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The SpaceX’s Choice of Goldman Sachs as Lead Underwriter

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The logo for Goldman Sachs is seen on the trading floor at the New York Stock Exchange (NYSE) in New York City, New York, U.S., November 17, 2021. REUTERS/Andrew Kelly/Files

The reported selection of SpaceX choosing Goldman Sachs as a lead underwriter for its anticipated IPO marks a pivotal moment in the long arc of private-to-public capital transitions in the aerospace and defense sector. If confirmed and executed, the move signals not only SpaceX’s maturation as a commercial enterprise but also the increasing convergence of frontier technology firms with traditional Wall Street capital-formation machinery.

For years, SpaceX has occupied a unique position in global markets: a company with near-sovereign strategic importance in launch infrastructure, satellite communications via Starlink, and deep integration into U.S. national security missions, yet one that has remained deliberately private. This structure allowed it to scale aggressively without the quarterly earnings pressure typical of public markets.

However, the selection of a top-tier investment bank such as Goldman Sachs suggests that the company is now preparing to transition into a more formalized capital structure, one that can support even larger deployment of long-duration infrastructure capital.

An IPO of SpaceX would likely be one of the most complex in modern financial history. Unlike traditional tech listings, SpaceX is not a pure software company with high-margin recurring revenue. Instead, it operates across vertically integrated aerospace manufacturing, launch services, and global satellite broadband infrastructure. Each of these segments carries distinct risk profiles, regulatory constraints, and capital intensity.

Structuring a public offering would require careful segmentation of revenue streams and potentially novel approaches to valuation that account for long-term orbital infrastructure assets. The involvement of Goldman Sachs also reflects a strategic alignment with institutional investor appetite. In recent years, large asset managers and sovereign wealth funds have increasingly sought exposure to hard-tech infrastructure, particularly in areas tied to space, defense logistics, and global connectivity.

SpaceX, with its Starlink constellation rapidly expanding global internet coverage, sits at the intersection of telecommunications and orbital infrastructure—arguably one of the most capital-intensive but strategically valuable sectors in the global economy.

From a market perspective, an IPO could serve multiple functions. It would provide liquidity for early investors and employees, establish a public valuation benchmark for satellite internet and launch services, and potentially unlock a new wave of secondary capital for expansion into next-generation systems, including interplanetary transport ambitions.

It would also place SpaceX under heightened regulatory scrutiny and disclosure requirements, fundamentally altering its governance dynamics. However, challenges remain significant. Market timing is critical, especially in an environment where interest rates, risk appetite, and equity valuations can shift rapidly.

Additionally, SpaceX’s revenue concentration—heavily reliant on Starlink subscription growth and government contracts—may raise questions among public market investors about cyclical exposure and geopolitical risk. The selection of Goldman Sachs as a lead IPO partner represents more than a procedural banking appointment.

It signals that SpaceX is moving closer to entering the public equity ecosystem on a scale that could redefine aerospace market capitalization benchmarks. If successful, the offering would not just be another tech IPO—it would be a structural event in the evolution of capital markets, bridging orbital infrastructure with global public liquidity in a way that has few historical parallels.

VVV Begins Trading on Robinhood As Many V1 Punks Sell for 6 Figures

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VVV begins trading on Robinhood, marking another step in the gradual convergence between retail brokerage infrastructure and emerging crypto-native assets. The listing of VVV signals continued appetite among retail platforms for expanding token access beyond major-cap assets, especially as liquidity fragmentation across exchanges pushes issuers to seek broader distribution channels.

V1 Punks or V1 CryptoPunks Wrapped are the original 2017 CryptoPunks from the buggy V1 smart contract; pre-V2 official collection. They are historically significant as the true first edition but had a flaw that prevented proper ETH transfers to sellers. A community wrapper ERC-721 makes them safely tradable on platforms like OpenSea and Blur.

Reports of 45+ sales in 24h periods, with 100s of ETH traded. Some self-transfers and wash concerns noted in trading patterns. Unwrapped V1 Punks are risky to trade due to the original bug—use wrapped versions or new tools. V1s trade at a discount to V2 CryptoPunks due to provenance debates, but they appeal to history-focused collectors.

 

While the asset itself remains early in its market lifecycle, its inclusion on a mainstream brokerage interface underscores a broader trend: token discovery is increasingly being mediated by regulated, user-friendly fintech rails rather than purely decentralized exchanges. Alongside the token’s debut, the NFT market recorded renewed attention as several rare V1 Punks sold for six-figure sums.

