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.
Presented some of the recent work from the Tesla Autopilot team at CVPR this year, especially about "Occupancy Networks" – our approach to solve general obstacle detection and using it to enable sophisticated collision avoidance. Full talk here: https://t.co/wpGXlNHaWl (1/12)
— Ashok Elluswamy (@aelluswamy) August 21, 2022
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.
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.
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.”
These predictions are already used to prevent a lot of collisions. For e.g., Autopilot prevents ~40 crashes / day where human drivers mistakenly press the accelerator at 100% instead of the brakes. In the video Autopilot automatically brakes, saving this person's legs (7/12) pic.twitter.com/XtMssPT9cM
— Ashok Elluswamy (@aelluswamy) August 21, 2022
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.
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
SpaceX has updated its target for the thirteenth integrated flight test of Starship, aiming for as early as Thursday, July 23. The 90-minute launch window opens at 5:45 p.m. CT from the company’s Starbase facility in South Texas.
The target flight was initially rescheduled for today, but SpaceX pushed it back again.
This latest adjustment follows an aborted attempt earlier in the week and reflects the iterative, rapid-development approach that has defined the Starship program. With the vehicle already stacked and ground teams making final preparations, the mission represents another step toward proving the full reusability of the world’s most powerful rocket system.
Now targeting to launch Starship’s thirteenth flight test as early as Thursday, July 23 → https://t.co/Rp7VwBzpWx pic.twitter.com/Y0YNzfc5zk
— SpaceX (@SpaceX) July 19, 2026
The original launch attempt on July 16 was scrubbed at T-0 when several Raptor engines on the Super Heavy booster failed to ignite properly. The automatic abort system triggered just as the engines began their startup sequence, preventing liftoff.
SpaceX CEO Elon Musk confirmed that some engines did not start as expected, prompting the decision to replace two Raptors on Booster 20 to ensure reliability. The issue occurred despite a successful full-duration static fire earlier, highlighting the complexities of coordinating 33 engines under flight conditions.
This cautious approach underscores SpaceX’s commitment to safety amid an aggressive test cadence.
Flight 13 builds directly on the lessons from Flight 12 in May 2026. The Super Heavy booster’s primary goals include a successful liftoff, ascent, stage separation, boostback burn, and controlled splashdown in the Gulf of America.
Hardware and software modifications address the off-nominal flip and boostback burn problems from the prior flight, where propellant slosh and engine relight issues led to an uncontrolled impact.
For the Starship upper stage, objectives include deploying 20 operational Starlink V3 satellites, the first real payload of this type, performing a single Raptor engine relight in space, and executing a controlled entry, descent, and splashdown in the Indian Ocean. Propulsion upgrades aim to improve engine-out capability after one vacuum Raptor was lost on Flight 12.
Additional test elements focus on heat shield performance. Six satellites carry cameras to image the tiles during flight, while white-painted tiles and upgraded attachments on flaps and the aft skirt will gather data for future reusability.
The FAA completed its mishap investigation into Flight 12 earlier this month, clearing the regulatory path.
This suborbital mission, the second with V3 vehicles, advances Starship toward operational missions, including potential crewed flights and support for NASA’s Artemis program. Success would mark significant progress in rapid reusability and satellite deployment from the massive system.
Elon Musk dismissed reports claiming SpaceX had placed a massive order for NVIDIA GPUs worth $52 billion. The denial came hours after Taiwanese media, citing unnamed industry sources, reported that SpaceX planned to acquire approximately 13,000 AI server racks, equating to roughly 1 million GB300 GPUs, from Foxconn.
Each rack was estimated at around $4 million, with deliveries potentially starting in late 2025.
The story suggested this would mark SpaceX’s first major foray into Foxconn-manufactured NVIDIA hardware, breaking from suppliers like Supermicro and Dell. Musk responded bluntly on X:
This is fake news
— Elon Musk (@elonmusk) July 20, 2026
Despite the denial, the rumored scale aligns with SpaceX’s explosive growth in AI infrastructure. NVIDIA’s GB300 (successor to the GB200 NVL) racks deliver unprecedented performance for large-scale training and inference. A $52 billion commitment would dwarf most corporate AI budgets and provide the compute muscle needed for frontier models.
SpaceX already operates gigawatt-scale terrestrial clusters like Colossus in Memphis, Tennessee, and has monetized them aggressively through leasing deals.
