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SpaceX customer iSpace updates Falcon 9-launched Moon lander, rover plans
Japanese commercial space company iSpace has provided an updated schedule for its first private missions to the Moon, both set to launch on Falcon 9 rockets and land on the Moon as early as 2021 and 2023.
iSpace’s goal is to understand and map lunar resources (particularly water ice) and eventually gather and process those materials into resources that could help enable far more ambitious lunar exploration, up to and including a partially self-sustaining lunar outpost capable of supporting astronauts. Known as Hakuto-R (“white rabbit” reboot), iSpace began as a team pursuing the Google Lunar XPRIZE before its cancelation in 2018 after several postponements pushed competing teams well past the prize deadline.
We also announced an updated mission schedule for the HAKUTO-R Program. We will perform a lunar landing in 2021 and a lunar landing and rover deployment in 2023. https://t.co/jGaZ3eqRRE— HAKUTO-R (@HAKUTO_Reboot_e) August 22, 2019
Despite the death of the Lunar XPRIZE, iSpace managed to not only survive but thrive in a more entrepreneurial environment. The company managed to convince several major investors of the potential value of commercial space exploration and became one of a select few spaceflight startups – certainly the only space resources startup – that has raised almost $100 million.
Relative to similar startups Planetary Resources (purchased by a blockchain company; effectively dead) and Deep Space Industries (acquired by Bradford Space), iSpace is in an unprecedentedly healthy position to realize its space resource ambitions.
NewSpace, OldProblems
One could likely climb to the Moon with nothing more than a printed stack of all the studies, analyses, white papers, and hollow promises ever published on the utilization of space-based resources, an ode to the simultaneous promise and pitfalls the idea poses. As many have discovered, developing the ability to acquire, refine, and sell space resources is one of the most long-lead problems in existence. Put another way, funding a space exploration company on the promise of (or income from) space resources is a bit like paying for a solid-gold ladder by selling the fruit you needed it to reach.
For such an enterprise to make economical sense, one must either have access to ladders that are cheaper than their weight in gold or be able to sell the harvested fruit at breathtaking premiums. The point of this analogy is to illustrate just how challenging, expensive, and immature deep space exploration is relative to the possible resources currently within its grasp. There is also a bit of a circular aspect to space resource utilization: to sell the resources at the extreme premiums needed to sustain their existence, there must be some sort of established market for those resources – ready to purchase them the moment they’re available.
To build a market on space resources, one must already possess space resources to sell. This is the exact thing that government space agencies like NASA should develop, but entrenched and greedy corporate interests have effectively neutered NASA’s ability to develop technology that might transcend the need for giant, ultra-expensive, expendable rockets.
The need to secure funding via investors – investors expecting some sort of return – is the biggest roadblock to space resource utilization. Really, the only conceivable way to sustainably raise funding for space resource acquisition is to already have a functional and sustainable company as a base. SpaceX is a prime example: the company hopes to fund the development of a sustainable city on Mars with income from its launch business and Starlink internet constellation.
Ambitious plans, solid funding
Given all of the above, it’s extremely impressive that iSpace has managed to raise nearly $100M in just a few years and has done so without the involvement of one or several ultra-wealthy angel investors. Of course, it must still be acknowledged that the cost of iSpace’s longer-term ambitions can easily be measured in the tens of billions of dollars, but given an extremely lean operation and rapid success, $100M could plausibly fund at least one or two serious lunar landing attempts.
In the realm of flight tests, iSpace previously planned to perform a demonstration launch in 2020, in which a simplified lander would be used to orbit the Moon but not land. In the last year or so, the company has decided to entirely forgo that orbital test flight and instead plans to attempt a Moon landing on its first orbital flight, scheduled to launch on Falcon 9 no earlier than (NET) 2021. If successful, this inaugural landing would be followed as few as two years later (2023) by a lander and a lunar rover. Assuming a successful second landing, iSpace would move to ramp its production rates, launch cadence, and general ambitions, prospecting all over the Moon in 5-10+ separate lander missions.
iSpace will still face the brick wall that all space resource companies eventually run into. Even if the company can successfully demonstrate a Moon landing and resource prospecting, it will need additional funding (and thus a commercially sustainable plan to sell investors on) to continue work and eventually, just maybe, get to a point where selling space-based resources can become a sustainable source of income.
Regardless of iSpace’s long-term business strategy, the early 2020s will be jam-packed with attempted commercial lunar landings, including Hakuto-R, Astrobotic, Intuitive Machines, and perhaps several other companies’ attempts. By all appearances, the exceptional mix of high performance and low cost offered by SpaceX’s Falcon 9 rocket will serve as a major enabler, allowing companies to put most of their funding into their landers instead of launch costs.
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Tesla’s Head of AI, Ashok Elluswamy, says that something that was expected with version 14.3 of the company’s Full Self-Driving platform has already partially shipped with the current build of version 14.2.
Tesla and CEO Elon Musk have teased on several occasions that reasoning will be a big piece of future Full Self-Driving builds, helping bring forth the “sentient” narrative that the company has pushed for these more advanced FSD versions.
Back in October on the Q3 Earnings Call, Musk said:
“With reasoning, it’s literally going to think about which parking spot to pick. It’ll drop you off at the entrance of the store, then go find a parking spot. It’s going to spot empty spots much better than a human. It’s going to use reasoning to solve things.”
Musk said in the same month:
“By v14.3, your car will feel like it is sentient.”
Amazingly, Tesla Full Self-Driving v14.2.2.2, which is the most recent iteration released, is very close to this sentient feeling. However, there are more things that need to be improved, and logic appears to be in the future plans to help with decision-making in general, alongside other refinements and features.
On Thursday evening, Elluswamy revealed that some of the reasoning features have already been rolled out, confirming that it has been added to navigation route changes during construction, as well as with parking options.
He added that “more and more reasoning will ship in Q1.”
🚨 Tesla’s Ashok Elluswamy reveals Nav decisions when encountering construction and parking options contain “some elements of reasoning”
More uses of reasoning will be shipped later this quarter, a big tidbit of info as we wait v14.3 https://t.co/jty8llgsKM
— TESLARATI (@Teslarati) January 9, 2026
Interestingly, parking improvements were hinted at being added in the initial rollout of v14.2 several months ago. These had not rolled out to vehicles quite yet, as they were listed under the future improvements portion of the release notes, but it appears things have already started to make their way to cars in a limited fashion.
Tesla Full Self-Driving v14.2 – Full Review, the Good and the Bad
As reasoning is more involved in more of the Full Self-Driving suite, it is likely we will see cars make better decisions in terms of routing and navigation, which is a big complaint of many owners (including me).
Additionally, the operation as a whole should be smoother and more comfortable to owners, which is hard to believe considering how good it is already. Nevertheless, there are absolutely improvements that need to be made before Tesla can introduce completely unsupervised FSD.
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.
Tesla AI Head says future FSD feature has already partially shipped
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
