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SpaceX Exceeds Launch Goals for 2023, Plans to Launch 90% of Payloads in 2024

SpaceX Exceeds Launch Goals

SpaceX has exceeded its launch goals for 2023, delivering 80% of all Earth payload mass to orbit so far this year, CEO Elon Musk said. China has delivered 10%, and the rest of the world combined has delivered the remaining 10%.

Following the company’s record-breaking 62nd successful flight of the year on Sunday, Musk revealed a few details about SpaceX’s plans for next year. The space exploration company, he said, will be responsible for delivering 90% of all payload to orbit mass for 2024. And once SpaceX’s bold Starship program gets up and running, that number will exceed 99%, Musk said.

“These magnitudes are madness to consider, but necessary to make consciousness multiplanetary,” Musk said in a post on his social media platform, X.

Musk’s latest Starship predictions come a little more than a week after the rocket’s booster performed a “static fire” test, igniting its engines for six seconds. The booster fired 29 of its 33 engines during its first static fire on August 6; all 33 engines fired up during this second test on August 25.

After the successful static fire, Musk teased the highly anticipated second launch of Starship, saying: “Getting ready for the next Starship flight.”

It’s still unclear exactly when SpaceX plans to try to fly Starship again. The rocket’s first flight occurred on April 20 of this year and ended in a fiery explosion above the Gulf of Mexico. Musk said in June that SpaceX has made more than 1,000 design changes to Starship following the destruction of the first rocket. He said at the time that both the pad and rocket should be ready for a secondary launch in about six weeks.

These optimistic plans come in the wake of a lawsuit a coalition of environmental groups brought against the Federal Aviation Administration for allowing SpaceX to launch Starship without properly addressing the impact on the surrounding area. It remains unclear whether this suit will impact Starship’s timeline.

“The FAA’s failure to fully consider the impacts of the Starship Launch Program,” the suit reads, “was arbitrary and capricious, in violation of NEPA and the Administrative Procedure Act.”

This increase in rocket flights spearheaded by Musk and SpaceX represents an additional environmental threat in the form of the injection of soot into the upper layers of the atmosphere, something that could warm those layers and weaken the protection of the ozone layer, contributing to climate change.

At around the same time that SpaceX was launching its 62nd rocket of the year, delivering an additional 21 Starlink satellites into orbit, the company’s Dragon capsule safely delivered four astronauts back to Earth.

The astronauts, making up NASA and SpaceX’s Crew-6 mission, were returning after a six-month stay aboard the international space station. The Dragon capsule — whose exterior heated up to around 3,500 degrees Fahrenheit — was flying at more than 17,000 miles per hour before deploying a series of parachutes and landing in the ocean off the coast of Jacksonville, Florida.

In addition to the environmental concerns, there are also safety concerns associated with SpaceX’s ambitious launch plans. The company has had a number of high-profile rocket failures in recent years, including the explosion of a Falcon 9 rocket in 2016 that killed a SpaceX employee.

Despite the risks, Musk has said that he is committed to making SpaceX the leading provider of launch services in the world. He has also said that he believes that Starship will eventually be used to transport humans to Mars.

Only time will tell whether Musk’s ambitious plans will be realized. But one thing is for sure: SpaceX is playing a major role in the future of space exploration.

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Meta is betting big, perhaps too big, on artificial intelligence. As the global race to build AI infrastructure heats up, the social media giant is investing billions into what it believes will define the next era of computing. But as Wall Street’s latest reaction shows, not everyone is buying it.

The company, whose chief executive is Mark Zuckerberg, is constructing two giant data centers in the U.S. as part of a wider AI expansion. U.S. tech companies collectively will invest as much as $600 billion in infrastructure over the next three years, according to estimates from industry insiders, with Meta as one of the biggest spenders.

But as Silicon Valley celebrates the AI boom, investors are asking one question: whether Meta’s spending spree is sustainable, let alone strategic.