The collection, known as V1 Punks, represents one of the earliest iterations of the CryptoPunks experiment and has long been treated as a historical artifact within NFT culture. These transactions highlight the persistence of demand for culturally significant digital collectibles, even in periods where broader NFT trading volumes remain uneven. The six-figure price points suggest that scarcity combined with provenance continues to drive valuation in legacy NFT sets, particularly those tied to the earliest Ethereum-based art movements.

Taken together, the simultaneous emergence of new token listings on Robinhood and high-value secondary NFT sales reflects a bifurcated digital asset market.

On one side, brokerage platforms are packaging early-stage tokens like VVV for mainstream accessibility; on the other, legacy NFT collections such as V1 Punks continue to function as cultural store-of-value assets rather than speculative trading vehicles. This duality underscores how digital assets are increasingly stratified between liquidity-driven instruments and provenance-driven collectibles.

Market participants are, in effect, pricing two different narratives: one centered on utility and distribution, the other on historical significance and rarity. Looking ahead, the trajectory of both VVV and V1 Punk sales will likely depend on broader liquidity conditions, risk appetite, and the continued integration of crypto assets into mainstream financial platforms.

If brokerage-driven listings expand further, assets like VVV may benefit from increased retail visibility, though volatility remains a defining feature of early-stage tokens. Meanwhile, NFTs with historical significance such as V1 Punks may continue to decouple from broader market cycles, trading instead on cultural narrative and collector demand. The intersection of these trends suggests a maturing ecosystem where infrastructure access and digital provenance are becoming equally important drivers of valuation.

The day’s activity reflects a market still defining the boundary between speculative experimentation and established digital asset classes, with both brokerage listings and legacy NFT sales contributing to an evolving narrative of value formation in blockchain-based economies.

Nvidia Posts Record $81.6 Billion Q1 Revenue as AI Infrastructure Boom Accelerates

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American multinational technology company NVIDIA has delivered another historic quarter, reporting record revenue of $81.6 billion for the first quarter of fiscal 2027, ended April 26, 2026.

The AI giant chip maker historic report, comes as surging global demand for artificial intelligence infrastructure continued to fuel unprecedented growth across its business.

Nvidia significantly surpassed Wall Street expectations of approximately $79 billion, with quarterly revenue rising 85% year-over-year.

The company’s dominant Data Center segment remained the primary growth engine, generating a record $75.2 billion in revenue, representing a 92% increase from the same period last year and a 21% rise sequentially.

The strong performance highlights NVIDIA’s growing influence at the center of the global AI race, as enterprises, cloud providers, and hyperscalers continue investing aggressively in AI factories and next-generation computing infrastructure.

Key financial metrics

GAAP net income surged 211% year-over-year to $58.3 billion, while GAAP earnings per share climbed to $2.39, also up 214% from the previous year. Non-GAAP earnings per share came in at $1.87, exceeding analyst expectations of around $1.77.

NVIDIA also maintained exceptionally strong profitability levels, posting gross margins of 74.9% on a GAAP basis and 75.0% on a non-GAAP basis. Free cash flow for the quarter reached approximately $48.6 billion.

The company continued its aggressive shareholder return strategy, distributing nearly $20 billion through stock buybacks and dividends during the quarter.

NVIDIA additionally announced a new $80 billion share repurchase authorization and raised its quarterly cash dividend from $0.01 to $0.25 per share, marking a dramatic 25-fold increase.

According to founder and CEO Jensen Huang, the rapid expansion of AI infrastructure is reshaping the global technology landscape.

He noted that the buildout of AI factories represents one of the largest infrastructure expansions in human history, adding that agentic AI is already generating measurable value across industries and scaling rapidly within enterprises.

As part of its evolving strategy, NVIDIA introduced a new reporting structure centered around two major platforms: Data Center and Edge Computing. The Data Center category will now be further segmented into Hyperscale and ACIE (AI Clouds, Industrial, and Enterprise), reflecting the diversification of demand drivers across industries.

Despite the record-breaking earnings, NVIDIA shares traded slightly lower in after-hours trading as investors weighed the company’s forward guidance and potential signs of moderation in the AI investment cycle.

The company also acknowledged the increasingly competitive AI semiconductor landscape in a recent regulatory filing, noting that several major customers are developing their own custom AI chips and application-specific integrated circuits (ASICs) tailored for specific workloads.

Although NVIDIA did not directly identify the companies, major hyperscalers including Google, Amazon, Meta, and Microsoft have all accelerated efforts to build proprietary AI silicon solutions.

Meta recently unveiled four custom AI chips designed for manufacturing by Taiwan Semiconductor Manufacturing Company, while Google continues to expand its Tensor Processing Unit (TPU) ecosystem.

