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.
Investor's Corner
Tesla price targets drop in shock move from three Wall Street firms
Despite Tesla not being an automotive company exclusively, the Wall Street firms and analysts covering its shares are widely dialed in on its performance regarding quarterly deliveries. While it holds some importance, Tesla, from an internal perspective, is more focused on end-to-end AI, Robotaxi, self-driving, and its Optimus robot.
Tesla price targets (NASDAQ: TSLA) have received several cuts over the past few days as Wall Street firms are adjusting their forecast for the company’s stock following a miss in quarterly delivery figures for the first quarter.
Despite Tesla not being an automotive company exclusively, the Wall Street firms and analysts covering its shares are widely dialed in on its performance regarding quarterly deliveries. While it holds some importance, Tesla, from an internal perspective, is more focused on end-to-end AI, Robotaxi, self-driving, and its Optimus robot.
In a notable shift underscoring mounting caution on Wall Street, three prominent investment banks slashed their price targets on Tesla Inc. shares over the past two weeks following the electric-vehicle giant’s disappointing first-quarter 2026 delivery numbers. The revisions highlight softening EV sales figures and, according to some, execution challenges.
Tesla delivered 358,023 vehicles in the January-to-March period, a 14 percent sequential decline and a miss versus consensus forecasts of roughly 365,000 to 370,000 units.
Production hit 408,000 vehicles, yet the delivery shortfall, paired with limited updates on autonomous-driving progress and new-model timelines, rattled investors. Shares fell about 8.7 percent since April 1.
Wall Street analysts are now adjusting their forecasts accordingly, as several firms have made adjustments to price targets.
Goldman Sachs
Goldman Sachs cut its target from $405 to $375 while maintaining a Hold rating. Analyst Mark Delaney pointed to soft EV sales trends and margin pressures.
Truist Financial followed on April 2, lowering its target from $438 to $400 (Hold unchanged), with analyst William Stein citing misses in both auto deliveries and energy-storage deployments, plus a lack of fresh details on AI initiatives and upcoming vehicles.
It is a strange drop if using AI initiatives and upcoming vehicles as a justification is the primary focus here. Tesla has one of the most optimistic outlooks in terms of AI, and CEO Elon Musk recently hinted that the company is developing something for the U.S. market that will be good for families.
Baird
Baird’s Ben Kallo made a very modest trim, reducing its target from $548 to $538, keeping and maintaining the ‘Outperform’ rating it holds on shares. Kallo said the price target adjustment was a prudent recalibration tied to near-term risks.
Truist
Truist analyst William Stein pointed to deliveries and energy storage missing expectations, and cut his price target to $400 from $438. He maintained the ‘Hold’ rating the firm held on the stock previously.
JPMorgan
Adding to the bearish tone on Monday, April 6, JPMorgan’s Ryan Brinkman reiterated an Underweight (Sell) rating and $145 price target, implying roughly 60 percent downside from recent levels.
Brinkman highlighted a “record surge in unsold vehicles” that adds to free-cash-flow woes, with inventory swelling to an estimated 164,000 units.
Tesla’s comfort level taking risks makes the stock a ‘must own,’ firm says
He lowered his Q1 2026 EPS estimate to $0.30 from $0.43 and full-year 2026 EPS to $1.80 from $2.00, both below consensus. Brinkman noted that expectations for Tesla’s performance have “collapsed” across financial and operating metrics through the end of the decade, yet the stock has risen 50 percent, and average price targets have increased 32 percent.
This disconnect, he argued, prices in an unrealistic sharp pivot to stronger results beyond the decade, while near-term realities remain materially weaker.
He advised investors to approach TSLA shares with a “high degree of caution,” citing elevated execution risk, competition, and valuation concerns in lower-price, higher-volume segments.
The revisions have pulled the overall consensus lower. Aggregators show the average 12-month price target now ranging from approximately $394 to $416 across roughly 32 analysts, with a prevailing Hold rating and a mixed split of Buy, Hold, and Sell recommendations.
