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Tesla details its self-driving Supercomputer that will bring in the Dojo era

(Credit: Tesla)

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Tesla’s Senior Director of Artificial Intelligence, Andrej Karpathy, detailed the automaker’s self-driving Supercomputer that will era in Dojo. Dojo is Tesla’s 4-dimensional Autopilot training program and was first discussed in 2020 by CEO Elon Musk. Karpathy gave a 40-minute presentation regarding Autonomous Vehicles at the 2021 Conference on Computer Vision and Pattern Recognition (CVPR 2021).

Tesla has been working on its self-driving program for several years, and through that time, it has trained its Autopilot and Full Self-Driving suite by using a Neural Network to make it more accurate and robust in its movement. As a result, Tesla has established itself as one of the companies with the most robust semi-autonomous driving programs globally.

Despite this, Tesla continues to make strides to improve it even further. This started back in August 2020, when CEO Elon Musk detailed Dojo, a 4-dimensional training program that will process monumental volumes of video data. This aligns with Tesla’s recent decision to adopt a Vision-only approach in its vehicles, ditching radar in the Model 3 and Model Y.

Musk said:

“Tesla is developing a NN training computer called Dojo to process truly vast amounts of video data. It’s a beast! Please consider joining our AI or computer/chip teams if this sounds interesting.”

For a long time, Tesla has worked with what Musk called “just been like 2D.” He said that the 4D system would work tremendously better since it’s basically video.

During the Q2 2020 Earnings Call, Musk said:

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“So what we’ve been doing, thus far, has really just been like 2D — mostly 2D, and like I said, well correlated in time. So just hard to convey just how much better a fully 4D system would work — does work. It’s capable of things that if you just look — looking at things as individual pictures as opposed to video — basically, like you could go from like individual pictures to surround video, so it’s fundamental. So the car will seem to have just like a giant improvement.”

Now that Tesla is moving closer to the completion of Dojo, Karpathy talked about the Neural Network, Supercomputers, and the excellent work of Tesla’s Supercomputing team.

In Karpathy’s presentation, the AI head stated that there are three main factors to get a Neural Network signal to work: Large amounts of video, clean data, and diverse scenarios to make the suite as well-rounded as possible. It is evident that through Tesla’s decision to make its two mass-market vehicles vision-based, that large amounts of data is one of the biggest factors. The Model 3 and Model Y have dominated Tesla’s sales numbers globally for some time, meaning they contribute more data to the Neural Network than the other two vehicles in Tesla’s fleet.

Now that Dojo has been in development for some time, Karpathy unveiled some details about the Supercomputer that Tesla uses for data consumption and storage. A slide in the presentation details the specifications:

  • 720 nodes of 8x A100 80 GB (5760 GPUs total)
  • 1.8 EFLOPS (720 nodes * 312 TFLOPS-FP16-A100 * 8 GPU/nodes)
  • 10 PB of “hot tier” NVME storage @ 1.6 TBps
  • 640 Tbps of total switching capacity

Credit: Yarrow B. | YouTube

Karpathy said that these specs make it “roughly the number five Supercomputer in the world” during his presentation.

Now, Dojo is still not released, and Karpathy was unwilling to comment further on the progress or any of the finer points of what will likely bring Tesla close to Level 5 autonomy. Still, there should be more details in the coming months. Tesla has stuck by the 2021 time frame for Dojo since first talking about it, so hopefully, the company will shed more detail on it during the Q2 or Q3 2021 Earnings Call.

Karpathy’s full presentation is available below.

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Joey has been a journalist covering electric mobility at TESLARATI since August 2019. In his spare time, Joey is playing golf, watching MMA, or cheering on any of his favorite sports teams, including the Baltimore Ravens and Orioles, Miami Heat, Washington Capitals, and Penn State Nittany Lions. You can get in touch with joey at joey@teslarati.com. He is also on X @KlenderJoey. If you're looking for great Tesla accessories, check out shop.teslarati.com

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Autonomous vehicle red tape gets slashed by Trump Administration

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Credit: Zoox

The Trump Administration today made several key moves to help with the deployment of autonomous vehicles by cutting overreaching red tape that has stifled growth and innovation for years.

The moves, which were put forth by the National Highway Traffic Safety Administration (NHTSA), aim to grant temporary exemptions to at least one company currently, although that could expand in the coming months. Additionally, it will work with organizations to develop standards and a sound but efficient regulatory landscape.

Zoox is the only company mentioned explicitly by the Trump Administration in its press release announcing the new terms today. They will receive a temporary two-year exemption that will allow the commercial deployment of up to 2,500 vehicles annually for two years.

There is a potential exemption for Robomart, Inc., which “requests a temporary exemption from certain FMVSS No. 500 requirements for a low-speed vehicle operated by an ADS without a human driver onboard. NHTSA will publish a separate notice seeking public comment on its merits once the initial evaluation is complete,” the agency said.