SpaceX’s newest Starmind will make earth data centers obsolete
Major customers include Anthropic (paying ~$1.25 billion monthly for 220,000+ GPUs), Google (~$920 million monthly for 110,000 GPUs), and Reflection AI. These arrangements are projected to generate tens of billions in annual revenue, far outpacing traditional SpaceX businesses.
Such an investment would fuel internal AI efforts, particularly Grok models under the integrated SpaceXAI division, while supporting ambitious orbital data center plans. SpaceX envisions launching thousands of AI-optimized satellites powered by solar energy and cooled in space, bypassing terrestrial power and land constraints.
This “Starmind” constellation could position the company as a leader in space-based computing.
SpaceX as an Emerging AI Powerhouse
Once primarily known for reusable rockets and Starlink satellite internet, SpaceX has transformed into a multifaceted AI player.
The 2026 acquisition of xAI integrated Grok development directly into the company. Starlink’s low-latency global network complements massive compute clusters, enabling efficient data flow for training and serving AI models.
Musk has long argued that AI scaling demands solutions beyond Earth, citing things like real estate and electricity limits on the ground.
While the Foxconn deal may not be in the cards, SpaceX’s trajectory is continuing on the path of blending aerospace engineering with hyperscale AI to dominate both launches and intelligence infrastructure.
Elon Musk shed more details on the upcoming improvements to Tesla’s Full Self-Driving suite, specifically one that the CEO mentioned last week, which should help owners see fewer interventions.
Last week, Musk hinted that one major improvement that Tesla planned to roll out to Full Self-Driving users was the car’s ability “to remember your specific interventions and match each person’s individual preferences.”
Elon Musk says your Tesla will start to learn your individual preferences
This small bit of detail was linked to a post from Tesla community member Whole Mars, who said that FSD’s tendency to exit the carpool lane, a feature that owners can turn on but at times the car will disregard.
It sounds like, based on Musk’s two responses since that original post, it is safe to say the things FSD will start to remember are wide-ranging. However, it seems the biggest differences will be noticed with parking performance, which Musk continues to mention.
Highway Lane Preferences
The initial post Musk mentioned, with these new remembered preferences soon to arrive for Tesla owners everywhere, was the Carpool/Express Lane.
Tesla has a setting in the FSD menu that lets drivers enable HOV Lane travel. However, the car won’t always stay in that suggested or preferred lane.
The car will start to remember your specific interventions and match each person’s individual preferences
— Elon Musk (@elonmusk) July 18, 2026
Some owners have also complained of left lane camping, an illegal maneuver in at least some states. Cruising in the passing lane has resulted in tickets for some, as it is illegal in over 30 states in the U.S.
Tesla did not confirm if these preferences would also be included in new FSD behaviors, but it would certainly help move the company toward fewer interventions.
Parking Preferences
This seems to be the real focus of the entire operation, as Musk stated several weeks ago that parking was overwhelmingly the most frequent reason for interventions.
The major issue with parking is not necessarily the parking “performance,” as FSD is generally good at parking. It definitely has its issues; we’ve recorded plenty of them, including this one as recent as last week:
Yeah it seems like FSD v14.3.5 is having some issues with parking early on https://t.co/Bw5ULfVmDq pic.twitter.com/RHdpjOEpIo
— TESLARATI (@Teslarati) July 13, 2026
However, the changes coming are more about preferences, meaning where you park and how your car enters the spot, either pulling in or backing in. Owners have also reported that pulling into the correct driveway is a relatively rare thing for FSD, something else that needs to be confronted.
Musk basically confirmed that all of these things would be part of Tesla’s plan to address driver preferences with FSD:
Yes
— Elon Musk (@elonmusk) July 20, 2026
It’s obvious there is something big coming with FSD, and the company’s focus seems to be eliminating any intervention that would be related to preferences. This is probably the biggest bottleneck between Tesla and being fully autonomous. Critical interventions do occur, but they are much less frequent.
The only time a driver should be taking over is because of a critical intervention; this seems to be the goal of Tesla right now.
This all seems to be a priority as Tesla continues to move closer to the prospect of unsupervised driving.
SpaceX adjusts Starship Flight 13 test launch target date once again
Elon Musk debunks $52 billion SpaceX-NVIDIA GPU deal
