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Tesla’s applications for Dojo in FSD, Optimus and potentially more

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Much excitement surrounding Tesla’s Dojo supercomputing cluster has been swirling in recent months since the system went online, and the automaker already expects it to be one of the world’s most powerful supercomputers by early next year. But one reporter recently noted that Dojo could someday have additional uses beyond processing vast amounts of data for Tesla’s Full Self-Driving (FSD) system and humanoid robot.

Dojo can process millions of terabytes of video data per second from the company’s vehicles, training its neural network at an incredible rate. The company has said that the video foundation models input to Dojo would effectively serve as the brain of its vehicles and its Optimus robot.

In a recent video segment about how Dojo is expected to revolutionize self-driving, however, Yahoo Finance reporter Pras Subramanian also talked about the supercomputing cluster’s potential applications beyond FSD and Optimus.

The short discussion, hosted by Seana Smith, details how the Dojo system will use Tesla’s AI model to train FSD. However, Subramanian also says the supercomputer could someday be used for vessels other than cars, including motorcycles, bicycles and boats. The conversation also touched on how Dojo works, the complexity of training AI to handle roads and Ford and Volkswagen’s decision to end Argo AI operations, among other topics.

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You can watch a short clip from the video segment below or see the full conversation here.

As for cars, Musk has previously talked about the potential of using Dojo to perform traffic control simply with the system’s inputs for things like accidents, potholes, road closures or other data that would be useful for a Tesla to access in real-time. Musk said in June that Dojo had been “online and running useful tasks for a few months,” helping out with production workloads and spurring on the current round of excitement surrounding the computing cluster.

In June, Tesla posted about Dojo on X, detailing how its neural networks were already being accessed in its cars and adding that the company is “building the foundation models for autonomous robots.” Below is an excerpt from the thread:

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“Our multi-modal neural networks are already in customer vehicles—these networks take in arbitrary modalities such as camera videos, maps, navigation, IMU (Inertial Measurement Unit), GPS etc.

Tasks such as Occupancy prediction are already quite general in what they represent—in some ways, they are ontology-free & simply predict the probability that some 3D position is occupied.

Such occupancy can be used for collision avoidance by any robot.

All of this is enabled by fleet scale auto-labelling. By using video data from multiple trips in the same location, we can reconstruct the entire scene

In addition, we’re building off state-of-the-art generative modeling techniques—enabling us to predict possible outcomes given past observations, in a jointly consistent manner across multiple camera views”

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In 2021, Musk said that Dojo could likely someday reduce traffic fatalities by 90 percent and eventually it may be able to reduce them by more than 99 percent.

Last month, a report showed that Tesla had doubled its order of D1 Dojo chips for next year from Taiwan Semiconductor Manufacturing Company (TSMC), now totaling 10,000 units. According to the report, the company also plans to increase its order in 2025. Morgan Stanley also said last month that Dojo could add $500 billion to Tesla’s enterprise value.

Tesla Dojo trade secrets lawsuit officially settles out of court

What are your thoughts? Let me know at zach@teslarati.com, find me on X at @zacharyvisconti, or send your tips to us at tips@teslarati.com.

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Zach is a renewable energy reporter who has been covering electric vehicles since 2020. He grew up in Fremont, California, and he currently lives in Colorado. His work has appeared in the Chicago Tribune, KRON4 San Francisco, FOX31 Denver, InsideEVs, CleanTechnica, and many other publications. When he isn't covering Tesla or other EV companies, you can find him writing and performing music, drinking a good cup of coffee, or hanging out with his cats, Banks and Freddie. Reach out at zach@teslarati.com, find him on X at @zacharyvisconti, or send us tips at tips@teslarati.com.

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Tesla reveals huge Cybercab detail in new guide for First Responders

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Credit: Tesla

Tesla revealed a major new Cybercab detail in a guide it released for First Responders, showing new territory in its beliefs and intentions for the ride-hailing-focused vehicle that entered production in April.

The First Responders Guide is released to give fire departments, paramedics, and other emergency personnel the proper guidance on what to do in the event of an accident, entrapment, or other situation that would require immediate attention.

On one of the pages of the First Responders Guide, Tesla revealed a stark detail about the Cybercab, which could help personnel enter the vehicle more easily in case of an emergency.

