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SpaceX’s BFR program pursuing advanced Starship heat shield with NASA help
According to a Space Act Agreement signed by SpaceX and NASA’s Ames Research Center in June 2018, the private company has begun working with NASA to acquire some basic experience and lessons-learned with a thermal protection (heat shield) material that is largely new to SpaceX.
Known as TUFROC (short for Toughened Uni-piece Fibrous Reinforced Oxidation-Resistant Composite), the NASA Ames-developed material is capable of withstanding temperatures as high as 1700 C (~3100 F) and is apparently an item of interest to SpaceX’s next-gen BFR (Starship/Super Heavy) rocket program, particularly Starship’s heat shield.
As far as the public is aware, SpaceX has never attempted to manufacture or utilize a heat shield technology like TUFROC. Falling under a domain of thermal protection materials known as ceramic matrix composites (CMCs), TUFROC is essentially an umbrella term that covers any thermal protection system that combines a carbon cap, silica base, and a cured glass coating to prevent oxidation. In recent years, Boeing’s secretive X-37B spaceplane has successfully demonstrated TUFROC reuse after orbital velocity reentries, confirming that the material is capable of surviving those conditions while experiencing minimal to no ablation.
Contour remains approx same, but fundamental materials change to airframe, tanks & heatshield
— Elon Musk (@elonmusk) November 25, 2018
Much like SpaceX borrowed the NASA-developed PICA (phenolic-impregnated carbon ablator) heat shield technology and dramatically improved it for cost-effective use on Cargo (and soon Crew) Dragon, the basic concept behind TUFROC’s heat shielding capabilities likely lends itself just as well to potential improvements in cost reduction, ease of manufacturing, mechanical strength, thermal protection characteristics, and more.
Unlike the fatally fragile carbon-carbon tiles used on the Space Shuttle, TUFROC’s namesake “Fibrous Reinforced” aspects also make it dramatically more resistant to impact related forces like those that led to the Columbia disaster, while still preserving the composite’s impressive heat resistance. NASA already categorizes TUFROC as a “low-cost” TPS, further indicating that SpaceX could quite easily cut the cost of production by a significant degree.
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- Boeing’s X-37B spaceplane. (Boeing)
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- A visualization of the location of X-37B’s limited TUFROC heat shielding. (NASA)
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- A closeup of BFS’ nose section, featuring impressively varied tile-sizes, joining methods, and extremely precise curves on the interface between canard wings and the hull. (SpaceX)
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- A view of BFS just after separating from its booster stage. (SpaceX)
What is not clear about this budding relationship is how exactly SpaceX foresees TUFROC or a custom heat shield derivative fitting into its BFR program. Currently, the TPS has only been demonstrated on X-37B as a literal edge-case, standing in for a more traditional silica tile on the leading edges of the small spacecraft’s wings, where reentry heating is often the most extreme. It’s possible that SpaceX is interested in TUFROC for the same reasons – using it to cover BFS/Starship’s forward and rear fins and nothing more.
However, it could be the case that SpaceX hopes an improved TUFROC-X might be viable as a monolithic one-size-fits-all heat shield material throughout BFR’s Super Heavy booster and Starship upper stage. Being forced to deal with a variety of different TPS materials inevitably raises the complexity and cost of a given spacecraft, so being able to significantly reduce the number of materials needed could be a boon for Starship.
NASA and SpaceX’s Space Act Agreement can be found here [PDF].
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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.”
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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
