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LIVE Blog: Tesla AI Day

(Credit: Tesla)

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Tesla’s AI Day is here. In a few minutes, Tesla watchers would be seeing executives like Elon Musk provide an in-depth discussion on the company’s AI efforts on not just its automotive business but on its energy business and beyond as well. AI Day promises to be yet another tour-de-force of technical information from the electric car manufacturer. Thus, it is no surprise that there is a lot of excitement from the EV community heading into the event. 

Tesla has kept the details of AI Day behind closed doors, so the specifics of the actual event are scarce. That being said, an AI Day agenda sent to attendees indicated that they could expect to hear Elon Musk speak during a live keynote, speak with Andrej Karpathy and the rest of Tesla’s AI engineers, and participate in breakout sessions with the teams behind Tesla’s AI development. 

Similar to Autonomy Day and Battery Day, Teslarati would be following along on AI Day’s discussions to provide you with an updated account of the highly-anticipated event. Please refresh this page from time to time, as notes, details, and quotes from Elon Musk’s keynote and its following discussions will be posted here.

Simon 19:40 PT – A question about the use cases for the Tesla Bot was asked. Musk notes that the Tesla Bot would start with boring, repetitive, work, or work that people would least like to do.

Simon 19:25 PT – A question about AI and manufacturing is asked and how it potentially relates to the “Alien Dreadnaught” concept. Musk notes that most of Tesla’s manufacturing today is already automated. Musk also noted that humanoid robots would be done either way, so it would be great for Tesla to do this project, and safely as well. “We’re making the pieces that would be useful for a humanoid robot, so we should probably make it. If we don’t someone else will — and we want to make sure it’s safe,” Musk said.

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Simon 19:15 PT – And the Q&A starts. First question involves open-sourcing Tesla’s innovations. Musk notes that it’s pretty expensive to develop all this tech, so he’s not sure how things could be open-sourced. But if other car companies would like to license the system, that could be done.

Simon 19:11 PT – There will really be a “Tesla Bot.” It would be built by humans, for humans. It would be friendly, and it would eliminate dangerous, repetitive, boring tasks. This is still petty darn unreal. It uses the systems that are currently being developed for the company’s vehicles. “There will be profound applications for the economy,” Musk said.

Simon 19:06 PT – New products! A whole Tesla suit?! After a fun skit, Elon says the “Tesla Bot” would eventually be real.

Simon 19:00 PT – What is crazy is that Dojo is not even done. This is just what it is today. Dojo is still evolving, and it is going to be way more powerful in the future. Now, it’s Elon Musk’s turn. What’s next for Tesla beyond vehicles.

Simon 19:00 PT – Venkataramanan teases the ExaPOD. Yet another revolutionary solution from Tesla. With all this, it is evident that Tesla’s approach to autonomy is on a whole other level. It would not be surprising if it takes Wall Street and the market a few days to fully absorb what is happening here.

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Simon 18:55 PT – The specs of Dojo are insane. Behind its beastly specs, it seems that Dojo’s full potential lies in the fact that all this power is being used to do one thing: to make autonomous cars possible. Dojo is a pure learning machine, with more than 500,000 training nodes being built together. Nine petaflops of compute per tile, 36 terabytes per second of off-tile bandwidth. But this is just the tip of the iceberg for Dojo.

Simon 18:50 PT – Ganesh Venkataramanan, Project Dojo’s lead, takes the stage. He states that Elon Musk wanted a super-fast training computer to train Autopilot. And thus Project Dojo was born. Dojo is a distributed compute architecture connected by network fabric. It also has a large compute plane, extremely high bandwidth with low latencies, and big networks that are partitioned and mapped, to name a few.

(Credit: Tesla)

Simon 18:45 PT – Milan Kovac, Tesla’s Director of Autopilot Engineering takes the stage. He notes that he would discuss how neural networks are run in the company’s cars. He notes that Tesla’s systems require supercomputers.

Simon 18:40 PT – Ashok notes that simulations have helped Tesla a lot already. It has, for example, helped the company identify pedestrian, bicycle, and vehicle detection and kinematics. The networks in the vehicles were traded to 371 million simulated images and 480 million cuboids.

Simon 18:35 PT – Ashok notes that these strategies ultimately helped Tesla retire radar from its FSD and Autopilot suite and adopt a pure vision model. A comparison between a radar+camera system and pure vision shows just how much more refined the company’s current strategy is. The executive also touched on how simulations help Tesla develop its self-driving systems. He states that simulations help when data is difficult to source, difficult to label, or in a closed loop.

