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.
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.
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.

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.
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.
To solve several problems encountered over the last few years with the previous suite, Tesla re-engineered their NN learning from the ground up and utilized a multi-head route, camera calibrations, caching, queues, and optimizations to streamline all tasks.
(heavily simplified) pic.twitter.com/LG2TRgjxip
— Teslascope (@teslascope) August 20, 2021
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.
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.

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!
We’ve got an Elon sighting
— Rob Maurer (@TeslaPodcast) August 20, 2021
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.
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.
Anybody passionate about real world AI !! https://t.co/ydaWQlkE4O
— HIRO MIZUNO (@hiromichimizuno) August 20, 2021
Simon 17:05 PT – I guess AI Day is starting on “Elon Time?” We’re on to the next track of chill music.
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.
Made it pic.twitter.com/aAWqxgf0bP
— Johnna (@JohnnaCrider1) August 19, 2021
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.
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.
News
Tesla Cybercab spotted with interesting charging solution, stimulating discussion
The port is located in the rear of the vehicle and features a manual door and latch for plug-in, and the video shows an employee connecting to a Tesla Supercharger.
Tesla Cybercab units are being tested publicly on roads throughout various areas of the United States, and a recent sighting of the vehicle’s charging port has certainly stimulated some discussions throughout the community.
The Cybercab is geared toward being a fully-autonomous vehicle, void of a steering wheel or pedals, only operating with the use of the Full Self-Driving suite. Everything from the driving itself to the charging to the cleaning is intended to be operated autonomously.
But a recent sighting of the vehicle has incited some speculation as to whether the vehicle might have some manual features, which would make sense, but let’s take a look:
🚨 Tesla Cybercab charging port is in the rear of the vehicle!
Here’s a great look at plugging it in!!
— TESLARATI (@Teslarati) January 29, 2026
The port is located in the rear of the vehicle and features a manual door and latch for plug-in, and the video shows an employee connecting to a Tesla Supercharger.
Now, it is important to remember these are prototype vehicles, and not the final product. Additionally, Tesla has said it plans to introduce wireless induction charging in the future, but it is not currently available, so these units need to have some ability to charge.
However, there are some arguments for a charging system like this, especially as the operation of the Cybercab begins after production starts, which is scheduled for April.
Wireless for Operation, Wired for Downtime
It seems ideal to use induction charging when the Cybercab is in operation. As it is for most Tesla owners taking roadtrips, Supercharging stops are only a few minutes long for the most part.
The Cybercab would benefit from more frequent Supercharging stops in between rides while it is operating a ride-sharing program.
Tesla wireless charging patent revealed ahead of Robotaxi unveiling event
However, when the vehicle rolls back to its hub for cleaning and maintenance, standard charging, where it is plugged into a charger of some kind, seems more ideal.
In the 45-minutes that the car is being cleaned and is having maintenance, it could be fully charged and ready for another full shift of rides, grabbing a few miles of range with induction charging when it’s out and about.
Induction Charging Challenges
Induction charging is still something that presents many challenges for companies that use it for anything, including things as trivial as charging cell phones.
While it is convenient, a lot of the charge is lost during heat transfer, which is something that is common with wireless charging solutions. Even in Teslas, the wireless charging mat present in its vehicles has been a common complaint among owners, so much so that the company recently included a feature to turn them off.
Production Timing and Potential Challenges
With Tesla planning to begin Cybercab production in April, the real challenge with the induction charging is whether the company can develop an effective wireless apparatus in that short time frame.
It has been in development for several years, but solving the issue with heat and energy loss is something that is not an easy task.
In the short-term, Tesla could utilize this port for normal Supercharging operation on the Cybercab. Eventually, it could be phased out as induction charging proves to be a more effective and convenient option.
News
Tesla confirms that it finally solved its 4680 battery’s dry cathode process
The suggests the company has finally resolved one of the most challenging aspects of its next-generation battery cells.
Tesla has confirmed that it is now producing both the anode and cathode of its 4680 battery cells using a dry-electrode process, marking a key breakthrough in a technology the company has been working to industrialize for years.
The update, disclosed in Tesla’s Q4 and FY 2025 update letter, suggests the company has finally resolved one of the most challenging aspects of its next-generation battery cells.
Dry cathode 4680 cells
In its Q4 and FY 2025 update letter, Tesla stated that it is now producing 4680 cells whose anode and cathode were produced during the dry electrode process. The confirmation addresses long-standing questions around whether Tesla could bring its dry cathode process into sustained production.
The disclosure was highlighted on X by Bonne Eggleston, Tesla’s Vice President of 4680 batteries, who wrote that “both electrodes use our dry process.”
Tesla first introduced the dry-electrode concept during its Battery Day presentation in 2020, pitching it as a way to simplify production, reduce factory footprint, lower costs, and improve energy density. While Tesla has been producing 4680 cells for some time, the company had previously relied on more conventional approaches for parts of the process, leading to questions about whether a full dry-electrode process could even be achieved.
4680 packs for Model Y
Tesla also revealed in its Q4 and FY 2025 Update Letter that it has begun producing battery packs for certain Model Y vehicles using its in-house 4680 cells. As per Tesla:
“We have begun to produce battery packs for certain Model Ys with our 4680 cells, unlocking an additional vector of supply to help navigate increasingly complex supply chain challenges caused by trade barriers and tariff risks.”
The timing is notable. With Tesla preparing to wind down Model S and Model X production, the Model Y and Model 3 are expected to account for an even larger share of the company’s vehicle output. Ensuring that the Model Y can be equipped with domestically produced 4680 battery packs gives Tesla greater flexibility to maintain production volumes in the United States, even as global battery supply chains face increasing complexity.
Elon Musk
Tesla Giga Texas to feature massive Optimus V4 production line
This suggests that while the first Optimus line will be set up in the Fremont Factory, the real ramp of Optimus’ production will happen in Giga Texas.
Tesla will build Optimus 4 in Giga Texas, and its production line will be massive. This was, at least, as per recent comments by CEO Elon Musk on social media platform X.
Optimus 4 production
In response to a post on X which expressed surprise that Optimus will be produced in California, Musk stated that “Optimus 4 will be built in Texas at much higher volume.” This suggests that while the first Optimus line will be set up in the Fremont Factory, and while the line itself will be capable of producing 1 million humanoid robots per year, the real ramp of Optimus’ production will happen in Giga Texas.
This was not the first time that Elon Musk shared his plans for Optimus’ production at Gigafactory Texas. During the 2025 Annual Shareholder Meeting, he stated that Giga Texas’ Optimus line will produce 10 million units of the humanoid robot per year. He did not, however, state at the time that Giga Texas would produce Optimus V4.
“So we’re going to launch on the fastest production ramp of any product of any large complex manufactured product ever, starting with building a one-million-unit production line in Fremont. And that’s Line one. And then a ten million unit per year production line here,” Musk stated.
How big Optimus could become
During Tesla’s Q4 and FY 2025 earnings call, Musk offered additional context on the potential of Optimus. While he stated that the ramp of Optimus’ production will be deliberate at first, the humanoid robot itself will have the potential to change the world.
“Optimus really will be a general-purpose robot that can learn by observing human behavior. You can demonstrate a task or verbally describe a task or show it a task. Even show it a video, it will be able to do that task. It’s going to be a very capable robot. I think long-term Optimus will have a very significant impact on the US GDP.
“It will actually move the needle on US GDP significantly. In conclusion, there are still many who doubt our ambitions for creating amazing abundance. We are confident it can be done, and we are making the right moves technologically to ensure that it does. Tesla, Inc. has never been a company to shy away from solving the hardest problems,” Musk stated.








