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Tesla Roadster and ‘friends’ make history in newly-published log of 57k+ human objects in space
When the Tesla Roadster and its Starman occupant entered space aboard Falcon Heavy’s maiden voyage in 2018, it joined the ranks of one astronomer’s impressive database of human-made objects that have left Earth: The General Catalog of Artificial Space Objects (GCAT). It’s the most comprehensive collection of space object data available to the public, and its author recently published it in full for open-source use.
Jonathan McDowell, currently with the Harvard-Smithsonian Center for Astrophysics, created GCAT as an endeavor that began about 40 years go during his Apollo-inspired childhood.
“It was hard for me growing up in England to get details about space because the media there weren’t as interested in it as the U.S. media, so in a slightly obsessive way I started making a list of rocket launches… Now I have the best list,” McDowell told VICE in recently published comments. Lack of information in his younger days seems to have only been the beginning of the challenges the astronomer was willing to take on for his project. As detailed to VICE, McDowell also traveled to international space agency locations to obtain their old rocket lists and even learned Russian to translate that country’s space object data.
Although McDowell has been collecting his Catalog data for decades, the push to finally put all of his work online was inspired by more recent events. The risks of COVID-19 and “imminent death” threatened the database’s purpose. “There’s no point if it dies with me,” he told VICE. Publishing the GCAT had been in his plans, however, the pandemic pushed its priority to the top of McDowell’s personal bucket list.
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- Data from GCAT (J. McDowell, planet4589.org/space/gcat)
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- Data from GCAT (J. McDowell, planet4589.org/space/gcat)
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- Data from GCAT (J. McDowell, planet4589.org/space/gcat)
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- Data from GCAT (J. McDowell, planet4589.org/space/gcat)
So, what exactly might one use the GCAT for? McDowell had his own suggestions, including the determination of how many working satellites are currently in space. Since the data is easy to export into software that allows sorting of tab-delimited files, one could perhaps also look at the amount of debris produced over the years to get a general picture for how active spaceflight operations were in the past or how they may be progressing. Plenty of information about each object’s origin and owner is included for this kind of research.
One of the GCAT data sets tracks failed objects that would have otherwise made it to orbit. As an example, looking at the number of items from failed launch attempts in 1958 (52) gives a hint as to how intense the space race between the US and the Soviet Union was at the time. Data browsing could be used for general historical inquiry as well. For instance, Sputnik 1, launched by the Soviet Union on October 4, 1957, is object 00001; the Eagle lander still on the Moon from Apollo 11’s mission is object #04041; and the Tesla Roadster is object #43205.
Some of the data can inspire more historical awareness such as the listing of tools lost during on-orbit construction of the Soviets’ Mir Space Station in 1986. Of course, reminders of significant spaceflight misfortunes are also included like the Challenger Space Shuttle explosion in 1986 and SpaceX’s CRS-7 ISS resupply mission failure in 2015.
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- Data from GCAT (J. McDowell, planet4589.org/space/gcat)
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- Data from GCAT (J. McDowell, planet4589.org/space/gcat)
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- Data from GCAT (J. McDowell, planet4589.org/space/gcat)
Since GCAT is inclusive of both functional items and notorious bits of space junk logged from decades of data digging, the Tesla Roadster and its 57,000+ “friends” are poised to help with some serious research now and in the far future.
“My audience is the historian 1,000 years from now,” McDowell explained. “I’m imagining that 1,000 years from now there will be more people living off Earth than on, and that they will look back to this moment in history as critically important.” For fans of Star Trek, this type of record keeping certainly seems to be relevant to future humans more often than not (away mission, anyone?). Perhaps that type of science fiction storyline will transpire into reality, just as so many of SpaceX’s achievements have done already.
Interestingly enough, McDowell is working on another project to track deep space objects beyond Earth’s orbit. Will space debris take center stage around Mars and beyond like it does around our own planet? Seeing the progress in one comprehensive database will certainly be an interesting way to show just how far humans have come since object #00001.
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