Brinkman’s $145 target stands as a notable outlier on the bearish side.
Not Everyone Has Turned Bearish on Tesla Shares
Not all firms turned more pessimistic. Wedbush Securities held its bullish $600 target, stressing that AI and full self-driving technology represent the core value drivers, with current delivery softness viewed as temporary.
These moves reflect a broader Wall Street recalibration: near-term EV demand faces pressure from high interest rates, intensifying competition, especially from lower-cost Chinese rivals, and slower adoption.
At the same time, many analysts continue to see Tesla’s technology leadership in software-defined vehicles, autonomy, robotaxis, and energy storage as pathways to outsized long-term gains once macro conditions ease and new models launch.
With Tesla’s first-quarter earnings report due later this month, upcoming details on cost discipline, Cybertruck ramp-up, and AI roadmaps will likely shape whether these target adjustments prove prescient or overly cautious. Investors remain divided between immediate delivery realities and the company’s ambitious vision.
Tesla shares are trading at $348.82 at the time of publishing.
Elon Musk
Tesla Full Self-Driving feature probe closed by NHTSA
Actually Smart Summon allows owners to move their parked Tesla via a smartphone app remotely, directing the vehicle short distances in parking lots or private property while the driver supervises from the phone.
A probe into a popular Tesla self-driving feature has been closed by the National Highway Traffic Safety Administration (NHTSA) after over a year of scrutiny from the government agency.
The NHTSA has officially closed its investigation into Tesla’s Actually Smart Summon (ASS) feature, marking a regulatory win for the electric vehicle maker after more than a year of scrutiny.
Here’s our coverage on the launch of the probe:
Tesla’s Actually Smart Summon feature under investigation by NHTSA
The preliminary investigation, opened last January, examined roughly 2.59 million Tesla vehicles equipped with the feature across the Model S, Model X, Model 3, and Model Y lineups. ASS is not available for Cybertruck currently.
Actually Smart Summon allows owners to move their parked Tesla via a smartphone app remotely, directing the vehicle short distances in parking lots or private property while the driver supervises from the phone.
Here’s a clip of us using it:
Summon has had some good performances for me in the past
This was in October: https://t.co/w69Zp2bqeg pic.twitter.com/PVXSRj19E0
— TESLARATI (@Teslarati) April 5, 2026
Introduced as an upgrade to the original Smart Summon, the feature was designed to enhance convenience but drew attention after reports of low-speed incidents where vehicles bumped into stationary objects like posts, parked cars, or garage doors.
The NHTSA’s Office of Defects Investigation reviewed 159 incidents, including one formal Vehicle Owner’s Questionnaire complaint and media reports.
Notably, all events occurred at very low speeds, resulted only in minor property damage, and involved zero injuries or fatalities. The agency determined that the incidents were “extremely rare”, a fraction of one percent across millions of Summon sessions, and did not indicate a systemic safety-related defect.
A key factor in the closure was Tesla’s proactive response through over-the-air (OTA) software updates.
During the probe, Tesla deployed at least six updates that improved camera-based object detection, enhanced neural network performance for obstacle recognition, and refined the system’s response to potential hazards. These iterative improvements, delivered wirelessly to the entire fleet, addressed the primary concerns around detection reliability and operator reaction time.
Critics of Tesla’s autonomous features had initially pointed to the crashes as evidence of rushed deployment, especially given the feature’s reliance on the company’s vision-only Full Self-Driving (FSD) stack. However, NHTSA’s decision to close the case without seeking a recall underscores the low-severity nature of the events and the effectiveness of software-based fixes in modern vehicles.
It definitely has its flaws. I used ASS yesterday unsuccessfully:
It was pouring when I left the gym so I tried to Summon my Model Y
It turned the opposite way and drove out of range, stopping here and forcing me to walk even further across the lot in the rain for it 🤣
One day pic.twitter.com/iD10c8sriB
— TESLARATI (@Teslarati) April 5, 2026
However, improvements will come, and I’m confident in that.
