Elon Musk’s cautionary statements about uncontrolled experimentation with artificial intelligence (AI) have caused some to ridicule him as a fear-monger, and have given many in the mainstream press the idea that he is opposed to using AI, which is very far from the truth. In fact, AI is a major component of Tesla’s Autopilot system, and the company applies it in several other areas as well.
It was only recently that Tesla publicly revealed that it is working on its own AI hardware. At the NIPS machine learning conference in December, Elon Musk announced that Tesla is “developing specialized AI hardware that we think will be the best in the world.” The company has offered few details, but it’s widely assumed that the main application will be processing the algorithms for Tesla’s Autopilot software.
As Bernard Marr reports in a recent article in Forbes, there’s little doubt that Tesla is way ahead of its potential rivals in the data-gathering department. Every Model S and X built with the Autopilot hardware suite, which was introduced in September 2014, has the potential to become self-driving, and all Tesla vehicles, Autopilot-enabled or not, continually gather data and send it to the cloud. The company has many more sensors on the roads than any of its Detroit or Silicon Valley rivals, and the number will mushroom when Model 3 production hits its stride.
Tesla is crowd-sourcing data not only from its vehicles, but could one day obtain data on its drivers through internal cameras that detect hand placement on instruments or a person’s state of alertness. The company uses the information not only to improve Autopilot by generating data-dense maps, but also to diagnose driving behavior. Many believe that this sort of data will prove to be a valuable commodity that could be sold to third parties (much as data on web-browsing habits is today). McKinsey and Company has estimated that the market for vehicle-gathered data could be worth $750 billion a year by 2030.
Forbes explains that the AI built into Tesla’s system operates at several levels. Machine learning in the cloud educates the entire fleet, while within each individual vehicle, “edge computing” can make decisions about actions a car needs to take immediately. There’s also a third level of decision-making, in which cars can form networks with other Tesla vehicles nearby in order to share local information. In the future, when there are lots of autonomous cars on the road, these networks could also interface with cars from other makers, and systems such as traffic cameras, road-based sensors, and mobile phones.
At this point, no one knows what new forms of AI technology the mad scientists in Palo Alto are cooking up, but Forbes found some clues on the Facebook page of Tesla’s hardware partner Nvidia: “In contrast to the usual approach to operating self-driving cars, we did not program any explicit object detection, mapping, path planning or control components into this car. Instead, the car learns on its own to create all necessary internal representations necessary to steer, simply by observing human drivers.”
This unsupervised learning model contrasts with the more familiar approach of supervised learning, in which algorithms are trained beforehand about right or wrong decisions. Each approach has its pros and cons, and it’s likely that Tesla’s strategy includes both.
Forbes reports that Tesla’s use of AI is not limited to Autopilot – the company employs machine learning in the design and manufacturing processes, to process customer data, and even to scan the text in online forums for insights into commonly-reported problems. It’s ironic that some in the press choose to portray Elon Musk as an AI Luddite, when in fact Tesla may be one of the most sophisticated users of the technology.
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Note: Article originally published on evannex.com, by Charles Morris
Source: Forbes
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.
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.
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.
Tesla finally clarifies fatal Texas crash, confirms driver manually overrode acceleration
SpaceX makes $20 billion move to optimize its balance sheet