Simon 18:30 PT – Ashok returns to discuss Auto Labeling. Simply put, there is so much labeling that needs to be done that it’s impossible to be done manually. He shows how roads and other items on the road are “reconstructed” from a single car that’s driving. This effectively allowed Tesla to label data much faster, while allowing vehicles to navigate safely and accurately even when occlusions are present.

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Simon 18:25 PT – Karpathy returns to talk about manual labeling. He notes that manual labeling that’s outsourced to third-party firms is not optimal. Thus, in the spirit of vertical integration, Tesla opted to establish its own labeling team. Karpathy notes that in the beginning, that Tesla was using 2D image labeling. Eventually, Tesla transitioned to 4D labeling, where the company could label in vector space. But even this was not enough, and thus, auto labeling was developed.

Simon 18:23 PT – The executive states that traffic behavior is extremely complicated, especially in several parts of the world. Ashok notes that this partly illustrated by parking lots and how they are actually complex. Summoning a car from a parking lot, for example, used to utilize 400k notes to navigate, resulting in a system whose performance left much to be desired.

Simon 18:18 PT – Ashok notes that when driving alongside other cars, Autopilot must not only think about how they would drive, they must also think about how other cars would operate. He shows a video of a Tesla navigating a road and dealing with multiple vehicles to demonstrate this point.

Simon 18:15 PT – Director of Autopilot Software Ashok Elluswamy takes the stage. He starts off by discussing some key problems in planning in both non-convex and high-dimensional action spaces. He also shows Tesla’s solution to these issues, a “Hybrid Planning System.” He demonstrates this by showing how Autopilot performs a lane change.

Simon 18:10 PT – Karpathy’s discussion notes that today, Tesla’s FSD strategy is a lot more cohesive. This is demonstrated by the fact that the company’s vehicles could effectively draw a map in real-time as it drives. This is a massive difference compared to the pre-mapped strategies employed by rivals in both the automotive and software field like Super Cruise and Waymo.

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Simon 18:05 PT – The AI Director discusses how Tesla practically re-engineered their neural network learning from the ground-up and utilized a multi-head route. These include camera calibrations, caching, queues, and optimizations to streamline all tasks. Do note that this is an extremely simplified iteration of Karpathy’s discussion so far.

Simon 18:00 PT – Karpathy covers more challenges that are involved in even the basics of perception. Needless to say, AI Day is quickly proving to be Tesla’s most technical event right off the bat. That said, multi-camera networks are amazing. They’re just a ton of work, but it may very well be a silver bullet for Tesla’s predictive efforts.

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Simon 17:56 PT – Karpathy showcases a video of how Tesla used to process its image data in the past. He shows a popular video for FSD that has been shared in the past. He notes that while great, such a system proved to be inadequate, and this is something that Tesla learned when it launched Smart Summon. While per-camera detection is great, the vector space proves inadequate.

Simon 17:55 PT – Karpathy noted that when Tesla designs the visual cortex in its car, the company is modeling it to how a biological vision is perceived by eyes. He also touches on how Tesla’s visual processing strategies have evolved over the years, and how it is done today. The AI Director also touches on Tesla’s “HydraNets,” on account of their multi-task learning capabilities.

(Credit: Tesla)

Simon 17:51 PT – Karpathy starts off by discussing the visual component of Tesla’s AI, as characterized by the eight cameras used in the company’s vehicles. The AI director notes that AI could be considered like a biological being, and it’s built from the ground up, including its synthetic visual cortex.

Simon 17:48 PT – Elon Musk takes the stage. He apologizes for the event’s delay. He jokes that Tesla probably needs AI to solve these “technical difficulties.” The CEO highlights that AI Day is a recruitment event. He calls Tesla’s head of AI Andrej Karpathy. There’s no better person to discuss AI.

Simon 17:45 PT – We’re here watching the AI Day FSD preview video and we can’t help but notice that… are those Waypoints?!

Simon 17:38 PT – Looks like we’ve got an Elon sighting! And a preview video too! Here we go, folks!

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Simon 17:30 PT – A 30-minute delay. We haven’t seen this much delay in quite a bit.

Simon 17:20 PT – It’s a good thing that Tesla has great taste in music. Did Grimes mix this track?

Simon 17:15 PT – We’re 15 minutes in. “Elon Time” is going strong on AI Day. To be honest, though, this music would fit the “Rave Cave” in Giga Berlin this coming October.

