I/O Fund

As of Q3, Anthropic said it had more than 11,900 customers with TTM revenue of >$100K, up nearly 8X from 1,500 at the end of 2025 and just 20 at the end of 2023. $NVDA $MSFT $GOOG $AMZN

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Our firm’s back of the napkin math shows that Nvidia’s $NVDA ACIE segment could potentially overtake hyperscalers in two to six quarters. This is an important development as it results in Nvidia’s revenue being more resilient as hyperscalers shift capex toward designing and deploying their own custom chips. ACIE revenue grew faster than hyperscaler revenue last quarter at 138.5% compared to 101.2%, respectively. After reclassifying one company, the QoQ growth for ACIE was 25% compared to hyperscalers at 13%. Depending on how you model the two-quarter lumpiness, ACIE can conservatively overtake hyperscalers in 5-6 quarters at a 14% QoQ growth rate versus 10% QoQ growth rate for hyperscalers, or as soon as 2 quarters if the Q2 pace continues. In early September, Dell $DELL was in agreement with Nvidia’s results, stating that enterprises and neoclouds could contribute half of AI data center capacity growth through 2030, creating a $1 trillion total addressable market (TAM): “We’re expecting AI to be 75% of all data center demand by 2030, adding 200 gigawatts of power over that same time frame. And half of that, we believe, is right in our sweet spot with our customers, the Neoclouds, sovereigns and enterprises. And if you look at that math, we think the opportunity in front of us is more than $1 trillion over that time frame.” Although it may seem counterintuitive for Nvidia, Dell or Super Micro $SMCI to emphasize enterprise and neocloud customers over the hyperscalers and their $1 trillion capex next year, the reason is simple. Unlike the hyperscalers, these customers do not have those budgets to splurge tens of billions on custom chips. Instead, demand is more concentrated in ready-to-deploy servers that can immediately be brought online to generate revenue for immediate ROI, which Dell and Super Micro can do in as little as six hours to one day.

HBM has been one of the fastest growing markets within the AI buildout, with the market forecast to hit $106 billion in 2027, up 26X from just $4 billion in 2023, per Bain. $NVDA $AMD $MU $SKHY

AI’s “safe” bets like $NVDA and Big Tech are underperforming the $QQQ YTD. Meanwhile, some of 2026’s biggest triple-digit winners are hiding deeper in the AI stack. My Q4 Top 20 AI Stocks report, released last week, breaks down the lesser-known companies leading the charge. Link in bio.

Since bond yields bottomed in 2020, the U.S. has not been alone: 10-year yields in the U.K. and France have hit multi-decade highs, and Germany's has reached its highest level since 2008. io-fund.com/broad-market/bon…

Meta $META reported Q3 capex of $34.9 billion, up 80% YoY. Full-year capex was raised to $135-145 billion from $130-145 billion previously, implying Q4 capex of more than $54 billion at the midpoint. $NVDA $AMD $AVGO

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Google’s greatest competitive advantage may not be building a faster chip than $NVDA but building AI infrastructure at a lower cost. After years of designing accelerators around its own AI workloads, $GOOG is bringing that advantage to outside customers. Selling TPUs opens a massive new revenue opportunity, with analyst forecasts ranging from $100 billion to $250 billion by 2028. At the high end, that would rival what took Google Search decades to achieve. The catch? HBM shortages and customer financing could limit how quickly this opportunity translates into cash flow. Read our latest analysis here.⬇️ io-fund.com/ai-stocks/google…

Since 1880, the average secular bull market lasts 11.2 years, with an average gain of 675%. Compare this to the current bull market, going on 17.4 years old and up 1,073%, as of September 2026. io-fund.com/broad-market/the… $SPY $QQQ

We believe this bull market has considerably more room to run. However, before the next leg higher begins, we expect a correction that will shake many investors out of the trade – and the main AI proxy, $SMH, appears to be confirming this view. io-fund.com/broad-market/the… $SPY $QQQ

Nvidia’s $NVDA developer base has reached 11 million, more than tripling from 3 million in 2021. $AMD

The deteriorating macro backdrop, from bonds to inflation, could create a meaningful headwind for stocks, but that doesn’t necessarily mean the secular bull market is over. Below, we map out the headwinds at play, and what key factor could keep the bull market on track after a correction. io-fund.com/broad-market/bon… $SPY $QQQ

When the leading supplier producing 50% of global HBM signs an agreement with the world’s leading consumer that could account for 37% of HBM capacity in 2027, the queue for everyone else waiting to access memory gets longer. io-fund.com/ai-stocks/nvidia… $SKHY $MU $NVDA

What stocks could win big from the shift to AI inference? I break down my thoughts in the clip below. @cvpayne

Hyperscalers' bonds to fuel capex offer institutional investors an attractive 100-180+ basis point yield premium over Treasuries, meaning marginal balance sheet capacity is being funneled away from government debt auctions. io-fund.com/broad-market/ai-… $MSFT $AMZN $GOOG $ORCL

“Compute is worthless if you can’t power it.” With @cvpayne, I break down the I/O Fund’s early call on Bloom $BE at $16—and another company well positioned to meet the scale of power AI will require over the next decade.

In 2019 I said $NVDA would become the world's most valuable company. In 2021, that it would surpass $AAPL. In July 2024, I said AMD's $AMD returns would outpace Nvidia's over five years. So far, so good. This week, I cover why the next chapter could be AMD’s biggest. Link in bio.

AMD’s battle with Nvidia on GPUs looks surprisingly similar to $INTC, but there’s one major difference – AMD does not need to overtake $NVDA to win. Below, I map out why AMD’s $AMD next-generation GPU roadmap could continue to support higher returns than Nvidia through 2028. io-fund.com/ai-stocks/amd-st…

Model complexity and the KV cache are two primary drivers for memory, especially for inference requiring increasingly large context windows. Context windows for OpenAI’s leading models have risen 230-260X in three years to 1.05M tokens, while Meta’s Llama 4 Scout is 10X higher at 10M. $MSFT $AMZN $META $GOOG $MU io-fund.com/ai-stocks/micron…