Earnings Reveal Soaring Costs — and Investor Doubts

Meta’s latest quarterly report showed a sharp rise in costs: operating expenses were up $7 billion year over year and capital expenditures rose nearly $20 billion, largely driven by the acquisition of AI infrastructure and talent. The company generated $20 billion in profit for the quarter, but investors focused on the ballooning expenses — and the lack of clear AI monetization.

During the earnings call, Zuckerberg defended the aggressive spending.

“The right thing is to accelerate this — to make sure we have the compute we need for AI research and our core business,” he said. “Once we get the new frontier models from our Superintelligence Lab (MSL) online, we’ll unlock massive new opportunities.”

But the reassurance didn’t land. Meta’s stock sank 12% by Friday’s close, wiping out more than $200 billion in market value within days.

Big Spending, Small Returns (For Now)

While Meta isn’t alone in its AI splurge – Google, Microsoft, Nvidia, and OpenAI are also spending billions on computing – the key difference is in the results. Google and Nvidia are already experiencing strong revenue growth thanks to AI, while OpenAI, although much more risky, has one of the fastest-growing consumer products in history, generating around $20 billion a year.

But Meta has yet to introduce the blockbuster AI product that would seem to justify the astronomical spending.

Its flagship Meta AI assistant reportedly serves over a billion users, but this is largely a factor of its embedding across Facebook, Instagram, and WhatsApp rather than organic adoption. Analysts say it still lags far behind in functionality and brand strength compared to competitors such as ChatGPT and Claude.

Meanwhile, Meta’s Vibes video generator, which gave the company a fleeting bump in engagement, has yet to prove its commercial viability. And while the Vanguard smart glasses it introduced with Ray-Ban do hold some promise for combining AI and augmented reality, they’re still more prototype than core business driver.

Zuckerberg’s Vision: Superintelligence and the Future

Undeterred by the skepticism, Zuckerberg insists Meta’s AI ambitions are only just getting started. He said the company’s Superintelligence Lab, or MSL, is working on next-generation “frontier models” that will power classes of products entirely new.

“It’s not just Meta AI as an assistant,” Zuckerberg said. “We expect to build new models and products — things that redefine how people and businesses interact with technology.”

Yet, he didn’t provide any details or timelines-a thing that frustrated analysts, who wanted some concrete projections. The promise of “more details in the coming months” wasn’t enough to calm investor nerves.

The AI Bubble Question

A massive infrastructure build-out at Meta has revived fears that the technology industry might be inflating yet another bubble. With tens of billions of dollars pouring into GPUs, data centers, and AI labs, some analysts warn that valuations in the sector are running ahead of tangible outcomes.

Yet, others argue that Meta’s financial position gives it more room to experiment. Unlike many AI startups, Meta still has a profitable advertising empire to fall back on. Its 3 billion monthly active users across its apps provide an unmatched data advantage — if it can find a compelling AI use case.

Where Does Meta Go From Here?

The direction of the company is not determined. Fundamental strategic questions are still hanging:

Will Meta use its vast personal data ecosystem to challenge OpenAI and Anthropic directly?

Does it want to integrate AI-powered advertising and business tools for enterprises?

Or will it shift to immersive consumer products, merging AI with AR/VR in the metaverse?

For now, those answers remain elusive. One thing is for sure: Zuckerberg is playing the long game, one that could either solidify Meta’s role in the next era of computing or turn into one of Silicon Valley’s most expensive miscalculations. As the AI arms race accelerates, Meta’s challenge isn’t just to build smarter machines — it’s to convince investors, and the world, that the company still knows where it’s going.

Redmond, Washington — In a bold move to expand its artificial intelligence infrastructure, Microsoft announced a $9.7 billion deal with data-center operator IREN that would give the tech giant long-term access to Nvidia’s next-generation AI chips. The agreement underscores how deeply the AI race has become defined by access to high-performance computing power.

That investment will also translate into a five-year partnership that lets Microsoft significantly ramp up its cloud computing and AI without having to immediately build new data centers or secure additional power—two of the biggest bottlenecks constraining Microsoft’s AI expansion today.