Tech giant Google also recently confirmed plans to launch a new AI infrastructure company focused on its proprietary AI chips, with investment backing from Blackstone.

NVIDIA further cautioned that some customers may eventually offer cloud-based AI services that compete directly with its own AI cloud offerings, potentially intensifying competition in the rapidly evolving market.

Nevertheless, NVIDIA’s latest performance reinforces its position as the dominant force in AI infrastructure. With its Blackwell platform ramping up production and future Rubin architectures on the horizon, the company remains deeply embedded in the next phase of the global artificial intelligence revolution.

Looking ahead, the company projected second-quarter fiscal 2027 revenue of approximately $91 billion, plus or minus 2%, signaling continued momentum despite rising investor scrutiny over sustainability of AI spending levels.

Nvidia Reports Another Record Quarter, Authorizes Massive $80bn Buyback Program

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Nvidia delivered another blockbuster quarter on Wednesday, underscoring how the artificial intelligence boom continues to reshape the global technology industry, even as the chip giant signaled that the pace of growth may begin to moderate after two years of explosive expansion.

The company reported revenue of $81.6 billion for the quarter ended April 26, up 20% from the prior quarter, while data center revenue climbed to a record $75.2 billion, reinforcing Nvidia’s dominant position at the center of the AI infrastructure race.

The results further cement Nvidia’s status as the primary supplier powering the generative AI economy, with demand from hyperscalers, cloud providers, and AI model developers continuing to surge as companies race to expand computing capacity.

“Our Blackwell architecture is everywhere, adopted and deployed by every major hyperscaler, every cloud provider, and every major model maker,” Nvidia Chief Financial Officer Colette Kress said.

The earnings report also revealed how aggressively Nvidia is positioning itself financially and strategically for the next phase of AI expansion. Alongside the results, the company authorized a massive $80 billion share repurchase program, one of the largest buyback authorizations in corporate America, signaling management’s confidence in sustained long-term cash generation.

The scale of the buyback highlights the extraordinary profitability Nvidia has achieved from the AI boom. Few companies in history have generated revenue growth at the pace Nvidia has posted over the last two years, fueled largely by demand for its advanced graphics processing units used to train and operate large AI models.

Yet beneath the headline numbers, the report also pointed to important shifts in the market.

Nvidia projected revenue of $91 billion for the next quarter, representing growth of roughly 12%, a notable slowdown compared with the hypergrowth rates investors have become accustomed to since the generative AI boom began.

The moderation is seen as an indication that the company may be entering a more mature phase of the AI infrastructure cycle, where growth remains enormous in absolute dollar terms but becomes harder to sustain at the pace seen over the past two years. Even so, the figures remain staggering by industry standards. Nvidia’s quarterly revenue now exceeds the annual sales of many global semiconductor firms.

The earnings also provided fresh insight into Nvidia’s expanding influence beyond chips alone. One of the biggest surprises in the filing was the rapid growth of the company’s private investment portfolio.

Nvidia disclosed that its holdings in privately owned companies, categorized as “non-marketable equity securities,” surged from $22 billion in January to $43 billion by April. The increase was driven largely by $18.5 billion in new investments during the quarter, compared with just $649 million in equivalent purchases in the prior quarter.

The figures do not include Nvidia’s recent investments in public companies such as Corning and IREN, nor its previously announced commitment to invest $30 billion in OpenAI earlier this year.

That growing web of investments has drawn increased attention from investors and regulators who are closely watching how deeply Nvidia is embedding itself across the AI ecosystem, including cloud providers, model developers, and infrastructure firms.

The company’s strategy increasingly resembles a vertically integrated AI empire spanning chips, networking, software, cloud infrastructure, and strategic equity stakes.

During the earnings call, Nvidia CEO Jensen Huang highlighted the company’s expanding partnership with Anthropic, one of OpenAI’s biggest competitors.

“The amount of capacity we’re going to bring online for Anthropic this year and next year is going to be quite significant,” Huang told investors. “Our coverage for Anthropic had been largely zero until this.”

The comments come amid intensifying competition among AI labs to secure computing power as training costs continue to soar. Nvidia’s latest Blackwell chips are at the center of that race, with major AI developers competing for supply.

The company also indicated that China remains a limited contributor to current growth despite recent approvals involving exports of H200 chips. Kress said Nvidia had not yet generated meaningful revenue from those exports and warned that uncertainty remains over whether broader imports into China will ultimately be permitted.