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Simon 17:10 PT – A good thing to keep in mind is that AI Day is a recruitment event. Some food for thought just in case the discussions take a turn for the extremely technical. AI Day is designed to attract individuals who speak Tesla’s language in its rawest form. We’re just fortunate enough to come along for the ride.

Tesla Board Member Hiro Mizuno sums it up in this tweet pretty well.

Simon 17:05 PT – I guess AI Day is starting on “Elon Time?” We’re on to the next track of chill music.

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Simon 17:00 PT – And with 5 p.m. PST here, the music is officially live on the AI Day live stream. Looks like we’re in for some wait. Wonder how many minutes it would take before it starts? Gotta love this chill music though.

Simon 16:58 PT – While waiting, I can’t help but think that a ton of TSLA bears and Wall Street would likely not understand the nuances of what Tesla would be discussing today. Will Tesla go three-for-three? It was certainly the case with Battery Day and Autonomy Day.

Simon 16:55 PT – T-minus 5 minutes. Some attendees of AI Day are now posting some photos on Twitter, but it seems like photos and videos are not allowed on the actual venue of the event. Pretty much expected, I guess.

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Simon 16:50 PT – Greetings, everyone, and welcome to another Live Blog. This is Tesla’s most technical event yet, so I expect this one to go extremely in-depth on the company’s AI efforts and the technology behind it. We’re pretty excited.

Don’t hesitate to contact us with news tips. Just send a message to tips@teslarati.com to give us a heads up. 

Simon is an experienced automotive reporter with a passion for electric cars and clean energy. Fascinated by the world envisioned by Elon Musk, he hopes to make it to Mars (at least as a tourist) someday. For stories or tips--or even to just say a simple hello--send a message to his email, simon@teslarati.com or his handle on X, @ResidentSponge.

Investor's Corner

xAI targets $5 billion debt offering to fuel company goals

Elon Musk’s xAI is targeting a $5B debt raise, led by Morgan Stanley, to scale its artificial intelligence efforts.

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(Credit: xAI)

xAI’s $5 billion debt offering, marketed by Morgan Stanley, underscores Elon Musk’s ambitious plans to expand the artificial intelligence venture. The xAI package comprises bonds and two loans, highlighting the company’s strategic push to fuel its artificial intelligence development.

Last week, Morgan Stanley began pitching a floating-rate term loan B at 97 cents on the dollar with a variable interest rate of 700 basis points over the SOFR benchmark, one source said. A second option offers a fixed-rate loan and bonds at 12%, with terms contingent on investor appetite. This “best efforts” transaction, where the debt size hinges on demand, reflects cautious lending in an uncertain economic climate.

According to Reuters sources, Morgan Stanley will not guarantee the issue volume or commit its own capital in the xAI deal, marking a shift from past commitments. The change in approach stems from lessons learned during Musk’s 2022 X acquisition when Morgan Stanley and six other banks held $13 billion in debt for over two years.

Morgan Stanley and the six other banks backing Musk’s X acquisition could only dispose of that debt earlier this year. They capitalized on X’s improved operating performance over the previous two quarters as traffic on the platform increased engagement around the U.S. presidential elections. This time, Morgan Stanley’s prudent strategy mitigates similar risks.

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Beyond debt, xAI is in talks to raise $20 billion in equity, potentially valuing the company between $120 billion and $200 billion, sources said. In April, Musk hinted at a significant valuation adjustment for xAI, stating he was looking to put a “proper value” on xAI during an investor call.

As xAI pursues this $5 billion debt offering, its financial strategy positions it to lead the AI revolution, blending innovation with market opportunity.

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SpaceX to debut new Dragon capsule in Axiom Space launch

Ax-4’s launch marks the debut of SpaceX’s latest Crew Dragon and pushes Axiom closer to building its own space station.

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spacex-dragon-axiom-ax-4-mission-iss
(Credit: SpaceX)

Axiom Space’s Ax-4 mission targets the International Space Station (ISS) with a new SpaceX Crew Dragon capsule.

The Axiom team will launch a new SpaceX Dragon capsule atop a Falcon 9 rocket from NASA’s Kennedy Space Center in Florida on Wednesday at 8:00 a.m. EDT (1200 GMT). The Ax-4 mission launch was initially set for Tuesday, June 10, but was delayed by one day due to expected high winds.

As Axiom Space’s fourth crewed mission to the ISS, Ax-4 marks the debut of an updated SpaceX Crew Dragon capsule. “This is the first flight for this Dragon capsule, and it’s carrying an international crew—a perfect debut. We’ve upgraded storage, propulsion components, and the seat lash design for improved reliability and reuse,” said William Gerstenmaier, SpaceX’s vice president of build and flight reliability.

