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SpaceX's "Christmas tree" is a Raptor engine for the holidays

Raptor performs a static fire test at SpaceX's McGregor, Texas development facilities. (SpaceX)

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SpaceX CEO Elon Musk showed off a holiday-themed Raptor engine “Christmas tree” with its very own star on top. Musk noted via a tweet that the company’s Starship propulsion team is “making great progress” building, testing, and refining the Raptor engines that will one day propel the next-generation rocket to Earth orbit and beyond.

On December 13th, Musk revealed that SpaceX is preparing to ship the 17th completed Raptor engine to the company’s McGregor, Texas rocket test and development facilities, the site of several dedicated test stands for the Starship engine. Likely one of the most complex rocket engines ever designed, built, or tested, Raptor relies on an exotic combustion cycle, referring to the specifics of how engines turn their propellant into meaningful thrust.

Raptor uses what is known as full-flow staged combustion (FFSC) and is the first FFSC engine to graduate beyond ground testing and actually fly, thus far having completed two flight tests in July and August 2019 as part of SpaceX’s Starhopper test campaign. In simple terms, the FFSC cycle aims to extract as much energy from a rocket’s propellant as efficiently as possible, resulting in what is theoretically the most efficient possible chemical propulsion from a given fuel and oxidizer combination.

Due to the sheer complexity required to achieve full-flow staged combustion, the engine type is incredibly rare and only two other (once) functional examples exist – one developed by Soviet engineers in the 20th century and the other built, tested, and inexplicably scrapped by NASA in the 2000s. In fact, the Soviet RD-270 engine’s thrust-to-weight ratio is likely second only to SpaceX’s own Merlin 1D engine, an absolutely spectacular achievement for a propulsion bureau operating in the late 1960s.

RD-270 had major development challenges and would likely have taken years of additional hardware-rich (i.e. destructive trial and error) testing to produce an engine actually capable of reliable flight. Before the program was cancelled in 1970, 22 engines were tested and no single RD-270 survived to perform a fourth static fire, a testament to the immense challenge of FFSC engines.

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Energomash’s FFSC RD-270 engine.

SpaceX appears to have had a much better go of it with Raptor, although many, many engines have definitely been destroyed or irreparably damaged since the full-scale engine’s February 2019 static fire debut. SpaceX CEO Elon Musk says that the 17th completed Raptor engine is almost ready to head to McGregor, Texas to kick off development and acceptance testing.

It remains to be seen when exactly Raptor engines will be mature and reliable enough to perform the 3-10 minute burns needed to send a Starship to orbit, let alone the Moon or Mars, but Musk appears confident that SpaceX is making great progress along those lines.

Per photos and info posted by NASASpaceflight.com earlier today, Raptor engine SN15 is already installed on a recently-reactivated McGregor test stand ahead of its first rocket-related test in almost half a decade.

Formerly used to test Falcon 9 first stages before SpaceX built a new stand for Falcon 9 and Heavy, that tripod stand has been reactivated for the sole purpose of supporting vertical Raptor engine static fire testing, which Musk says will simplify and expedite development by making test conditions much more flight-like. As of now, all subscale and full-scale Raptor engine static fire testing has been performed at horizontal test stands in McGregor, apparently resulting in wear and behavior that would not likely appear if engines were tested vertically.

SpaceX has gone through the same process with its Merlin engine programs, beginning with horizontal testing (far easier and simpler) but ultimately building a number of dedicated vertical test bays to ensure that engine acceptance and development tests can be performed under more flight-like conditions.

SpaceX’s Merlin 1D (Vacuum and Sea Level) tests stands, as well as a bay for upper stage static fires. (April 17, 2018 – Aero Photo)

According to NASASpaceflight, SpaceX may have already fired up Raptor SN15 on its reactivated tripod test stand earlier this week, kicking off Raptor’s first Starhopper-free vertical static fire testing. It’s now unclear where the twin horizontal Raptor test bays will fit into future engine testing given Musk’s comments. More importantly, every completed Starship and Super Heavy rocket will require several dozen new Raptor engines and every one of those engines will likely need to pass acceptance testing (including static fires) in McGregor before they can be installed on a launch vehicle.

SpaceX’s Falcon 9 rocket already requires 10 engines per new booster and upper stage, a test burden SpaceX has only managed with the help of two Merlin 1D stands and one Merlin Vacuum stand, all vertical. In other words, it’s safe to say that the reactivated tripod stand is likely just the first of several vertical Raptor test stands to come.

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Everyone knows that only the best Christmas trees are regulated by ITAR 🙂

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Eric Ralph is Teslarati's senior spaceflight reporter and has been covering the industry in some capacity for almost half a decade, largely spurred in 2016 by a trip to Mexico to watch Elon Musk reveal SpaceX's plans for Mars in person. Aside from spreading interest and excitement about spaceflight far and wide, his primary goal is to cover humanity's ongoing efforts to expand beyond Earth to the Moon, Mars, and elsewhere.

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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.” 

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Credit: @BLKMDL3/X

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. 

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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.

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Credit: Tesla China

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.

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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.

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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.

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Gage Skidmore, CC BY-SA 4.0 , via Wikimedia Commons

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.

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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.

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