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SpaceX wins NASA funds to build and test Starship’s orbital refueling technology
On September 27th, NASA announced a new round of Tipping Point funding worth a total of $43.2M that will be dispersed among 14 separate companies, all focused on advancing “important technologies necessary for sustained exploration of the Moon and Mars.”
Aside from Blue Origin and a dozen others, SpaceX received $3M to work with NASA’s Marshall Space Flight Center (MSFC) to build and test “cryogenic fluid couplers”, a type of nozzle Starship will need to refuel in orbit.
Noted multiple times over the years (and in recent days) by both SpaceX and CEO Elon Musk, an extremely robust and reliable method of orbital refueling is essential to the success of Starship’s current designed – perhaps more so than any other single aspect of the next-generation launch vehicle. Although Starship-Super Heavy will likely offer respectable performance in single-launch mode, the implicit need to recover and reuse both booster and spacecraft takes a big chunk out of the rocket’s potential capabilities.
Much like Falcon 9 and Heavy must sacrifice performance for booster landings, Super Heavy will also need to retain some amount of propellant for its boostback and landing burns. However, while just 1 kg of orbital payload is lost for every ~5-10 kg of extra hardware and propellant on the booster, things are far more consequential when discussing orbital stage reusability. Every single kilogram of hardware and propellant meant for Starship recovery and reuse will result in a 1:1 reduction in payload capacity. This becomes highly consequential when recovering the spacecraft involves the addition of something like 100-200 metric tons worth of wings, fins, heat shield tiles, batteries, propellant, and more.
As such, SpaceX is faced with a conundrum: to make spaceflight truly cheap, full reusability is a necessity, but full reusability almost fundamentally constrains the resultant rocket’s performance and utility. SpaceX’s solution: prolific orbital refueling on the order of anywhere from 1-10+ dedicated tanker launches for every Starship launch. By refueling in Earth orbit, be it low Earth orbit or something much more eccentric, Starship can be extremely reusable while still offering performance that even a similarly-sized, fully-expendable rocket couldn’t begin to compete with.
Although the theory behind SpaceX’s strategy is undeniably sound, the fact remains that orbital refueling has never been tested anywhere close to the scale, speed, or reliability Starship will need for numerous in-orbit refuelings to be a practical solution. Assuming SpaceX uses every ounce of Starship and Super Heavy’s performance for each tanker launch to low Earth orbit (LEO), Starship will have to be able to repeatedly and rapidly transfer at least 150 metric tons (330,000 lb) of liquid oxygen and methane in microgravity conditions.
Without Earth’s gravity and the force of multiple Raptor engines to help things along, it could be quite a challenge to transfer hundreds of tons of propellant in a reasonable timeframe while in orbit. In fact, SpaceX already has Space Act Agreements in place with NASA centers to mature orbital propellant transfer technology. The September 27th award simply continues that relationship, although this particular case involves the first direct funding from NASA – meant to help SpaceX over the “tipping point”.
This time around, SpaceX will work directly with NASA MSFC to build and test actual prototypes of the nozzles (“cryogenic fluid couplers”) Starship will use to mate and refuel in orbit.
“SpaceX will collaborate with NASA’s Marshall Space Flight Center in Huntsville, Alabama, to develop and test coupler prototypes – or nozzles – for refueling spacecraft such as the company’s Starship vehicle. A cryogenic fluid coupler for large-scale in-space propellant transfer is an important technology to aid sustained exploration efforts on the Moon and Mars.”
NASA, 09/27/19
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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
