News
SpaceX begins work on Starship orbital propellant transfer test for NASA
More than six months after SpaceX won a NASA ‘Tipping Point’ award to demonstrate a large-scale cryogenic propellant transfer in orbit with Starship, the agency has begun disbursing funds, officially kicking off work on the mission.
Back in October 2020, NASA awarded 15 different companies more than $370 million for research and development projects related to managing cryogenic propellant in space, lunar surface operations, and autonomous landing technology. More than two-thirds of that funding went to four real in-space demonstrations of cryogenic propellant management and storage from Lockheed Martin, United Launch Alliance (ULA), SpaceX, and little-known startup Eta Space.
All four missions are fascinating in their own rights. Leaning heavily on Rocket Lab’s small Electron rocket and Photon spacecraft/kickstage, Eta Space will launch a tiny “cryogenic oxygen fluid management system” and demonstrate its performance for some nine months in orbit. Lockheed Martin will perform a similar but slightly larger test with cryogenic liquid hydrogen – far colder and much harder to handle – in low Earth orbit (LEO). Despite major investments in launch startup and competitor ABL Space, Lockheed Martin selected rocket-3D-printing startup Relativity to launch the mission – possibly because the company says it will be able to print a custom fairing to accommodate the payload’s unusual dimensions.
While vague, ULA appears to have plans to test the claimed long-duration coast capabilities of the Vulcan rocket’s Centaur V upper stage, though it’s unclear if that testing will be performed on the ground or in space. Finally, NASA awarded SpaceX $53 million for a “large-scale flight demonstration to transfer 10 metric tons of…liquid oxygen…between tanks on a Starship.”
In the context of NASA’s shocking April 2021 decision to competitively award SpaceX – and SpaceX alone – a $2.9 billion contract to return humanity to the Moon with Starship, the agency’s $53M investment in a demonstration of a capability Starship cannot reach the Moon without seems like a no-brainer. On its own, SpaceX’s next-generation fully-reusable Starship launch vehicle is expected to be able to deliver payloads of 100 to 150 metric tons (220,000-330,000 lb) to LEO. However, to make Starship fully reusable, the ship itself – also serving as the upper stage – is extremely heavy, drastically undercutting its performance to higher orbits.
To high Earth orbits, a lone Starship offers performance akin to SpaceX’s own Falcon Heavy. For Starship to be a truly revolutionary rocket, SpaceX will have to master rapid reusability and orbital refueling. Even with moderate refueling, Starship’s potential performance immediately leapfrogs all other existing and planned rockets. With full refueling in LEO, Starship quickly becomes capable of delivering dozens to 100+ tons of cargo and passengers to the surface of Mars. With refueling in high Earth orbit, Starship could land hundreds of tons on Earth’s Moon and likely launch cargo and spacecraft anywhere in the solar system in short order.
Ultimately, US Federal Procurement Database entries show that NASA ultimately procured $50.4 million for SpaceX’s propellant transfer demonstration, began disbursing funds ($15.1M) on May 4th, 2021, and expects SpaceX to complete work by the end of 2022. It’s unclear if NASA expects SpaceX to recover the Starship involved in the test.
If the rest of NASA’s funding is contingent upon successfully returning Starship for hands-on inspections and maximum data recovery, 2022 is a more reasonable target. If NASA deems data returned from orbit satisfactory, on the heels of SpaceX filing for an orbital Starship launch debut as early as next month, that demonstration mission could easily happen this year given that SpaceX only needs to launch one Starship to complete it.
Elon Musk
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
Tesla CEO Elon Musk has provided an updated estimate for the training data needed to achieve truly safe unsupervised Full Self-Driving (FSD).
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
10 billion miles of training data
Musk comment came as a reply to Apple and Rivian alum Paul Beisel, who posted an analysis on X about the gap between tech demonstrations and real-world products. In his post, Beisel highlighted Tesla’s data-driven lead in autonomy, and he also argued that it would not be easy for rivals to become a legitimate competitor to FSD quickly.
“The notion that someone can ‘catch up’ to this problem primarily through simulation and limited on-road exposure strikes me as deeply naive. This is not a demo problem. It is a scale, data, and iteration problem— and Tesla is already far, far down that road while others are just getting started,” Beisel wrote.
Musk responded to Beisel’s post, stating that “Roughly 10 billion miles of training data is needed to achieve safe unsupervised self-driving. Reality has a super long tail of complexity.” This is quite interesting considering that in his Master Plan Part Deux, Elon Musk estimated that worldwide regulatory approval for autonomous driving would require around 6 billion miles.
