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Mars’ longtime polar mystery may have finally been solved

Frozen carbon dioxide covers the south pole of Mars. NASA/JPL-Caltech

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From the surface, Mars may seem like a dry, desert-like world lacking water, but a closer look at the planet’s poles will some striking structures: massive polar ice caps.

At the north pole, the ruddy terrain peeks through the ice, like zebra stripes. In the south pole lurks a mystery, a massive deposit of frozen carbon dioxide and water ice. Scientists have spent decades trying to understand how it formed and how it’s linked to the amount of carbon dioxide (CO2) in the Martian atmosphere.

A pair of scientists in the 1960s came up with a plausible theory, and now, decades later, a new study published in Nature Astronomy may have confirmed their findings.

A look at the layering of water ice (white arrows) and CO2 ice (black arrows) at Mars’ south pole. Credit: NASA/JPL-Caltech

The massive deposit measuring 3,280 feet (1 kilometer) thick contains sheets of water ice and carbon dioxide arranged in alternating layers, like a cake. It’s topped off with a thin frosting of carbon dioxide ice, and scientists noticed something interesting: the massive ice deposit contains as much carbon dioxide as the entire Martian atmosphere.

Peter Buhler, a planetary scientist at NASA’s Jet Propulsion Laboratory led the new study. The team used computer simulations to map out the ice, and they were surprised at how closely their models matched with what Robert B. Leighton and Bruce Murray predicted decades ago.

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“Usually, when you run a model, you don’t expect the results to match so closely to what you observe,” he said in a statement. “But the thickness of the layers, as determined by the model, matches beautifully with radar measurements from orbiting satellites.”

Mars has a decent supply of water, it’s just locked up in ice deposits like the one seen here at the Korolev crater. Credit: ESA/DLR/FU Berlin

The ice cap puzzled researchers because according to science, it shouldn’t exist. That’s because water ice is more thermally stable and darker than carbon dioxide ice, which means that it should destabilize when layered between water ice.

However, the new model explains this behavior. Buhler and his team say there are three reasons why the frozen carbon dioxide exists. First, Mars wobbles as it orbits the sun, and when it does, the slight changing of the tilt alters the amount of sunlight that hits the ice. Second, each type of ice reflects the sun a bit differently. And lastly, because of the exposure to sunlight, the carbon dioxide sublimates–meaning it goes directly from a solid to a gas–which alters the atmospheric pressure.

As Mars wobbles, the amount of sunlight reaching the ice varies, causing the ice to form and then later sublimate. When the carbon dioxide ice was forming, water ice would’ve been trapped with it. But when that ice sublimated, the more stable water ice would have remained behind, forming the layers we now see at the south pole.

https://www.youtube.com/watch?v=8Gj8dr6AsYg

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Mars’ climate, just like Earth’s, has changed over millions of years. To that end, not all of the carbon dioxide ice was lost; some were left behind to build up the varying layers we see—a process that has altered the red planet’s atmospheric pressure. 

This is what Leighton and Murray hypothesized back decades ago, and this is what Buhler’s new model shows.

“Our determination of the history of Mars’s large pressure swings is fundamental to understanding the evolution of Mars’s climate, including the history of liquid water stability and habitability near Mars’s surface,” Buhler said in a statement.

By understanding what processes formed the south polar ice cap, scientists can better understand more of what happened in Mars’ history.

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Elon Musk

Tesla isn’t joking about building Optimus at an industrial scale: Here we go

Tesla’s Optimus factory in Texas targets 10 million robots yearly, with 5.2 million square feet under construction.

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Tesla’s Q1 2026 Update Letter, released today, confirms that first generation Optimus production lines are now well underway at its Fremont, California factory, with a pilot line targeting one million robots per year to start. Of bigger note is a shared aerial image of a large piece of land adjacent to Gigafactory Texas, that Tesla has prominently labeled “Optimus factory site preparation.”

