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India could become the fourth country ever to soft-land a spacecraft on the Moon next week
The Indian Space Research Organization (ISRO) is perhaps just a few weeks (maybe days) away from attempting to place the country in the history books, hopefully setting India up to become the fourth nation on Earth – after the Soviet Union, United States, and China – to successfully soft-land on the Moon.
Known as Chandrayaan-2, the mission seeks to simultaneously launch a lunar orbiter, lander, and rover, altogether weighing nearly 3900 kg (8600 lb) at liftoff. If successful, the trio of spacecraft will remain integrated for about two months as the orbiter slowly raises its Earth orbit to eventually intercept and begin orbiting the Moon. Although originally expected to launch on Sunday, July 14th (July 15th local time), a bug with the Indian-built launch vehicle’s upper stage has pushed Chandrayaan-2 outside its original launch window, which ended today (July 16th). Depending on the complexity of the mission profile ISRO is using, the delay should be no more than a few days to a few weeks before the next launch window opens.
Editor’s note: Following ISRO’s July 15th scrub, the Chandrayaan-2 Moon lander mission has been rescheduled for launch no earlier than (NET) 2:43 pm local time, July 22nd (2:13 am PDT/9:13 UTC, July 23rd).
Fourth to the Moon (in one piece)
- All the way back in 1966, the Soviet Union (USSR) became the first to successfully soft-land an uncrewed spacecraft on the Moon with a mission known as Luna-9. Some four months after the momentous achievement, the United States became the second, safely landing Surveyor-1 on the Moon in June 1966.
- At the height of the space race, huge amounts of money was being funneled into these milestones, permitting the companies, institutions, and space agencies building, launching, and operating the individual missions to almost throw hardware at the metaphorical wall until something stuck. With the Soviet space program, this involved 17 failures, two successes, and one partial success in the first 7 years of the Luna initiative, culminating in Luna 9’s successful landing in February 1966.
- The US had three major separate programs known as Ranger, Lunar Orbiter, and Surveyor, the former of which was meant to simply fly past or impact the Moon to acquire detailed photos of its surface. Ranger suffered five consecutive failures and one partial failure before three full successes, while Orbiter was a complete success (5/5) and Surveyor failed only 2 of 7 attempts.
- Ultimately, this little snippet of history is simply meant to emphasize the utterly different approaches of those pathfinder programs relative to modern exploration efforts. In the case of ISRO’s Chandrayaan-2, failure would likely mean several years of delays before the next possible attempt – there is no concurrent (verging on mass-) production of multiple spacecraft like there was with Surveyor and Luna.
- Just shy of 50 years after the back-to-back first and second soft landings of Luna-9 and Surveyor-1, China became the third nation on Earth to successfully soft-land on the Moon with its 2013 Chang’e-3 mission, featuring a lander and rover. This was followed by Chang’e-4 in 2018, which continues to successfully operate 8 months after achieving the first successful soft-landing on the far side of the Moon.
- Finally, just several months ago, private company SpaceIL – supported by Israeli aerospace company IAI – attempted (albeit unsuccessfully) to make Israel the fourth country to land on the Moon.
Indian spacecraft, Indian rocket
- This finally brings us to Chandrayaan-2, what can only be described as a continuation of a recent resurgence in interest and serious robotic exploration of the Moon. Once it launches, the mission will take roughly 56 days to get into position for an attempted soft-landing. Prior to landing, the orbiter – in a circular, 100-km (62 mi) lunar orbit – will actively scout the intended landing site with a high-resolution ~0.3m/pixel camera to help the lander avoid any dangerous terrain.
- Once complete, the lander – carrying a tiny, ~27 kg (60 lb) rover – will begin its deorbit and landing maneuvers, hopefully culminating in a successful, gentle landing near the Moon’s South pole.
- Sadly, the Vikram lander and Pragyaan rover have an expected life of just one lunar day after landing, translating to ~14 Earth days or ~340 hours. This is a strong indicator that the Chandrayaan-2 landing component was not designed to survive the ultra-cold and harsh lunar night, also ~14 Earth days long.
- This isn’t much of a surprise, as surviving the lunar night is a whole different challenge that is rarely worth the hardware, effort, and funding required until the first prerequisite – a soft landing on the Moon – has been successfully demonstrated.
- A follow-up mission known as Chandrayaan-2 has already been proposed and would likely permit far lengthier exploration of the lunar south pole if India and launch partner Japan choose to move forward with it.
