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.
Tesla has expanded its branded ‘For Business’ Supercharger program that it launched last year, as yet another company is using the platform to attract EV owners to its business and utilize a unique advertising opportunity.
Francis Energy of Oklahoma is launching four Superchargers in Norman, where the University of Oklahoma is located. The Superchargers, which are fitted with branding for Francis Energy, will officially open tomorrow.
It will not be the final Supercharger location that Francis Energy plans to open, the company confirmed to EVWire.
Back in early September, Tesla launched the new “Supercharger for Business” program in an effort to give businesses the ability to offer EV charging at custom rates. It would give their businesses visibility and would also cater to employees or customers.
“Purchase and install Superchargers at your business,” Tesla wrote on a page on its website for the new program. “Superchargers are compatible with all electric vehicles, bringing EV drivers to your business by offering convenient, reliable charging.”
The first site opened in Land O’ Lakes, Florida, which is Northeast of Tampa, as a company called Suncoast launched the Superchargers for local EV owners.
Tesla launches its new branded Supercharger for Business with first active station
The program also does a great job at expanding infrastructure for EV owners, which is something that needs to be done to encourage more people to purchase Teslas and other electric cars.
Francis Energy operates at least 14 EV charging locations in Oklahoma, spanning from Durant to Oklahoma City and nearly everywhere in between. Filings from the company, listed by Supercharge.info, show the company’s plans to convert some of them to Tesla Superchargers, potentially utilizing the new Supercharger for Business program to advertise.
Moving forward, more companies will likely utilize Tesla’s Supercharger for Business program as it presents major advantages in a variety of ways, especially with advertising and creating a place for EV drivers to gain range in their cars.
Tesla Cybercab is perhaps the most highly-anticipated project that the company plans to roll out this year, and as it is undergoing its testing phase in pre-production currently, there are some things to work through with it.
Over the weekend, an image of the Cybercab being loaded onto a tow truck started circulating on the internet, and people began to speculate as to what the issue could be.
Hmmmmmm… https://t.co/L5hWcOXQkb pic.twitter.com/OJBDyHNTMj
— TESLARATI (@Teslarati) January 11, 2026
The Cybercab can clearly be seen with a Police Officer and perhaps the tow truck driver by its side, being loaded onto, or even potentially unloaded from, the truck.
However, it seems unlikely it was being offloaded, as its operation would get it to this point for testing to begin with.
It appears, at first glance, that it needs assistance getting back to wherever it came from; likely Gigafactory Texas or potentially a Bay Area facility.
The Cybercab was also spotted in Buffalo, New York, last week, potentially undergoing cold-weather testing, but it doesn’t appear that’s where this incident took place.
It is important to remember that the Cybercab is currently undergoing some rigorous testing scenarios, which include range tests and routine public road operation. These things help Tesla assess any potential issue the vehicle could run into after it starts routine production and heads to customers, or for the Robotaxi platform operation.
This is not a one-off issue, either. Tesla had some instances with the Semi where it was seen broken down on the side of a highway three years ago. The all-electric Semi has gone on to be successful in its early pilot program, as companies like Frito-Lay and PepsiCo. have had very positive remarks.
The Cybercab’s future is bright, and it is important to note that no vehicle model has ever gone its full life without a breakdown. It happens, it’s a car.
Nevertheless, it is important to note that there has been no official word on what happened with this particular Cybercab unit, but it is crucial to remember that this is the pre-production testing phase, and these things are more constructive than anything.
Tesla analyst Andrew Percoco of Morgan Stanley teased the company’s dominance in its self-driving initiative, stating that its lead over competitors is “not even close.”
Percoco recently overtook coverage of Tesla stock from Adam Jonas, who had covered the company at Morgan Stanley for years. Percoco is handling Tesla now that Jonas is covering embodied AI stocks and no longer automotive.
His first move after grabbing coverage was to adjust the price target from $410 to $425, as well as the rating from ‘Overweight’ to ‘Equal Weight.’
Percoco’s new note regarding Tesla highlights the company’s extensive lead in self-driving and autonomy projects, something that it has plenty of competition in, but has established its prowess over the past few years.
He writes:
“It’s not even close. Tesla continues to lead in autonomous driving, even as Nvidia rolls out new technology aimed at helping other automakers build driverless systems.”
Percoco’s main point regarding Tesla’s advantage is the company’s ability to collect large amounts of training data through its massive fleet, as millions of cars are driving throughout the world and gathering millions of miles of vehicle behavior on the road.
This is the main point that Percoco makes regarding Tesla’s lead in the entire autonomy sector: data is King, and Tesla has the most of it.
One big story that has hit the news over the past week is that of NVIDIA and its own self-driving suite, called Alpamayo. NVIDIA launched this open-source AI program last week, but it differs from Tesla’s in a significant fashion, especially from a hardware perspective, as it plans to use a combination of LiDAR, Radar, and Vision (Cameras) to operate.
Percoco said that NVIDIA’s announcement does not impact Morgan Stanley’s long-term opinions on Tesla and its strength or prowess in self-driving.
NVIDIA CEO Jensen Huang commends Tesla’s Elon Musk for early belief
And, for what it’s worth, NVIDIA CEO Jensen Huang even said some remarkable things about Tesla following the launch of Alpamayo:
“I think the Tesla stack is the most advanced autonomous vehicle stack in the world. I’m fairly certain they were already using end-to-end AI. Whether their AI did reasoning or not is somewhat secondary to that first part.”
Percoco reiterated both the $425 price target and the ‘Equal Weight’ rating on Tesla shares.
Tesla expands its branded ‘For Business’ Superchargers
Tesla Cybercab ‘breakdown’ image likely is not what it seems