Permit documents show Tesla is seeking to add over 5.2 million square feet of new building space to the Giga Texas North Campus by the end of 2026, at an estimated construction investment of $5 billion to $10 billion. The longer term production target for that facility is 10 million Optimus units per year. Giga Texas already sits on 2,500 acres with over 10 million square feet of existing factory floor, and the North Campus expansion is being built to support multiple projects, including the dedicated Optimus factory, the Terafab chip fabrication facility (a joint Tesla/SpaceX/xAI venture), a Cybercab test track, road infrastructure, and supporting facilities.

Credit: TESLA

Texas makes strategic sense beyond the existing infrastructure. The state’s tax structure, lower labor costs relative to California, and the proximity to Tesla’s AI training cluster Cortex 1 and 2, both located at Giga Texas and now totaling over 230,000 H100 equivalent GPUs, means the Optimus software stack and the factory producing the hardware will share the same campus. Tesla’s Q1 report also confirmed completion of the AI5 chip tape out in April, the inference processor designed specifically to power Optimus units in the field.

As Teslarati reported, the Texas facility is intended to house Optimus V4 production at full scale. Musk told the World Economic Forum in January that Tesla plans to sell Optimus to the public by end of 2027 at a price between $20,000 and $30,000, stating, “I think everyone on earth is going to have one and want one.” He has previously pegged long term demand for general purpose humanoid robots at over 20 billion units globally, citing both consumer and industrial use cases.

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Tesla (TSLA) Q1 2026 earnings results: beat on EPS and revenues

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Credit: Tesla

Tesla (NASDAQ: TSLA) reported its earnings for the first quarter of 2026 on Wednesday afternoon. Here’s what the company reported compared to what Wall Street analysts expected.

The earnings results come after Tesla reported a miss on vehicle deliveries for the first quarter, delivering 358,023 vehicles and building 408,386 cars during the three-month span.

As Tesla transitions more toward AI and sees itself as less of a car company, expectations for deliveries will begin to become less of a central point in the consensus of how the quarter is perceived.

Nevertheless, Tesla is leaning on its strong foundation as a car company to carry forward its AI ambitions. The first quarter is a good ground layer for the rest of the year.

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Tesla Q1 2026 Earnings Results

Tesla’s Earnings Results are as follows:

  • Non-GAAP EPS – $0.41 Reported vs. $0.36 Expected
  • Revenues – $22.387 billion vs. $22.35 billion Expected
  • Free Cash Flow – $1.444 billion
  • Profit – $4.72 billion

Tesla beat analyst expectations, so it will be interesting to see how the stock responds. IN the past, we’ve seen Tesla beat analyst expectations considerably, followed by a sharp drop in stock price.

On the same token, we’ve seen Tesla miss and the stock price go up the following trading session.

Tesla will hold its Q1 2026 Earnings Call in about 90 minutes at 5:30 p.m. on the East Coast. Remarks will be made by CEO Elon Musk and other executives, who will shed some light on the investor questions that we covered earlier this week.

You can stream it below. Additionally, we will be doing our Live Blog on X and Facebook.

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SpaceX is following in Tesla’s footsteps in a way nobody expected

In the span of just months in early 2026, SpaceX has transformed itself into one of the world’s most ambitious AI companies. The catalyst: its February acquisition of xAI.

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Credit: Grok

When Elon Musk founded Tesla in 2003, it was a plucky electric car startup betting everything on lithium-ion batteries and a niche luxury Roadster.

Two decades later, Tesla is far more than a car company. Its valuation increasingly hinges on Full Self-Driving software, the Optimus humanoid robot, the Robotaxi program, and the Dojo supercomputer cluster purpose-built for AI training.

Musk has repeatedly described Tesla as an AI and robotics company that happens to sell vehicles. The cars, in this view, are merely the first scalable platform for real-world AI.

Now, SpaceX is tracing an eerily similar path, only faster and in a direction almost no one anticipated. Founded in 2002 to make spaceflight routine and eventually multiplanetary, SpaceX spent its first two decades perfecting reusable rockets, landing Falcon 9 boosters, and building the Starlink megaconstellation.

