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SpaceX could land Starship on Mars in 2024, says Elon Musk
Four years after Elon Musk revealed “aspirational” plans to launch Starships to Mars in 2022, the SpaceX CEO now believes that 2024 is a more accurate target.
For SpaceX, that two-year ‘delay’ is more impressive than anything given that the company practically restarted Starship development from scratch a year after Musk set the 2022 target. In late 2018, after more than two years of work developing a Starship (then BFR) built out of carbon fiber composites, the CEO revealed that the company was going to completely redesign the rocket to use steel for all major structures.
Two and a half years after that decision, SpaceX has built a vast Starship factory capable of building at least one ship per month, cumulatively fired dozens of full-scale Raptor engines for more than 30,000+ seconds, flown eight full-scale prototypes, and recovered the first full-size Starship in one piece after a high-altitude launch and bellyflop-style descent and landing.
It doesn’t come as a huge surprise that Starship probably wont be attempting any Mars launches in 2022. Had SpaceX not had to return to the drawing board in 2018, Musk may well have been able to achieve that 2022 goal, but wholly redesigning Starship with steel almost certainly delayed development by at least a year. For interplanetary launches, the most efficient trajectories – those that allow a rocket to maximize payload capacity – are only open for several weeks every ~25 months. That means that a rocket that’s one year behind a Mars launch window will still have to wait more than two years for the next launch opportunity.
In Starship’s case, even if SpaceX were ready for its first Mars cargo missions in 2023, it would need to wait until September or October 2024. That’s far from out of the question but three full years will arguably give SpaceX a good amount of time to both ensure that Starship is technically ready and reliable enough to land on Mars while also determining – and likely designing and building – the cargo those first Starships will carry.
SpaceX could also launch the first one or several Mars-bound Starships with an absolute minimum payload under the assumption that success will require several failures, in which case the company would have until 2026 to develop a system capable of finding and gathering Martian ice, processing it into cryogenic liquid oxygen and methane, and storing that propellant for months or even years. Without that complex system of in-situ resource utilization (ISRU), Starship will never be able to leave Mars, turning initial crewed missions into one-way trips.
In the meantime, while SpaceX has successfully proven that Starship’s exotic skydiver-style landing is viable on planets with atmospheres, orbital Starship flight tests will likely pose just as many challenges. Starship will have the largest heat shield of any spacecraft ever built, while that heat shield will also be the first non-ablative shield ever developed by SpaceX. Even if Starship aces reentries from low Earth orbit (LEO), reentries from geostationary, lunar, or Mars transfer orbits are all multiple times more stressful, requiring still more testing to ensure that its ceramic heat shield and steel hull can withstand interplanetary velocity reentries.
SpaceX will also have to develop unprecedented thermal management solutions to keep hundreds of tons of cryogenic liquid propellant at the right temperatures for weeks, months, or even years in orbit, deep space, and on the surfaces of other moons and planets. This is all to say that SpaceX has its work cut out for it as it approaches the dawn of orbital Starship flight tests and has to tackle a number of daunting technical challenges it might end up being the first to solve. But, as SpaceX always has, it will devour each problem piece by piece until Starship is exactly as capable and revolutionary as the company and its CEO have long promised – if a bit behind schedule.
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
