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
Investor's Corner
Tesla deliveries get a big boost in expectations from Wall Street
Tesla deliveries got a big boost in expectations from Wall Street firm Goldman Sachs, who believes the company will report some stronger-than-expected numbers when the second quarter comes to an end in the coming weeks.
Goldman Sachs has raised its vehicle delivery forecast for Tesla (NASDAQ: TSLA) in the second quarter of 2026, signaling growing confidence in the electric vehicle leader’s near-term momentum despite mixed market signals. Analyst Mark Delaney lifted the bank’s Q2 estimate to 420,000 units from a previous 405,000, surpassing the Visible Alpha consensus estimate of 400,000.
The upward revision stems from stronger-than-expected sales data across key regions. Europe stands out with projected year-over-year growth of 85-90 percent, driven by robust demand for Tesla’s Model Y and refreshed offerings. China posted high single-digit gains, while markets like South Korea and Australia also contributed positive momentum. These gains help offset mid-teens declines in U.S. deliveries through May, where broader EV market headwinds and competition persist.
Goldman extended its optimism to the full year, increasing its 2026 delivery projection to 1.73 million vehicles from 1.72 million. Longer-term forecasts remain unchanged, with 1.88 million units expected in 2027 and 1.96 million in 2028. The bank also nudged its 2026 earnings-per-share estimate higher to $1.35 from $1.30, reflecting anticipated margin benefits from higher volumes and operational efficiencies.
Despite these positive adjustments, Goldman maintained its Neutral rating and $375 price target on Tesla shares. At current trading levels near $411, the stock sits about 8-9 percent above the target, highlighting ongoing valuation concerns even as delivery momentum builds. Tesla’s Q1 2026 deliveries totaled 358,023 units, setting a baseline for recovery expectations in the current period.
This update arrives as Tesla prepares to report official Q2 figures shortly after June 30. Investors and analysts will closely watch not only headline delivery numbers but also regional breakdowns, average selling prices, and progress on energy storage deployments and autonomous technology initiatives.
The move by Goldman Sachs underscores a broader narrative for Tesla: while legacy auto markets face softening demand and tariff uncertainties, Tesla’s global footprint and product pipeline provide resilience. Europe’s surge reflects pent-up demand and policy support for EVs, while China’s steady growth highlights Tesla’s competitive positioning against local rivals.
Tesla still has its work cut out for it, including U.S. price sensitivity and intensifying competition. Yet Goldman’s revision adds to a series of analyst notes suggesting Q2 could mark a turning point. As Tesla pushes toward higher production rates at facilities in Fremont, Shanghai, and Berlin, sustained execution will be key to validating these higher forecasts.
We have said numerous times that deliveries are becoming a less important metric in the grand scheme of things, as AI truly takes precedence in the company’s thesis.
For Tesla bulls, the Goldman note reinforces faith in underlying demand trends. For skeptics, the unchanged rating serves as a reminder that delivery beats alone may not immediately resolve valuation debates in a high-interest-rate environment. Tesla’s stock reaction will likely hinge on the official numbers and management commentary in the coming weeks.
News
SpaceX makes first acquisition post-IPO with coding leader Cursor
SpaceX has exercised its option to acquire Cursor, the innovative AI coding company, in an all-stock transaction valued at $60 billion. The deal, announced on June 16, marks a significant step in SpaceX’s expansion into advanced artificial intelligence, building on months of close collaboration between the companies.
Cursor, officially operated by Anysphere, Inc., is an AI-native code editor and coding agent designed to transform software development. Founded in 2022 by a group of MIT graduates in San Francisco, Cursor builds on the familiar foundation of Visual Studio Code but integrates powerful AI capabilities directly into the core experience.
Unlike traditional code editors or simple extensions, Cursor functions as a full “coding agent” that turns natural-language instructions into actionable code.
SpaceX has exercised the option to acquire @cursor_ai in an all-stock transaction with the goal of building the world’s most useful AI models.
For the past few months, SpaceXAI has been jointly training a model with Cursor, which will be released in Cursor and Grok Build soon.… https://t.co/X5mepgXgjJ
— SpaceX (@SpaceX) June 16, 2026
Developers interact with Cursor through features like its Composer agent, which can search entire codebases, edit multiple files, run terminal commands, debug issues, and complete complex multi-step programming tasks autonomously.
Users describe high-level goals, such as “build a scalable API endpoint with authentication,” and the AI plans, implements, tests, and refines the solution while the human oversees decisions. Additional tools include advanced autocomplete (Tab), context-aware chat, and infrastructure for handling billions of daily requests.
The platform has gained considerable traction, surpassing $3 billion in annual recurring revenue by early 2026 and earning adoption by over half of the Fortune 500 companies. Its agentic approach accelerates development dramatically, allowing engineers to focus on architecture and creativity rather than repetitive coding.