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Elon Musk launches TERAFAB: The $25B Tesla-SpaceXAI chip factory that will rewire the AI industry

It was an engineering and manufacturing powerhouse, not a software play. Yet, in the span of just months in early 2026, SpaceX has transformed itself into one of the world’s most ambitious AI companies. The catalyst: its February acquisition of xAI.

The xAI deal, announced on February 2, was structured as an all-stock transaction that valued the combined entity at roughly $1.25 trillion—SpaceX at $1 trillion and xAI at $250 billion. In a memo to employees, Musk framed the merger as the creation of “the most ambitious, vertically-integrated innovation engine on (and off) Earth.”

The new SpaceX now owns Grok, the large language model family that powers the chatbot of the same name, along with xAI’s massive training infrastructure. More importantly, it has a declared mission to move AI compute off-planet.

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Earth-based data centers are hitting hard limits on power, cooling, and land. Musk’s solution is orbital data centers, or constellations of solar-powered satellites that act as supercomputers in the sky.

SpaceX has already asked regulators for permission to launch up to one million such satellites. Starship, the company’s fully reusable heavy-lift vehicle, is the only rocket capable of delivering the necessary mass at the required cadence.

Each orbital node would enjoy near-constant sunlight, vast radiator surfaces for passive cooling, and zero terrestrial real-estate costs. Musk has predicted that within two to three years, space-based AI inference and training could become cheaper than anything possible on the ground.

This is not a side project; it is the strategic centerpiece Musk has envisioned for SpaceX. Starlink already provides the global low-latency backbone; next-generation V3 satellites will carry onboard AI accelerators. Rockets deliver the hardware, while AI optimizes every aspect of launch, landing, and constellation management.

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The feedback loop is self-reinforcing, too. Better AI makes better rockets, which launch more AI infrastructure.

Just yesterday, on April 21, SpaceX doubled down.

It secured an option to acquire Cursor—the fast-growing AI coding tool beloved by software engineers—for $60 billion later this year, or pay a $10 billion partnership fee if the full deal does not close.

Cursor’s models already help engineers write code at superhuman speed. Pairing that technology with SpaceX’s Colossus-scale training clusters (the same ones powering Grok) positions the company to dominate AI developer tools, much as Tesla dominates autonomous driving software.

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Why SpaceX just made a $60 billion bet on AI coding ahead of historic IPO

The parallels with Tesla are striking. Both companies began in a single, capital-intensive sector: Tesla with EVs, SpaceX with launch vehicles. Both used early hardware success to fund AI at scale. Tesla’s Dojo supercomputers train neural nets on billions of miles of real-world driving data; SpaceX now trains on telemetry from thousands of orbital assets and re-entries.

Tesla’s FSD chip runs inference on cars; SpaceX’s future satellites will run inference in orbit.

Tesla’s Optimus robot will work in factories; SpaceX envisions lunar factories manufacturing more AI satellites, eventually using electromagnetic mass drivers to fling them into deep space.

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Critics once dismissed Musk’s multi-company empire as unfocused. The 2026 moves reveal the opposite: deliberate convergence.

SpaceX is no longer merely a rocket company that sells internet from space. It is an AI company whose competitive moat is literal orbital infrastructure and the only vehicle that can service it at scale. The forthcoming IPO, expected later this year, will almost certainly be pitched not as a space play but as the purest bet on AI infrastructure the public market has ever seen.

Whether the orbital data-center vision survives regulatory scrutiny, astronomical concerns about light pollution, or the sheer engineering challenge remains to be seen.

Yet the strategic direction is unmistakable. Just as Tesla proved that software and AI could redefine the century-old automobile, SpaceX is proving that rockets are merely the delivery mechanism for the next great computing platform—one that floats above the clouds, powered by the sun, and limited only by the physics of orbit.

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In that unexpected sense, history is repeating. Tesla stopped being “just a car company” years ago. SpaceX has now stopped being “just a rocket company.” Both are becoming something far larger: AI powerhouses with hardware moats so deep that competitors will need their own reusable megaconstellations to keep up.

The age of terrestrial AI is ending. The age of space-based AI is beginning—and SpaceX is building the launchpad.

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