Here are the five new terms that Secretary Sean Duffy has implemented through the NHTSA today:

  1. Allow Zoox to commercially deploy its robotaxis through a temporary exemption.
    This temporary exemption will allow the commercial deployment of up to 2,500 vehicles annually for two years, subject to an enhanced, adaptable oversight structure that can evolve as Zoox’s technology advances.
  2. Accelerate development of first-ever AV performance standards through a partnership with SAE Industry Technologies Consortia (ITC).
    This partnership will fund a three-year, $5 million “A2SCEND” consortium, bringing together experts to gather data and accelerate creation of the first-ever AV performance standards. This project will inform a single national standard for AV safety to eliminate the patchwork regulatory landscape that has stifled innovation for years.
  3. Publish an interim final rule that allows vehicles manufactured prior to an exemption to be eligible for a commercial deployment exemption.
    This rule will modernize the application process and improve access to exemptions for innovators, including AV developers, by granting the NHTSA Administrator the discretion to apply temporary exemptions to vehicles manufactured prior to the effective date of an exemption grant.
  4. Streamline the application process for Part 555 exemptions by updating guidance and soliciting feedback from the public.
    By updating the Part 555 exemption process—which allows automakers to temporarily sell a limited number of non-compliant vehicles, primarily to test new technologies—NHTSA is aiming to create a more flexible oversight structure for exemptions and summarize recent AV framework activities, including expanded exemption pathways, streamlined crash reporting, and ongoing efforts to modernize Federal Motor Vehicle Safety Standards (FMVSS).
  5. Establish a new Federal Docket for public feedback on NHTSA’s updated safe AV development and deployment guidance.
    NHTSA is updating its technical guidance for AVs for the first time since 2017—focusing on key safety areas like emergency responder interactions, safety management systems, remote assistance, and post-crash behavior to help the industry scale up driverless deployments safely.

Additionally, the NHTSA said it has modernized some safety standards by proposing updates to:

  • FMVSS 102 – Transmission shifting
  • FMVSS 103/104 – Windshield defrosting and wiping
  • FMVSS 110 – Tire placards
  • FMVSS 135 – Braking systems
  • FMVSS 101 – Controls and displays
  • FMVSS 108 – Vehicle lighting
  • FMVSS 111 – Mirrors and rearview display
  • FMVSS 126 – Electronic stability control systems
  • FMVSS 201/208 – Sun visors and warning labels

These changes aim to make the regulatory process for autonomous vehicles more streamlined and efficient, which could help the U.S. gain dominance over autonomous vehicle systems moving forward.

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Elon Musk has a crazy prediction about AI in two years

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Daniel Oberhaus, CC BY-SA 4.0 , via Wikimedia Commons

Elon Musk is, in many respects, one of the biggest and most influential figures in modern-day artificial intelligence.

Given that Tesla, SpaceX, and xAI are all looked at in their respective fields as leaders to an extent, each of them has a heavy influence on the future of AI, even though two of them are not thought of, at face value, as AI companies.

Musk has grand expectations for what is to come with AI, not only as a form of assistance to make human lives easier, but to make humans multiplanetary and solve some of the biggest issues that face us today. But even he is astounded by AI’s pace of progress.

He believes that in two years, AI will be so mind-blowing it might be unrecognizable.

This progress can be seen in a variety of ways, but perhaps the most popular way people have shown AI’s progress, especially on social media, is through an incredibly arbitrary way of watching Will Smith eat spaghetti:

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This is a great way to show people how AI is improving, especially from a perspective that examines how it can manufacture images and video from prompts. AI is an incredibly complex concept, however, and it goes much deeper than Will Smith eating Italian food.

Musk’s most widely adopted method of AI is likely Tesla Full Self-Driving, which impacts millions of people as they utilize it to increase safety with their travel. Musk has routinely pushed incredibly aggressive timelines for self-driving, especially unsupervised.

Perhaps this perspective is why he feels that things will be solved in a timeframe that is much more aggressive than most of us would think. Regardless, the progress of AI is moving fast, and it seems that Musk’s expectations for it could be high.

But if it can actually achieve full-length motion pictures and even more realistic production value, it will be hard to distinguish between reality and AI very soon.

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Tesla just built it 10 millionth car

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Credit: Tesla

Tesla just officially confirmed it has built its 10 millionth car, a major milestone for the company that started producing sustainable electric powertrains less than two decades ago.

In that time, Tesla has truly revolutionized the automotive industry, disrupting the idea of what a car should be, how it should be fueled, and how it truly impacts day-to-day life.

Tesla achieved this feat across four production facilities: the Fremont Factory in Fremont, California, Gigafactory Shanghai in China, Gigafactory Berlin in Germany, and Gigafactory Texas in Austin, Texas.

The 10 millionth vehicle was a Diamond Black Model Y.

Over the course of the past roughly 18 years, Tesla has evolved its lineup from a sporty sedan built on a Lotus body to a lineup of various body styles, performance metrics, and other characteristics that make each one unique.

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This is an incredible achievement for a company that is young compared to what it goes up against. When Tesla entered the automotive market, Ford, GM, and Stellantis widely dominated the playing field. Since then, Tesla has caused such a disruption that these three massive brands had to scramble to create EV projects of their own.

Despite their best efforts, they have not been able to match the prowess or the effectiveness of Tesla. They are all reliant on Tesla’s charging infrastructure, their software is inferior, and their self-driving projects are elementary in comparison.

Tesla felt its fair share of growing pains over the years as well. As recent at 2019, there were complaints about build quality, paint quality, and overall luxuriousness. These things have all been improved upon through the company’s maturity, and these strides in quality have led to this 10 million vehicle production achievement, something that other small-and-scrappy EV makers will hope to accomplish one day.

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