Google’s driverless ride-hailing company Waymo has revealed the latest in a string of AI research-related announcements, this time sharing results from a first-of-its-kind study on collisions with vulnerable road users.
Waymo last week announced EMMA, its end-to-end, multimodal research model for autonomous driving, though it isn’t being used commercially at this point. The company also went on to detail its current approach to AI in a separate press release, noting its continued research into real-world models and AI training, a concept that may sound familiar to those who have followed Tesla’s Full Self-Driving (FSD) development.
On Monday, however, Waymo shared results from a study on Vulnerable Road Users (VRUs), in which the company reconstructed hundreds of collisions involving VRUs like pedestrians, cyclists, and motorcyclists. Waymo says that the research, as conducted in a partnership with Nexar, is the largest dataset of its kind in the U.S., providing key insights into real-world crash scenarios.
The companies analyzed dash camera footage of 335 collisions involving VRUs across six U.S. cities, leveraging over 500 million miles of driving data from Nexar for the research. The partnership also worked with Waymo research partner VUFO, which contributed to the below models on collision injury risk.

Credit: Waymo

Credit: Waymo
According to the National Highway Traffic Safety Administration (NHTSA), there were an estimated 7,522 pedestrians and 1,105 cyclists who lost their lives in traffic crashes in 2022, though Waymo says VRU collision data remains scarce. The company explains this by noting that several VRU-related incidents don’t get reported to authorities or insurance firms, while the U.S. and other major accident databases lack data on these particular incidents.
“We’re excited to partner with Waymo on this cutting-edge research,” said Henrik Liers, Managing Director of Waymo research partner VUFO. “Our common work addresses critical limitations in existing models and provides a more precise, interdisciplinary approach to assessing injury risk for vulnerable road users. This is a significant contribution towards improving road safety.”
Tesla’s Full Self-Driving and end-to-end learning models
The recent developments from Waymo come as General Motors’s (GM’s) Cruise, Amazon’s Zoox, and Tesla’s Supervised Full Self-Driving (FSD) aim to offer similar robotaxi services. While Tesla doesn’t currently operate a paid ride-hailing service as Waymo does, it unveiled the two-seat, steering wheel-free Cybercab robotaxi last month.
Interestingly, Tesla’s FSD system has been touted by some as a more scalable solution, in no small part due to its end-to-end system that trains on millions of clips of real-time driving footage. Another factor is that FSD is available to any Tesla owner who purchases the software, meaning that its neural network stands to have a much wider potential research base than systems like Waymo—at least until services scale up substantially.
Tesla’s Cybercab isn’t expected to go into production until 2026, though FSD Supervised will certainly collect a substantial amount of data in the meantime. As of Tesla’s Q3 earnings call, the company has over 2 billion cumulative miles of data from FSD Supervised users, after it surpassed a milestone of 1.3 billion miles in April.
Tesla FSD V13 to implement features required for unsupervised driving: exec
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Elon Musk
Tesla finally clarifies fatal Texas crash, confirms driver manually overrode acceleration
Tesla has finally clarified the situation regarding the viral crash in Texas where a Model 3 slammed into a home.
CEO Elon Musk replied to reports on Monday that stated the crash was due to the company’s Full Self-Driving or Autopilot suite, which seemed unlikely to those who are familiar with it. Video showed the car slamming into a house at an excessive rate of speed, making it highly unlikely the crash was due to the suite’s operation, as it does not travel at those speeds in residential areas.
Musk said:
“This makes no sense. FSD drives slowly through neighborhood streets, and this was a high-speed crash!”
Tesla’s Head of AI, Ashok Elluswamy, added context, revealing that the company’s data shows the driver “manually overrode self-driving by pressing the accelerator all the way to 100%.”
He revealed the speed reached by the car was 73 MPH, and the accelerator was still pressed “even after the crash.”
Yup. In this case, the driver manually overrode self-driving by pressing the accelerator all the way to 100% of the accel pedal in this residential area. They reached a speed of 73 mph during the crash, and had the accelerator pressed even after the crash.
— Ashok Elluswamy (@aelluswamy) June 22, 2026
Authorities are reportedly investigating “whether Tesla’s Autopilot system played a role after a Model 3 left the roadway…slammed through a brick house at high speed and fatally struck Matha Avila as she sat inside,” the New York Post reported.
The National Highway Traffic Safety Administration (NHTSA) is now investigating the crash. Tesla will work with the agency to provide them with whatever information they need in order to clarify the cause of the crash.
Similarly, Tesla had claims of a fatal accident in Harris County, Texas, a few years ago. Early reports indicated that Full Self-Driving was the cause of the crash. After the National Transportation Safety Board (NTSB) worked with Tesla, the agency proved there was “no use of the Autopilot system at any time during this ownership period of the vehicle, including the time frame up to the last transmitted timestamp on April 17, 2021.”
Tesla alleged “driverless” crash in Texas: What is known so far
“Application of the accelerator pedal was found to be as high as 98.8 percent,” the NTSB said in their findings. The highest recorded speed in the five seconds leading up to the impact was 67 miles per hour. The area where the crash occurred is residential, and Texas State laws have default speed limits of 30 MPH in residential streets.
This appears to be a similar situation. However, an investigation will prove what happened for sure.
Investor's Corner
SpaceX makes $20 billion move to optimize its balance sheet
SpaceX announced today that it commenced its first-ever public bond offering, marking a significant step in the newly public company’s capital markets strategy.