Tesla Cybercab has one important piece that AI4 cars might need for FSD

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It shows Tesla has no intention of releasing any Cybercab units that were initially proposed for ride-hailing services for the general public with any manual controls, meaning a steering wheel or pedals:

“A Cybercab equipped with steering wheel, brake pedal, and an acceleration pedal is typically an engineering or test vehicle, and operates at SAE Level 2 autonomy. Cybercab is not typically equipped with a steering wheel or acceleration and brake pedals.”

This is a major development for those who continue to believe Tesla planned to release the Cybercab with any sort of manual controls so that passengers could take over if needed. However, when Tesla started manufacturing production versions of the Cybercab in Giga Texas earlier this year, they were spotted without a steering wheel or pedals.

It essentially confirms the company has no intentions of bringing manual controls to the car’s production versions. Some have argued that the likelihood of Tesla having something

There still are some Cybercab units out there with a steering wheel and pedals, and as Tesla said, these cars are engineering or test vehicles, which have Safety Monitors on board to help the car out of a precarious situation or emergency.

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Tesla Full Self-Driving v14 ‘Lite’ Release Notes: new capabilities and features

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(Credit: Megan Gale/Twitter)

Tesla released the Full Self-Driving v14 ‘Lite’ suite to owners of Hardware 3 or AI3 vehicles today, adding several new features to the vehicles that were once believed to be capable of unsupervised self-driving.

Now, Tesla has released this modified suite to older Tesla vehicles, adding plenty of new features and capabilities.

Here are the full release notes for the suite:

  • Distilled the intelligence from HW4 V14 into HW3. This allows HW3 to directly learn how to handle scenarios using HW4 V14 as a guide. This process unlocks the improvements that have been made to HW4 including Reinforcement Learning (RL) and offline models for HW3.
  • Improved both proactive and reactive responsiveness across a wide variety of categories including navigation handling, merges and forks, pedestrian interactions, traffic lights, and vehicle cut-in scenarios.
  • Improved general comfort in nominal scenarios through fewer false slowdowns, smoother steering and more consistent lane centering.
  • Introduced parking, unparking, and reversing capabilities.
  • Added Arrival Options for you to select where FSD should park: in a Parking Lot, on the Street, in a Driveway, or at the Curbside.
  • Speed Profiles are now available at all times, to further customize driving style preference.

These improvements, according to Tesla’s Head of AI, Ashok Elluswamy, help distill the driving behavior from AI4’s v14 series into both the camera and compute configurations of AI3.

Tesla Full Self-Driving v14 ‘Lite’ for older cars finally gets released

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He added:

“It includes destination options and speed profiles on city roads, but more importantly significantly improved safety. We hope you’ll enjoy it, once the build ships wide.”

Tesla will continue to roll out the v14 Lite suite more widely in the coming weeks, the company said.

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Tesla Full Self-Driving v14 ‘Lite’ for older cars finally gets released

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tesla model 3 model y
Credit: Tesla Inc.

Tesla has finally released its Full Self-Driving v14 ‘Lite’ suite for older cars that equip the Hardware 3 or AI 3 chip, which have not been able to handle the newest versions of the company’s driver assistance software.

Tesla officially started releasing the v14 Lite suite to owners in the Early Access Program last night. The company’s Head of AI, Ashok Elluswamy, said that the rollout will continue over the next few weeks. The build distills the driving behavior from AI4’s v14 series into both the camera and compute configurations of an AI3 car.

It also includes a variety of new features that were available to AI4 cars running v14, including:

  • Start Self-Driving from Park
  • Arrival and Parking Options
  • Speed Profiles

The release is highly anticipated because those owners with AI3 vehicles were early adopters into the FSD platform and were promised that their cars would be capable of achieving Full Self-Driving.

However, Tesla CEO Elon Musk admitted during the company’s recent Q1 Earnings Call that these vehicles would not be capable of achieving unsupervised Full Self-Driving, which is what Tesla had originally said.

Owners were not pleased with this answer, or the idea that their commitment to buying the suite outright for thousands of dollars would not yield the ability to drive without operating the car. Tesla gave some solutions for this, including a discount on a new car, or an upgrade to an AI4 or AI5 self-driving computer and new, upgraded cameras.

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Tesla owners do not seem pleased with these options, as they require giving the company more money.

Nevertheless, it is important to note that Tesla came through for owners here by releasing v14 Lite before the end of Q2, something it had promised owners during the previous Earnings Call. Tesla has had trouble keeping up with timelines, but this is a big achievement for the team.

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