The closure comes as Tesla continues to push boundaries with its autonomous driving ambitions, including unsupervised FSD rollouts and robotaxi initiatives. For owners, the ruling reinforces confidence in Actually Smart Summon as a convenient, low-risk tool rather than a hazardous experiment.
While broader NHTSA reviews of Tesla’s higher-speed FSD capabilities remain ongoing, this outcome highlights how data-driven analysis and rapid OTA remediation can satisfy regulators in the evolving landscape of automated driving technology.
Tesla has not issued an official statement on the closure, but the move is widely viewed as bullish for the company’s autonomy roadmap, reducing one layer of regulatory overhang and allowing focus on further refinements.
Elon Musk
Tesla uses Model S and X ‘sentimental’ value to enforce massive pricing move
By slashing production and creating immediate scarcity, the company has transformed these remaining vehicles into limited-edition relics. The price hike is not driven by rising material costs or new features.
Tesla is using the “sentimental” value that CEO Elon Musk talked about with the Model S and Model X to enforce one of the most massive pricing moves it has ever applied as it begins to phase out the flagship vehicles.
Tesla quietly executed one of its most calculated pricing plays yet. After officially ending production of the Model S and Model X, the company raised prices on every remaining new and demo unit by roughly $15,000.
The refreshed starting prices now sit at:
- $109,990 for the Model S AWD
- $124,900 for the Model S Plaid
- $114,900 for the Model X AWD
- $129,900 for the Model X Plaid
NEWS: Tesla has raised the price on all remaining new (and demo) Model S and Model X vehicles left in inventory by $15,000.
New starting prices:
• Model S AWD: $109,990
• Model S Plaid: $124,900
• Model X AWD: $114,900
• Model X Plaid: $129,900 pic.twitter.com/qBEhsYAfXr— Sawyer Merritt (@SawyerMerritt) April 5, 2026
Every vehicle comes fully loaded with the Luxe Package, Full Self-Driving Supervised, four years of premium connectivity and service, and lifetime free Supercharging. What looks like a simple inventory adjustment is, in reality, a masterclass in monetizing nostalgia.
These are not ordinary cars. For many owners, the Model S and Model X represent the purest expression of Tesla’s original promise—the sleek, over-engineered flagships that proved electric vehicles could be faster, quieter, and more desirable than their gasoline counterparts.
Tesla removes Model S and X custom orders as sunset officially begins
They are the vehicles that carried Elon Musk’s vision from Silicon Valley startup to global automaker.
The final units rolling off the line carry an emotional weight that numbers alone cannot capture. Buyers are not simply purchasing transportation; they are acquiring a piece of Tesla history, the last examples of the very models that defined the brand’s first decade.
Tesla, with this move, understands this sentiment deeply.
By slashing production and creating immediate scarcity, the company has transformed these remaining vehicles into limited-edition relics. The price hike is not driven by rising material costs or new features.
It is driven by the knowledge that a certain segment of buyers, loyalists, collectors, and enthusiasts, will pay a premium precisely because these cars are about to disappear. The strategy converts emotional attachment into margin.
Where other automakers might discount outgoing models to clear lots, Tesla is betting that sentiment is worth more than volume.
The move also quietly rewards existing owners. Scarcity instantly boosts resale values for the hundreds of thousands of Model S and X already on the road, reinforcing brand loyalty among the very people who helped build Tesla’s reputation.
In the end, Tesla’s pricing decision reveals a sophisticated understanding of its audience. As the company pivots toward next-generation platforms, it has found a way to extract one final, lucrative chapter from its heritage.
For buyers willing to pay the new prices, the premium is not just for the car; it is for the feeling of owning the last true originals. Tesla has turned sentiment into strategy, and in the process, reminded everyone that even in the EV era, emotion remains a powerful line on the balance sheet.
Tesla price targets drop in shock move from three Wall Street firms
Tesla Full Self-Driving feature probe closed by NHTSA