The company announced an offering of senior unsecured notes expected to raise at least $20 billion.
The move comes just a short time after SpaceX completed one of the largest initial public offerings in history. In mid-June, the company priced shares at $135 and raised more than $85 billion, propelling founder Elon Musk’s net worth past the trillion-dollar mark and giving the firm substantial liquidity.
🚨 SpaceX has announced its inaugural offering of senior unsecured notes.
The net proceeds will be used to repay outstanding loans under its bridge loan facility in full.
This inaugural debt offering represents a financing milestone for SpaceX, which previously depended… pic.twitter.com/pcOZuVbTRv
— TESLARATI (@Teslarati) June 22, 2026
According to the company’s SEC filing, the net proceeds from the notes will be used primarily to repay in full the outstanding borrowings under its existing bridge loan facility, cover related fees and expenses, and fund general corporate purposes. The offering is being conducted under Rule 144A, as well as Regulation S, targeting qualified institutional buyers and non-U.S. investors. Notes will be unsecured obligations ranking equally with other unsubordinated debt.
The $20 billion bridge loan was used to refinance approximately $17.5 billion in higher-cost “junk” debt tied to X and xAI. SpaceX had merged with xAI in February 2026 in an all-stock deal. The bridge facility, which matures in September 2027, had represented the bulk of SpaceX’s long-term debt.
SpaceX officially acquires xAI, merging rockets with AI expertise
In connection with the bond launch, SpaceX disclosed it held approximately $100.8 billion in cash and cash equivalents as of June 19. Investor calls began on the announcement date, with pricing and launch expected shortly thereafter. Rating agencies have assigned investment-grade ratings to the proposed bonds, reflecting confidence in SpaceX’s dominant position in commercial launches and the growth trajectory of its Starlink internet offering.
The debt raise also allows SpaceX to optimize its balance sheet by replacing short-term, higher-cost bridge financing with longer-date, lower-cost fixed-income securities. This provides greater financial flexibility to support capital-intensive initiatives, including the development of Starship, the expansion of the Starlink constellation, and the integration of AI capabilities following the xAI combination.
SpaceX shares (NASDAQ: SPCX) fell sharply on the news, dropping over 16 percent overall on the market on Monday. The stock had surged initially after debuting but pulled back amid profit-taking and broader market dynamics.
Overall, the bond offering underscores SpaceX’s transition to a mature public company with access to diverse funding sources. It positions the firm to pursue its long-term vision of multiplanetary expansion and AI infrastructure, while maintaining a disciplined approach to its capital structure in a high-growth but capital-heavy industry.
Elon Musk
SpaceX confirms third massive compute deal at Colossus data center
SpaceX confirmed today that it has officially signed its third massive compute deal, providing compute at its Colossus data center in Southaven, Mississippi.
Reflection AI will gain immediate access to NVIDIA GB300 chips at SpaceX’s Colossus 2 data center. In return, Reflection will pay SpaceX $150 million per month starting on July 1, with total payments reaching approximately $6.3 billion if the contract runs through its duration, which is until 2029. Either party can terminate the agreement with 90 days’ notice after the initial three-month period.
CNBC first reported the deal.
🚨 SpaceXAI has agreed to a new compute deal with Reflection AI.
Reflection gets access to NIVIDIA GB300s, and will pay $150M per month to SpaceXAI for the compute. pic.twitter.com/bNPare8U5u
— TESLARATI (@Teslarati) June 22, 2026
This latest partnership highlights SpaceX’s strategy of commercializing its massive Colossus supercomputing infrastructure, originally developed to power Elon Musk’s Grok AI models. The company has rapidly expanded its customer base in the AI sector following its February 2026 merger with xAI, a transaction that valued the combined entity at $1.25 trillion.
SpaceX has previously signed significant compute deals with other major players.
It granted Anthropic exclusive access to the full capacity of its Colossus 1 data center, which exceeds 300 megawatts and includes over 220,000 NVIDIA GPUs. Details from SpaceX’s IPO filings indicate Anthropic will pay $1.25 billion per month through May 2029, potentially generating around $45 billion over the term of the deal.
Additionally, Google agreed to pay SpaceX $920 million per month for compute capacity from October 2026 through June 2029. This 32-month period will provide Google access to roughly 110,000 NVIDIA GPUs, along with supporting processors and memory. Capacity ramps up through September at a reduced fee, with termination options after the first year.
SpaceXA also established arrangements for computing power with Cursor, an AI coding startup. SpaceX acquired them in a $60 billion all-stock deal.
These arrangements position SpaceX’s collective position as an AI infrastructure powerhouse with high-margin revenue potential. The Google deal alone could generate nearly $29.5 billion over its term, while the Reflection contract adds another $6.3 billion.
Combined with the Anthropic arrangement, SpaceX stands to realize tens of billions in revenue from compute leasing in the coming years, which diversifies beyond SpaceX’s traditional rocket launches and Starlink operation.
The deals underscore growing demand for advanced AI training and inference capacity amid chip shortages and surging model development needs. Reflection, valued at $25 billion and focused on “American open intelligence” with government and national security ties, cited recent restrictions on closed models as validation for open-source approaches.
For SpaceX, the partnerships transform capital-intensive data centers into flexible revenue sources while supporting its broader AI ambitions after the company has gone public.