature of the AI that they’re building is one that crushes all humans at all games. I mean, it’s basically the plotline in ‘War Games’”.

Unveiling a 5ft 8in AI-powered humanoid robot may seem to contradict Musk’s concerns. However, rather than leave development to parties who he believes would be less responsible, Musk believes Tesla can lead in building ethical AI and robotics.

Musk has form in this area after co-founding OpenAI. The company’s mission statement is: “To build safe Artificial General Intelligence (AGI), and ensure AGI’s benefits are as widely and evenly distributed as possible.”

Of course, it all feels a little like building nuclear weapons to deter them—it’s an argument that’s sure to have some rather passionate views on either side.

During the unveiling of Tesla Bot, Musk was sure to point out that you could easily outrun and overpower it.

Tesla Bot is designed to “navigate through a world built for humans” and carry out tasks that are dangerous, repetitive, or boring. One example task is for the robot to be told to go to the store and get specific groceries.

Of course, all we’ve seen of Tesla Bot at this point is a series of PowerPoint slides (if you forget about the weird dance by a performer dressed as a Tesla Bot … which we’re all trying our hardest to.)

The unveiling of the robot followed a 90-minute presentation about some of the AI upgrades coming to Tesla’s electric vehicles. Tesla Bot is essentially a robot version of the company’s vehicles.

“Our cars are basically semi-sentient robots on wheels,” Musk said. “It makes sense to put that into humanoid form.”

AI Day was used to hype Tesla’s advancements in a bid to recruit new talent to the company. 

On its recruitment page, Tesla wrote: “Develop the next generation of automation, including a general purpose, bi-pedal, humanoid robot capable of performing tasks that are unsafe, repetitive or boring.

“We’re seeking mechanical, electrical, controls and software engineers to help us leverage our AI expertise beyond our vehicle fleet.”

A prototype of Tesla Bot is expected next year, although Musk has a history of delays and showing products well before they’re ready across his many ventures. Musk says that it’s important the new machine is not “super expensive”.

Find out more about Digital Transformation Week North America, taking place on 9-10 November 2021, a virtual event and conference exploring advanced DTX strategies for a ‘digital everything’ world.

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“How could it be that Tesla, who has never designed a chip before – would design the best chip in the world?” Musk boasted in 2019. 

Select Car Leasing tested Tesla’s full self-driving microchip, which is developed by Samsung, against 12 other innovations:

Against some of mankind’s greatest innovations, Tesla’s chip is only second to something not designed by any of us—the human brain.

To put the power of Tesla’s chip in perspective, the research highlights just how many of each device below it that it could power. The mind-blowing standouts for me are that it could power 180 RAF F-35 Fighter Jets or 36 Mars Perseverance rovers.

All of this performance was achieved with just 15 watts of increased power consumption over Tesla’s previous microchip. Furthermore, it’s 20 percent cheaper.

“Elon Musk has sent a clear message that the future is in real-world AI. If businesses want to realise the benefits of deploying AI and the competitive advantages that come with it, then they have to be taking AI out of the lab and into the real world, so that AI can learn from the uncontrollable mess that living in the real world involves,” comments Daniel Warner, CEO and Founder of LGN.

(Image Credit: Tesla)

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The founder of Tesla and SpaceX has been one of the most vocal prominent figures in expressing concerns about AI – going as far as to call it humanity’s “biggest existential threat” if left unchecked.

Of course, given the nature of the companies Musk has founded, he is also well aware of AI’s potential.

Back in 2015, Musk co-founded OpenAI – an organisation founded with the aim of pursuing and promoting ethical AI development. Musk ended up leaving OpenAI in February last year over disagreements with the company’s work.

Earlier this week, Musk said that OpenAI should be more transparent and specifically said his confidence is “not high” in former Google engineer Dario Amodei when it comes to safety.

Responding to a piece by MIT Technology Review about OpenAI, Musk tweeted: “All orgs developing advanced AI should be regulated, including Tesla.”

In response to a further question of whether such regulations should be via individual governments or global institutions like the UN, Musk said he believes both.

Musk’s tweet generated some feedback from other prominent industry figures, including legendary Id Software founder John Carmack who recently stepped back from video game development to focus on independent AI research.

Carmack asked Musk: “How would you imagine that working for someone like me? Cloud vendors refuse to spawn larger clusters without a government approval? I would not be supportive.”

Coder Pranay Pathole shared a similar scepticism to Musk’s call as Carmack, saying: “Large companies ask for regulations acting all virtuous. What they are really doing is creating barriers for entry for new competition because only they can afford to comply with the new regulations.”

The debate over the extent of AI regulations and how they should be implemented will likely go on for some time – we can only hope to get them right before a disaster occurs. If you want to help Musk in building AI, he’s hosting a “super fun” hackathon at his place.

Interested in hearing industry leaders discuss subjects like this? Attend the co-located 5G Expo, IoT Tech Expo, Blockchain Expo, AI & Big Data Expo, and Cyber Security & Cloud Expo World Series with upcoming events in Silicon Valley, London, and Amsterdam.

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In a tweet, Musk wrote: “Tesla will hold a super fun AI party/hackathon at my house with the Tesla AI/autopilot team in about four weeks. Invitations going out soon.”