The acquisition integrates Cursor’s leading product, expert team of roughly 300 engineers, and distribution network among top software developers with SpaceX’s unparalleled computational resources. SpaceX’s Colossus supercomputer, equivalent to a million H100 GPUs, has already powered joint training of next-generation models. These models are expected to launch soon within Cursor and SpaceX’s Grok Build environment.
This combination positions SpaceX to develop the world’s most capable AI systems for coding and knowledge work. Access to Cursor’s real-world usage data from millions of professional developers provides unparalleled feedback loops for model improvement. Training on Colossus enables rapid iteration on massive datasets, potentially creating AI that outperforms current leaders in reliability, context handling, and complex reasoning.
For SpaceX, the benefits extend far beyond software tools. Rocket engineering, satellite constellation management, autonomous flight systems, and Starship development involve millions of lines of highly specialized, safety-critical code.
Cursor’s AI agents, supercharged by proprietary models trained on SpaceX’s domain expertise, could slash development timelines, reduce errors, and enable faster innovation cycles. This vertical integration of AI tooling strengthens SpaceX’s competitive edge in both aerospace and the broader AI race, complementing its xAI initiatives.
The deal reflects the exploding value of AI-native developer platforms. By owning Cursor outright, SpaceX secures a strategic talent pool and product pipeline that will accelerate internal projects while potentially offering enhanced tools to the wider engineering community. As AI continues reshaping software creation, this acquisition underscores SpaceX’s commitment to leveraging cutting-edge technology for ambitious goals, from Mars colonization to global connectivity.
News
Tesla Cybercab specs revealed: range, curb weight, range ratings, and more
Tesla’s Cybercab has taken a significant step toward production with new technical details emerging from 2026 EPA certification documents.
The filings, which include a Certificate of Conformity issued in late May, provide the most comprehensive public look yet at the purpose-built autonomous vehicle designed for high-volume, low-cost ride-hailing operations.
At its core, the Cybercab is a front-wheel-drive electric vehicle powered by a single 163 kW (219 horsepower) AC permanent magnet motor. Despite its modest output, prioritizing efficiency and cost over neck-snapping acceleration, the vehicle boasts a strong power-to-weight ratio thanks to its lightweight curb weight of 3,113 pounds and a GVWR of 3,730 pounds.
It operates on a 326-volt electrical architecture with a compact ~48 kWh lithium-ion battery pack. The standout revelation is the vehicle’s exceptional efficiency, which Tesla has routinely flexed in the past.
EPA lab tests list an equivalent all-electric range of 418 miles combined and 375 miles on the highway. Tesla has previously targeted around 300 miles of real-world range, and analysts expect the final EPA-rated figure to land near 280-300 miles after adjustment factors.
At a certified 165 Wh/mi in earlier testing, the Cybercab is reportedly the most efficient EV ever produced, significantly outperforming vehicles like the Lucid Air Pure.
New information about @Tesla‘s Cybercab has been revealed in public EPA documents.
• Front-wheel drive
• Battery capacity: ~48 kWh
• 219 horsepower
• Curb weight: 3,113 lbs
• GVWR: 3,730 lbs
• Motor power: 163kW
• Voltage: 326vEquivalent All Electric Range is listed at… pic.twitter.com/D4gkJJTj25
— Sawyer Merritt (@SawyerMerritt) June 15, 2026
This efficiency stems from deliberate design choices tailored for robotaxi duty. The two-seater features a highly aerodynamic shape, minimal weight, which is aided by structural battery integration of what are likely 4680 cells, and no steering wheel or pedals in its fully autonomous configuration.
For ride-hailing fleets, where average trips are short, and can be just five or ten miles, the smaller battery enables faster charging cycles, lower material costs, and reduced vehicle price, a key to Tesla’s goal of a ~$30,000 production cost.
Implications for Autonomous Mobility
These specs underscore Tesla’s strategy: maximize utilization and minimize operating expenses. A ~48 kWh pack could support dozens of short rides per charge, with energy costs potentially dropping below 20 cents per mile at scale. Front-wheel drive simplifies manufacturing and maintenance compared to dual-motor AWD setups in passenger Teslas.
The 219 hp motor provides ample performance for urban and highway speeds without excess, addressing questions about why such power is needed in a “slow” autonomous vehicle. Quick merges and hill climbing still matter for safety and passenger comfort.
Production has already begun at Giga Texas, with EPA certification clearing the path for U.S. deployment. While unsupervised Full Self-Driving remains the critical hurdle, these details paint a compelling picture of a vehicle engineered from the ground up for the robotaxi future: affordable to build, cheap to run, and capable of delivering strong range on a fraction of the battery capacity found in today’s EVs.
As Tesla ramps toward volume output, the Cybercab could reshape urban transportation economics.