That underscores the ongoing geopolitical risks hanging over the semiconductor industry as Washington continues tightening export restrictions aimed at limiting China’s access to advanced AI computing technologies. The restrictions have forced Chinese technology firms to accelerate efforts to develop domestic alternatives while prompting U.S. chipmakers to restructure supply chains and sales strategies.

Still, Nvidia’s latest results show that global AI demand remains strong enough to offset much of the China-related pressure for now. The company’s dominance has also reshaped capital spending priorities across the technology sector. Hyperscalers, including Microsoft, Amazon, and Google, are collectively spending hundreds of billions of dollars annually on AI infrastructure, much of it flowing directly into Nvidia’s ecosystem.

At the same time, AI startups and model developers are racing to secure access to Nvidia hardware amid fears that compute scarcity could become a competitive bottleneck.

Anthropic Strikes $40bn Infrastructure Deal with xAI’s, Turning Musk’s AI Ambitions Into a Compute Landlord Business

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Anthropic has struck one of the largest infrastructure agreements yet in the artificial intelligence race, committing to pay more than $40 billion over four years for computing capacity from xAI, according to disclosures contained in SpaceX’s S-1 filing.

The agreement gives Anthropic access to 300 megawatts of compute capacity at xAI’s Colossus 1 data center near Memphis, effectively securing the facility’s entire output. Anthropic will pay approximately $1.25 billion per month through May 2029, although the first two months come at a discounted rate while xAI completes deployment ramp-ups.

The transaction indicates that the economics of artificial intelligence are rapidly shifting from purely model development toward control of power-intensive infrastructure. In the AI industry, access to electricity, advanced chips, and large-scale data centers has increasingly become as strategically important as the models themselves.

For xAI, the agreement offers a massive new revenue stream at a critical moment. Elon Musk’s AI company has spent aggressively building GPU clusters to compete with rivals, including Anthropic, OpenAI, and Google. But maintaining unused compute infrastructure is extraordinarily expensive, particularly as companies race to deploy hundreds of thousands of Nvidia AI chips.

SpaceX described the arrangement as a way to “monetize unused compute capacity in our infrastructure,” adding in the filing that it expects to pursue “additional similar services contracts.”

The language points to an emerging hybrid strategy in the AI sector. Rather than using infrastructure solely for internal AI development, xAI is increasingly acting like a commercial cloud provider, leasing excess capacity to outside companies when utilization drops below planned levels.

That model has become known in Silicon Valley as the “neocloud” approach, where AI firms attempt to offset the staggering cost of building hyperscale computing clusters by selling spare compute to rivals, startups, or enterprises.

The agreement also reveals how quickly competitive lines are blurring in the AI race. Anthropic and xAI are direct rivals in foundation models and AI assistants, yet Anthropic is now relying on Musk’s infrastructure to expand its own capabilities.

The deal may also signal that xAI built more infrastructure than it currently needs. The company has invested heavily in Colossus, which was promoted as one of the world’s largest AI supercomputing clusters. However, recent reports of slowing usage for xAI’s Grok chatbot suggest parts of that capacity may not have been fully utilized.

xAI can convert idle assets into recurring revenue while preserving its long-term expansion plans by leasing the infrastructure to Anthropic.

The arrangement also reflects mounting financial pressure across the AI industry. Training and operating frontier AI systems now require enormous capital expenditures, forcing companies to search for alternative monetization strategies.

Infrastructure spending across the AI ecosystem has surged dramatically over the past two years. Hyperscalers and AI labs are collectively projected to spend hundreds of billions of dollars annually on data centers, networking equipment, advanced cooling systems, and power procurement.

At the center of the spending boom is Nvidia, whose AI chips remain the industry standard for training large language models. But acquiring GPUs alone is no longer sufficient. Companies now need access to reliable electricity grids, land, fiber connectivity, and advanced cooling systems capable of handling increasingly dense AI clusters.

The scale of the Anthropic-xAI agreement highlights how compute itself is becoming a tradable commodity in the AI economy. The structure also gives both sides flexibility. According to the filing, either company can terminate the arrangement with 90 days’ notice. That clause could prove important in an industry where technological shifts, regulatory changes, and competitive dynamics move rapidly.

For Anthropic, securing long-duration compute access helps reduce dependence on traditional cloud providers while guaranteeing access to scarce infrastructure as demand for AI accelerates. The company has been aggressively expanding capacity in recent months amid rising adoption of its Claude models across enterprise and developer markets.

The deal is expected to strengthen investor confidence ahead of any future public market ambitions. Generating stable, long-term infrastructure revenue may help offset concerns about the profitability and adoption trajectory of Grok and other consumer-facing AI products.