The hackathon will focus on the AI behind Tesla’s problematic AutoPilot feature which has been reported to accelerate erratically. Tesla has denied the claims but the hackathon suggests the company at least wants to make AutoPilot more robust.

Ahead of the hackathon announcement, Musk called for developers to join Tesla’s AI team which, he says, reports directly to him.

Talking up the opportunity, Musk highlighted that Tesla will soon have over a million connected vehicles worldwide. Every Tesla is fitted with the sensors and computing power needed for full self-driving which “is orders of magnitude more than everyone else combined”.

Musk says that an individual’s educational background is irrelevant. However, before you get too excited you can just waltz into Tesla, you will be required to pass a “hardcore coding test”.

Python is used “for rapid iteration” at Tesla to build neural networks before the code is converted into “C++/C/raw metal driver code” for the speed required for such critical tasks as piloting a vehicle.

As part of that need for speed, Tesla is also taking on the challenge of building its own AI chips. Musk says Tesla is seeking world-class chip designers to join the company’s teams based in Palo Alto and Austin.

Musk has been vocal about his fears of AI – calling it a potentially existential threat if left unchecked. However, he is also well aware of its opportunities (if that’s of any surprise given how it’s helping to inflate his and investors’ wallets).

“My actions, not just words, show how critically I view (benign) AI,” Musk wrote.

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Tesla currently uses Nvidia’s silicon for its vehicles. The company’s CEO, Elon Musk, said earlier this month that he’s a “big fan” of Nvidia but that an in-house AI chip would be able to outperform those of the leading processor manufacturer.

During a conference call on Thursday, Huang said its customers are “super excited” about  Nvidia’s Xavier technology for autonomous machines. He also notes that it’s currently in production, whereas Tesla’s rival is yet-to-be-seen.

Here’s what Huang had to say during the call:

“With respect to the next generation, it is the case that when we first started working on autonomous vehicles, they needed our help. We used the 3-year-old Pascal GPU for the current generation of Autopilot computers.

It’s very clear now that in order to have a safe Autopilot system, we need a lot more computing horsepower. In order to have safe computing, in order to have safe driving, the algorithms have to be rich. It has to be able to handle corner conditions in a lot of diverse situations.

Every time there are more and more corner conditions or more subtle things that you have to do, or you have to drive more smoothly or be able to take turns more quickly, all of those requirements require greater computing capability. And that’s exactly the reason why we built Xavier. Xavier is in production now. We’re seeing great success and customers are super excited about Xavier.

That’s exactly the reason why we built it. It’s super hard to build Xavier and all the software stack on top of it. If it doesn’t turn out for whatever reason for them [Tesla] you can give me a call and I’d be more than happy to help.”

The conference call was carried out following the release of Nvidia’s fiscal earnings report where the company reported better-than-expected earnings.

“Growth across every platform – AI, Gaming, Professional Visualization, self-driving cars – drove another great quarter,” said Huang. “Fueling our growth is the widening gap between demand for computing across every industry and the limits reached by traditional computing.”

However, due to lower-than-expected revenue guidance, Nvidia stock fell by six percent on Thursday following the earnings report.

What are your thoughts on Huang’s comments? Let us know below.

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Tesla is a pioneering and forward-looking company and, as our readers know well, AI is the future of just about everything. It would have been a safe bet Tesla intends to be at the forefront.

During a Tesla-hosted party at the NIPS intelligence conference in Long Beach, which has been called ‘draft day’ for how AI companies use it to recruit talent, Musk told attendees: “I wanted to make it clear that Tesla is serious about AI, both on the software and hardware fronts. We are developing custom AI hardware chips.”

No further details were provided about the company’s plans but Musk gave a shout out to Jim Keller, Vice President of Autopilot Hardware & Software Engineering at Tesla, for developing “AI hardware that we think will be the best in the world.”

However, Musk isn’t exactly a full supporter of AI. On multiple occassions he’s voiced his concerns about AI posing an apocalyptic-level threat to mankind if it’s not properly regulated.

“I think we should be very careful about artificial intelligence. If I had to guess at what our biggest existential threat is, it’s probably that. So we need to be very careful,” said Musk. “I’m increasingly inclined to think that there should be some regulatory oversight, maybe at the national and international level, just to make sure that we don’t do something very foolish.”

Musk even recently described his investments in AI research as “keeping an eye on what’s going on”, rather than viable return on capital.

The only thing less surprising than Tesla building AI is Musk’s optimism for driverless cars. While Tesla also manufactures things such as home batteries and even solar panels, the company’s main focus is cars.

Tesla’s vehicles pioneered many semi-autonomous features and have the capabilities to become fully driverless later on after the regulatory and insurance pieces come into place for each country.

At the party, Musk said he believes “half of new cars built ten years from now will be autonomous” and that general artificial intelligence will arrive in around seven or eight years.

What are your thoughts on Tesla building AI chips? Let us know in the comments.

 Interested in hearing industry leaders discuss subjects like this and sharing their use-cases? Attend the co-located AI & Big Data Expo events with upcoming shows in Silicon Valley, London and Amsterdam to learn more. Co-located with the  IoT Tech Expo, Blockchain Expo and Cyber Security & Cloud Expo so you can explore the future of enterprise technology in one place.

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