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Tesla Autopilot now enables the car to perceive space around it Tesla Autopilot now enables the car to perceive space around it

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Tesla Autopilot now enables the car to perceive space around it

Credit: Ashok Elluswamy

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Tesla Autopilot is now enabling the car to perceive the space around it thanks to the development of its Occupancy Networks. Tesla’s Autopilot Software Director, Ashok Elluswamy, shared a detailed thread on Twitter about a recent workshop the Autopilot team held. He also shared the workshop on Twitter.

In the video and Twitter Thread, Ashok explained how Tesla developed Occupancy Networks to literally give the car a sense of its surroundings. Humans have the ability to understand the objects around them at any given time. Is that car down the road moving at a slow speed or a fast speed? Do I, a pedestrian, have enough time to get across the street before being hit? What is that in the middle of the road? What is that falling from the sky? I should move out the way.

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These reactions to scenarios and split-second decisions come naturally to humans. Tesla’s Autopilot Team is working to program the vehicles to do the same thing and this will save lives. Imagine the car being able to correctly detect its surroundings while the driver isn’t even paying attention. An example is sudden unintended accelerations (SUA). Ashok pointed out that Autopilot prevents around 40 of these types of accidents daily.

The workshop was held in June at this year’s Conference on Computer Vision and Pattern Recognition (CVPR.) in New Orleans. Ashok explained that the team developed Occupancy Networks which enable the car to predict the volumetric occupancy of everything around it.

Ashok explained that the typical approaches such as image-space segmentation of free space or pixel-wise depth have many issues. The solution to those issues is Occupancy Networks.

In other words, Occupancy Networks enable the car to perceive the space around it and determine whether or not it can drive in that space. For example, if a UFO were to suddenly crash in front of you while you’re driving, you would react quickly in the safest way possible. This is what the Autopilot Team is training the software to do.

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Ashok shared details of how Occupancy Networks used Neural Radience Fields (NeRFs). “The occupancy representation of these networks allows for differentiable rendering of images (based on the Neural Radiance Fields work). However, unlike typical NeRFs, which are per scene, these occupancy nets generalize across scenes.”

You can read Ashok’s full Twitter thread here and you can watch his presentation here. We are a little over a month before Tesla’s AI Day and I’m sure Tesla will share more about the life-saving technology it is working on as well as the Optimus Bot.

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Dr. Know It All recently published a video about the new 10.69 update and shared his thought about Occupancy Network.

In a message on Twitter, he told me, “The beauty of Occupancy Networks is that the car doesn’t have to know what the objects it sees are, it just has to know that they are there in order to avoid them!”

Note: Johnna is a Tesla shareholder and supports its mission. 

Your feedback is important. If you have any comments, concerns, or see a typo, you can email me at johnna@teslarati.com. You can also reach me on Twitter @JohnnaCrider1

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Johnna Crider is a Baton Rouge writer covering Tesla, Elon Musk, EVs, and clean energy & supports Tesla's mission. Johnna also interviewed Elon Musk and you can listen here

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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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Tesla Q2 delivery consensus confirms this long-standing theory

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Credit: Joe Tegtmeyer/X

Tesla released what analysts believe the company will report in terms of deliveries and energy deployments for Q2, but the figures seem to confirm a long-standing theory on the company’s vehicle division.

For years, Tesla was just looked at as a car company. Now that it has established itself as a powerhouse in energy, AI, and tech as a whole, the company is now less hellbent on achieving quarterly growth, on a sequential basis, at least from a major standpoint.

Tesla topped out its annual deliveries in 2023 at 1.81 million, and in the two years since, the company has reported a decrease in deliveries for the entire 12-month term both times.

With Tesla delivering 358,023 cars in Q1, a 6.3 percent increase over Q1 2025, but falling short of Wall Street expectations at 365,000-370,000 units, the narrative around vehicle deliveries and their importance continued to change earlier this year. Some might say it is convenient, but others might say it is the typical evolution of a company that continues to change over time.

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For Q2, Tesla’s delivery consensus estimates sit at 406,024 units, analysts believe. They were surveyed from Daiwa, DB, Wedbush, Cowen, Canaccord, Baird, Wolfe, BMP Paribas, Goldman Sachs, RBC, Evercore ISI, Barclays, Bank of America, Wells Fargo, Morgan Stanley, Truist, UBS, Jefferies, JPM, Needham & Co., HSBC, and William Blair.

Credit: Tesla

Tesla is also expected to report deployments of 13.8 GWh this quarter.

The change to Tesla’s overall narrative now leans less on vehicle deliveries and more on its other projects. Most notably, Tesla’s Robotaxi project has taken the priority over most of its other business ventures, and investors and the public are more concerned about the deployment of vehicles into the fleet, the operation of a driverless ride-hailing service, Cybercab production and operation, and expansion into new cities.

Tesla analyst realizes one big thing about the stock: deliveries are losing importance

This big narrative switch happened when Tesla indicated it was looking at making transportation a service by launching a ride-hailing service that will operate using Tesla’s Full Self-Driving suite. Once unsupervised operation begins, Robotaxi could be a new way for people to get around, all without a driver in their car.

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Instead, they will rely on the billions of miles Tesla has accumulated from its real-world fleet.

It is important to note that Tesla remains significant in the automotive sector, and deliveries must continue as they have for years. Tesla still has a strong automotive business and needs to execute further on all facets to keep its investors happy.

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