- Chandrayaan-2 will be launched on an Indian-built Geosynchronous Satellite Launch Vehicle (GSLV) Mk III-D2 rocket, the most powerful rocket in India’s arsenal. Although GSLV Mk III weighs significantly more than SpaceX’s
- Falcon 9 when fully fueled (640 metric tons to F9’s 550), the rocket is almost a third less capable to Low Earth Orbit (LEO) – 8000 kg to F9’s ~23,000 kg.
- However, thanks to the development of an efficient liquid hydrogen/oxygen (hydrolox) upper stage and engine, the rocket comes into its own when dealing with its namesake – geostationary (i.e. high-altitude) satellite launches. To GTO, GSLV Mk III is reportedly capable of launching at least 4000 kg, almost half of Falcon 9’s expendable performance and almost 75% as much as Falcon 9 with booster landing.
- Even more impressive is the cost: ISRO purchased a block of 10 GSLV Mk III rockets in 2018 for roughly $630M, translating to ~$63M per rocket, nearly equivalent to Falcon 9’s own list price of $62M. This places GSLV Mk III around the same level as Russia’s Proton-M rocket in terms of a cost-to-performance ratio, still second to Falcon 9 in most cases. GSLV Mk III has only launched three times (all successful) since its 2014 debut and Chandrayaan-2 will be its fourth launch.
Elon Musk
SpaceX’s next trillion dollar bet has nothing to do with rockets, Musk tells staff
Elon Musk told SpaceX staff AI revenue will soon dwarf rockets and Starlink combined entirely.
Elon Musk told SpaceX employees this week that artificial intelligence, not rockets, will soon carry the company’s revenue. In a roughly 29 minute internal address posted on SpaceX’s X account on Tuesday, Musk said AI revenue will pass every other line of business at SpaceX “probably in September” and pull further ahead by the fourth quarter.
The numbers he gave are specific. SpaceX currently runs 1.4 gigawatts of AI compute capacity. Musk wants that at 10 gigawatts by the end of 2027, a jump he tied directly to revenue: “if we bring 10GW of AI online by the end of next year, it will be $300 billion to $500 billion a year in revenue.” He called those “big numbers,” which undersells a projection larger than what most countries produce in a year.
We made rockets reusable and are rebuilding the internet in space. The next challenge: making life multiplanetary and understanding the true nature of the universe
Watch @ElonMusk deliver a company update to @SpaceX employees pic.twitter.com/5c8rxoCQfu
— SpaceX (@SpaceX) August 11, 2026
Musk went further on where AI fits into SpaceX’s future. “Probably in four or five years, AI will be 99% of the value of SpaceX,” he told staff, adding that digital intelligence would eventually run “a trillion times” ahead of biological intelligence as computing scales. He tied that growth to the company’s founding mission, telling employees “we must win on AI, because the future is overwhelmingly AI and robots,” with the payoff meant to help fund Starship and a Mars program that increasingly runs through Terafab, the joint Tesla, SpaceX and xAI chip plant.
Elon Musk launches TERAFAB: The $25B Tesla-SpaceXAI chip factory that will rewire the AI industry
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None of this is entirely new territory. SpaceX told investors much the same story during its first earnings call as a public company on August 4, where Musk moved the company’s $1 trillion revenue target up a year to 2030 and said Starlink could someday carry a majority of the world’s internet. What the all hands video adds is a hard deadline and a specific power figure Musk had not given publicly before, along with a franker pitch to his own workforce that AI, not launch cadence, is now the thing SpaceX is betting its future on.
The AI revenue itself is not coming from SpaceX training its own models. It is largely Starlink acting as the network layer for xAI’s workloads, plus SpaceX renting out compute capacity directly, the same approach behind the roughly $16 billion the company spent on AI infrastructure in a single quarter.
Musk closed the video with a pitch aimed at recruiting and retention rather than investors, telling employees that anyone who helps SpaceX win the AI race will eventually get the chance to go to the moon or Mars themselves. Whether SpaceX can turn 1.4 gigawatts into 10 in seventeen months is the more immediate question, and one that will show up in quarterly numbers well before anyone leaves Earth.
In a new note to investors on Tuesday, Morgan Stanley analyst Andrew Percoco said that Tesla has one big financial question to answer for investors regarding its Robotaxi rollout, Full Self-Driving software, and Optimus.