Axiom Space is a Houston-based private space infrastructure company. It has been launching private astronauts to the ISS for research and training since 2022, building expertise for its future station. With NASA planning to decommission the ISS by 2030, Axiom has laid the groundwork for the Axiom Station, the world’s first commercial space station. The company has already begun construction on its ISS replacement.

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The Ax-4 mission’s research, spanning biological, life, and material sciences and Earth observation, will support this ambitious goal. Contributions from 31 countries underscore the mission’s global scope. The four-person crew will launch from Launch Complex 39A, embarking on a 14-day mission to conduct approximately 60 scientific studies.

“The AX-4 crew represents the very best of international collaboration, dedication, and human potential. Over the past 10 months, these astronauts have trained with focus and determination, each of them exceeding the required thresholds to ensure mission safety, scientific rigor, and operational excellence,” said Allen Flynt, Axiom Space’s chief of mission services.

The Ax-4 mission highlights Axiom’s commitment to advancing commercial space exploration. By leveraging SpaceX’s Dragon capsule and conducting diverse scientific experiments, Axiom is paving the way for its Axiom Station. This mission not only strengthens international collaborations but also positions Axiom as a leader in the evolving landscape of private space infrastructure.

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Tesla named official AV operator in Austin ahead of robotaxi launch

Tesla robotaxis could begin operating around Austin any day now, as echoed by an update to the city’s website.

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Just as Tesla prepares to launch its own commercial robotaxi services in Austin, Texas this month, the company has now appeared on the state’s website as an official operator of autonomous vehicles (AVs).

As of Monday, Tesla has been listed as an AV operator on Austin’s official Department of Motor Vehicles (DMV) site, ahead of the company’s expected launch of the long-awaited service sometime this month. The news, which X user Tesla Yoda first spotted, precedes some reports suggesting the robotaxi service could launch in the coming days, and it comes as the city becomes an increasingly competitive stomping ground for the emerging technology.

Although Tesla has been included on the list, the website says that Tesla is still in the testing phase, alongside most of the other AV operators in the city. At this time, Alphabet-owned robotaxi company Waymo is the only operator listed as being in the deployment phase, while Hyundai-owned company Motional is listed as being in the mapping phase.

Tesla is set to initially deploy the service as a limited pilot program using the company’s existing Model Y vehicles, and it will start by testing them in the safest areas of the city within geo-mapped boundaries as extra safety precautions upon launch.

Below you can see the full list of AV operators on the Austin DMV website at the time of writing, including both the Alphabet-owned Waymo and the Amazon-run Zoox.

Current list of AV operators in Austin

  • ADMT
    • Phase: testing
    • Parent company: VW
  • AVRide
    • Phase: testing
    • Parent company: AVRide Inc
  • Motional
    • Phase: mapping
    • Parent company: Hyundai
  • Waymo
    • Phase: deployment
    • Parent company: Alphabet (Google)
  • Tesla
    • Phase: testing
    • Parent company: Tesla
  • Zoox
    • Phase: testing
    • Parent company: Amazon

READ MORE ON AUTONOMOUS VEHICLES: Elon Musk just revealed more about Tesla’s June Robotaxi launch

Tesla’s Austin robotaxi launch, Full Self-Driving, and other AV companies

The news follows a report from Bloomberg a few weeks ago saying that Tesla was considering a launch date of June 12 for the service, though the validity of that report is still unclear. Additionally, Tesla could still change its plans on a launch date, though the company’s inclusion on the Austin DMV AV operators list appears to be a good sign either way.

The company has also been running internal pilot programs for the robotaxi service in Austin and around the Bay Area, California, with around 300 test operators operating the vehicles in the Texas city since at least April. Last fall, CEO Elon Musk also said that employees had already been piloting a ride-hailing program around the Bay.

Tesla has long touted its Full Self-Driving (FSD) program as the solution to autonomy, with the system utilizing cameras and real-time driver footage to train its AI neural network on how to drive. By comparison, most other companies utilize cameras and radar systems together, while relying on geo-mapped systems to determine where the robotaxi can operate.

Waymo launched driverless ride-hailing services in Austin through a partnership with Uber, though the company has also been running paid robotaxi rides in various parts of California since last year through its Waymo One app. Other companies such as the Amazon-owned firm Zoox and the Hyundai-led company Motional are also preparing to deploy services in Austin and other U.S. cities.

Tesla’s ‘Project Alicorn’ and what it means for the Robotaxi platform

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