FSD’s total training miles
As 2025 came to a close, Tesla community members observed that FSD was already nearing 7 billion miles driven, with over 2.5 billion miles being from inner city roads. The 7-billion-mile mark was passed just a few days later. This suggests that Tesla is likely the company today with the most training data for its autonomous driving program.
The difficulties of achieving autonomy were referenced by Elon Musk recently, when he commented on Nvidia’s Alpamayo program. As per Musk, “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.” These sentiments were echoed by Tesla VP for AI software Ashok Elluswamy, who also noted on X that “the long tail is sooo long, that most people can’t grasp it.”
News
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla emerged as one of the most recognized automakers at MotorTrend’s 2026 Software-Defined Vehicle (SDV) Innovator Awards.
As could be seen in a press release from the publication, two key Tesla employees were honored for their work on AI, autonomy, and vehicle software. MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla leaders and engineers recognized
The fourth annual SDV Innovator Awards celebrate pioneers and experts who are pushing the automotive industry deeper into software-driven development. Among the most notable honorees for this year was Ashok Elluswamy, Tesla’s Vice President of AI Software, who received a Pioneer Award for his role in advancing artificial intelligence and autonomy across the company’s vehicle lineup.
Tesla also secured recognition in the Expert category, with Lawson Fulton, a staff Autopilot machine learning engineer, honored for his contributions to Tesla’s driver-assistance and autonomous systems.
Tesla’s software-first strategy
While automakers like General Motors, Ford, and Rivian also received recognition, Tesla’s multiple awards stood out given the company’s outsized role in popularizing software-defined vehicles over the past decade. From frequent OTA updates to its data-driven approach to autonomy, Tesla has consistently treated vehicles as evolving software platforms rather than static products.
This has made Tesla’s vehicles very unique in their respective sectors, as they are arguably the only cars that objectively get better over time. This is especially true for vehicles that are loaded with the company’s Full Self-Driving system, which are getting progressively more intelligent and autonomous over time. The majority of Tesla’s updates to its vehicles are free as well, which is very much appreciated by customers worldwide.
Elon Musk
Judge clears path for Elon Musk’s OpenAI lawsuit to go before a jury
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder.
A U.S. judge has ruled that Elon Musk’s lawsuit accusing OpenAI of abandoning its founding nonprofit mission can proceed to a jury trial.
The decision maintains Musk’s claims that OpenAI’s shift toward a for-profit structure violated early assurances made to him as a co-founder. These claims are directly opposed by OpenAI.
Judge says disputed facts warrant a trial
At a hearing in Oakland, U.S. District Judge Yvonne Gonzalez Rogers stated that there was “plenty of evidence” suggesting that OpenAI leaders had promised that the organization’s original nonprofit structure would be maintained. She ruled that those disputed facts should be evaluated by a jury at a trial in March rather than decided by the court at this stage, as noted in a Reuters report.
Musk helped co-found OpenAI in 2015 but left the organization in 2018. In his lawsuit, he argued that he contributed roughly $38 million, or about 60% of OpenAI’s early funding, based on assurances that the company would remain a nonprofit dedicated to the public benefit. He is seeking unspecified monetary damages tied to what he describes as “ill-gotten gains.”
OpenAI, however, has repeatedly rejected Musk’s allegations. The company has stated that Musk’s claims were baseless and part of a pattern of harassment.
Rivalries and Microsoft ties
The case unfolds against the backdrop of intensifying competition in generative artificial intelligence. Musk now runs xAI, whose Grok chatbot competes directly with OpenAI’s flagship ChatGPT. OpenAI has argued that Musk is a frustrated commercial rival who is simply attempting to slow down a market leader.
The lawsuit also names Microsoft as a defendant, citing its multibillion-dollar partnerships with OpenAI. Microsoft has urged the court to dismiss the claims against it, arguing there is no evidence it aided or abetted any alleged misconduct. Lawyers for OpenAI have also pushed for the case to be thrown out, claiming that Musk failed to show sufficient factual basis for claims such as fraud and breach of contract.
Judge Gonzalez Rogers, however, declined to end the case at this stage, noting that a jury would also need to consider whether Musk filed the lawsuit within the applicable statute of limitations. Still, the dispute between Elon Musk and OpenAI is now headed for a high-profile jury trial in the coming months.
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
Tesla earns top honors at MotorTrend’s SDV Innovator Awards