Percoco said in the note that, for the most part, investors are still very positive about the direction the company is headed. However, there are some things the firm would like to see, and they have to do with financials.
Tesla (TSLA) Q2 2026 earnings results: miss on EPS, beat on revenue
Tesla bulls are more than convinced that the company’s Full Self-Driving software is proof it can develop physical AI. Financially, however, there are still some questions, especially on elevated spending, which CEO Elon Musk said would occur as the company works to roll out Robotaxi faster and continue developing its Optimus robot.
The latter two are where Tesla will have to prove progress to investors, as Percoco writes that both projects “will require clearer evidence that Robotaxi is scaling and more tangible Optimus proof points to support the ROI on elevated capex.”
Percoco said the second quarter earnings call did not change his long-term thesis of where Tesla is positioned in the AI race, which is out in front. However, there are concerns that weaker gross margins and higher R&D spend will stress financials, and that has “sharpened our (and investors’) focus on measurable progress across Robotaxi and Optimus.”
Additionally, Robotaxi still needs to be proven with more operation in existing cities while maintaining safety but improving how many rides it gives in any given time, he said. For Optimus, Percoco wrote that he is “still looking for evidence beyond commentary around SOP.”
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Morgan Stanley put Percoco in charge of covering Tesla after long-time analyst Adam Jonas transitioned to the automotive side.
Currently, Morgan Stanley has a $415 price target on Tesla and a ‘Hold’ rating on the stock. It is trading at around $330 at the time of publication, which was 2:30 P.M. on the East Coast.
SpaceX’s massive investment in AI will make it a big winner, Argus Research said after the company’s successful earnings call last week.
The firm also upgraded shares to a Buy from Hold and set a $160 price target.
SpaceX (NASDAQ: SPCX) is currently recovering from its heavy AI infrastructure investments, as it spent nearly $16 billion in Q2 alone. The company did this primarily by monetizing high-demand GPU compute capacity at a much faster pace than traditional data center economics would suggest.
Company CFO Bret Johnsen said that SpaceX would be able to pay back anything on new deployments within a year.
There are plenty of ways the company can do this:
Leasing excess compute capacity through contracts
SpaceX has already built Colossus and Colossus II, largely for its own model training. However, much of that capacity is already rented out to third parties. It already has major deals with Anthropic, Google, and Reflection AI. These partnerships are adding billions per month to SpaceX’s spreadsheet.
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High utilization driven by industry-wide scarcity
The demand for advanced AI training and inference capacity continues to exceed what is available for use. SpaceX can fill new racks quickly after they come online, so the capital deployed converts into revenue with minimal idle time.
Additionally, management and outside observers have described the new compute capital as behaving more like a cost-of-goods-sold than traditional multi-year capex, especially because of this rapid monetization pattern.
Capacity has already scaled from ~0.4 GW a year to 1.4 GW annually by the end of Q2. There are targets of more than 2 GW by year-end.
High incremental margins on the rental business once capacity is online
GPU cloud providers often operate at strong gross margins. SpaceX can monetize capacity that was already partially built or can be added efficiently. This means that incremental EBITDA margins on the rental revenue are usually high. This accelerates cash recovery relative to the gross capital outlay.
Parallel monetization of its own AI software and applications
Beyond pure infrastructure rental, SpaceX also generates revenue from Grok through subscriptions and usage, from X through ads, data, and other related services, enterprise APIs, and the planned integration of the Cursor coding tools acquisition.
These application layers ride on the same compute infrastructure and provide additional high-margin streams that could offset build-out costs. AI-segment revenue overall rose sharply to about $2.6 billion in Q2, according to Motley Fool. This was driven primarily by the infrastructure contracts, but the software side is also partially responsible.
Efficient, large-scale deployment and vertical integration advantages
SpaceX has emphasized the rapid construction of power and cooling infrastructure and favorable cost-per-megawatt economics relative to industry benchmarks in some disclosures.
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Combined with its ability to scale capacity aggressively and the fact that many contracts start generating revenue within months of capacity coming online, the effective payback compresses dramatically compared with more conventional multi-year data-center projects.
SpaceX’s dominant near-term recovery path will turn the AI clusters into a hyperscale-style compute rental business for other leading AI companies while still using a portion for internal models.
SpaceX’s next trillion dollar bet has nothing to do with rockets, Musk tells staff
Tesla has one big financial question to answer for investors: Morgan Stanley