IREN Shares Spike Following Microsoft Partnership

Following that announcement, IREN’s stock soared as much as 24.7% to a record high before finishing nearly 10% higher by Monday’s close. The news also gave a modest lift to Dell Technologies, which will be supplying AI servers and Nvidia-powered equipment to IREN as part of the collaboration.

The deal includes a $5.8 billion equipment agreement with Dell, part of which involves IREN providing Microsoft with access to systems equipped with the advanced Nvidia chips known as the GB300.

Strengthening Microsoft’s AI Muscle

The move highlights the increasing competition between tech giants like Amazon, Google, and Meta in securing computing capacity that powers generative AI tools such as ChatGPT and Copilot among other machine-learning models.

Microsoft has invested heavily in OpenAI amid mounting infrastructure constraints, as demand for AI-powered services explodes across its cloud ecosystem. Earnings reports from major tech firms last week showed that a limited supply of chips and data-center capacity remains the cap on how much the industry can capitalize fully on the boom in AI.

In return, IREN gets an immediate infrastructure boost by partnering with Microsoft without the high upfront costs associated with building new hyperscale data centers. That is also a way to stay agile as the generations are coming fast from Nvidia.

“This deal is a strategic move by Microsoft to expand capacity while maintaining its AI leadership without taking on the depreciation risks tied to fast-evolving chip hardware,” said Daniel Ives, managing director at Wedbush Securities.

IREN’s Huge Expansion Plans

IREN, whose market value has risen more than sixfold in 2025 to $16.5 billion, operates several large-scale data centers across North America, with a combined total of 2,910 megawatts.

Under the new deal, the company will deploy Nvidia’s processors in phases through 2026 at its 750-megawatt Childress, Texas campus, where it is building liquid-cooled data centers designed to deliver approximately 200 megawatts of critical IT capacity.

The prepayment by Microsoft would finance IREN’s payment for Dell equipment valued at $5.8 billion. However, the deal comes with strict performance clauses that allow Microsoft to revoke the contract if delivery timelines are not met by IREN.

Rising “Neocloud” Powerhouses

The deal also speaks to the emergence of “neocloud” providers like CoreWeave, Nebius Group, and IREN — companies that specialize in selling Nvidia GPU-powered cloud computing infrastructure. These firms have become key partners for Big Tech companies trying to scale AI operations faster than traditional data-center timelines allow.

Earlier this year, Microsoft inked a $17.4 billion deal with Nebius Group, a similar provider, for cloud infrastructure capacity. Taken together, the moves mark Microsoft’s multi-pronged strategy to secure AI infrastructure from multiple partners amid global shortages of Nvidia hardware.

A Broader AI Infrastructure Push

On the same day, AI infrastructure startup Lambda revealed a multi-billion-dollar deal with Microsoft to deploy more GPU-powered cloud infrastructure using Nvidia’s latest hardware.

To the industry analysts, these rapid investments are part of a larger race to lock in supply chains for a resource now viewed as critical as oil in the digital economy: AI computing.

“We’re seeing the dawn of a whole new AI infrastructure ecosystem,” said Sarah McKinney, an AI market strategist. “Microsoft’s deals with IREN and Nebius show that the company is securing every possible avenue to power the next wave of AI applications.”

The Growing Infrastructure Challenge of AI

High demand for AI, meanwhile, has put incredible pressure on computing resources globally. As companies scramble to find GPUs and data-center capacity, the cost of AI infrastructure has soared.

The partnership with existing operators like IREN ultimately gives Microsoft flexibility to meet surging workloads with a minimum of capital expenditure and supply chain delays. This approach allows it to further diversify its geographic footprint, reducing risks associated with power constraints or regulatory hurdles in any single region.

With this agreement, Microsoft forges its status as one of the leaders in the world’s artificial intelligence ecosystem and positions its Azure cloud as a backbone for next-generation AI applications. For IREN, the partnership represents a turning point in its transformation from a low-profile data center provider to an important player in the infrastructure powering the AI revolution. As the world’s demand for AI accelerates, one thing is clear: the race for computing power is just getting underway, and partnerships like Microsoft’s $9.7 billion IREN deal will likely define who leads in the next decade of artificial intelligence.

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