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On Nvidia's current role in the AI boom

Nvidia is the backbone of the AI revolution. It invented the GPUs that power virtually every major AI system on the planet.

And has evolved into something much more than a chip company: a full-stack, rack-scale AI systems company. And its CUDA software is so deeply embedded across every cloud, AI lab, and frontier model that it’s become the de facto AI infrastructure operating system.

Put simply, you can’t build the future of AI without Nvidia.

Where it stands today

In its most recent quarter (fiscal Q1 2027, reported May 20), Nvidia reported $81.6 billion in revenue, up 85.2% from a year earlier. Its data center business—essentially its AI business—grew about 92% to $75 billion. Free cash flow hit a record $49 billion, and gross profit margin held steady right around 75%.

Meanwhile, management guided next quarter to about $91 billion in revenue. As CEO Jensen Huang put it, demand has “gone parabolic.”

The growth engine is Blackwell, Nvidia’s current generation of AI systems, which is ramping faster than any product in the company’s history.

Nvidia also deepened a major partnership with Anthropic and now runs essentially every frontier AI model—OpenAI’s, Anthropic’s, Google’s, xAI’s (SpaceX), and more. And it’s rewarding shareholders, returning a record $20 billion this quarter while raising its dividend.

The long-term story is stronger than ever.

Where it’s going (and why I'm still bullish)

We’re still early in what Nvidia’s founder and CEO Jensen Huang describes as AI’s third major wave: agentic AI.

First came generative AI (chatbots that answer questions). Then came reasoning AI (systems that think a problem through). Now we’re in the agentic AI era, where “agents” do multi-step work on their own like a tireless digital employee.

Each rung up this ladder demands dramatically more computing power, and Nvidia is the biggest beneficiary every time.

Behind agentic AI sits an even bigger wave: physical AI, where things like autonomous drones, vehicles, and robots operate in the real world.

Management sees at least a $1 trillion revenue opportunity from its current and next-generation systems (Blackwell and Vera Rubin) from 2025 through 2027.

Nvidia’s rack-scale platforms deliver the industry’s lowest cost per token and highest throughput. And its next generation architecture, Vera Rubin, begins shipping in the second half of this year.

Meanwhile, Nvidia’s new Vera CPU—purpose-built for agentic workloads—opens a fresh $200 billion market the company has never tapped before.

Bottom line: I continue to believe Nvidia is on track to become a $10 trillion company before 2030, possibly as early as 2028. The stock will have pullbacks along the way—sometimes sharp ones—but I view them as buying opportunities.

For more analysis on growth stocks, check out my free investing letter here .

Rambus ranks #6 in my Memory Stock Power Rankings

Think of an AI system as a kitchen. The processor (GPU, TPU, XPU, etc.) is the chef. Memory is the pantry.

If the pantry is across the parking lot, the chef spends the day jogging back and forth for ingredients. It doesn’t matter how fast she can chop and cook; the pantry is a major bottleneck.

That’s basically what’s happening inside AI data centers. $50,000 AI chips often sit idle, eating electricity, time, and cash, waiting for the pantry to feed them data.

Rambus $RMBS is like a crew that comes in and installs features that allow ingredients (data) to get from the pantry to the chef faster and more efficiently.

The company does this through two main businesses.

First, it designs and sells physical “helper” chips—tiny, specialized semiconductors that sit on memory modules and help data move faster and more reliably.

Memory modules are essentially plug-and-play packages used in computers and data center servers. They’re basically a circuit board with DRAM chips (from companies like Micron and SK Hynix) and supporting chips (like Rambus’s) that make them work and boost their performance.

Rambus is one of just three companies in the world that makes the “memory interface chipset” servers need for fast and efficient high capacity memory. (Montage Technology and Renesas are the other two.)

Second, Rambus licenses its technology blueprints (called intellectual property or IP) to other companies including Nvidia, Micron, SK Hynix, Samsung, Intel, Broadcom, and Qualcomm—collecting royalties when these companies use its inventions in their products.

Rambus basically sells chips and IP that serve as the connective tissue that makes fast memory work.

How Rambus fits the AI story

Several ways. I’ll hit on two.

For example, in Part II of this series I explained how the base die—the control chip at the bottom of the memory stack—moved from a DRAM process to a logic process with HBM4, and that this turns the high bandwidth memory needed for AI into custom silicon.

Rambus built its next generation HBM controllers (and its HBM controller IP) explicitly for this custom-HBM world.

A second way: Most folks think about AI as GPUs. But as inference and agentic AI workloads scale, the systems around the GPUs get busier—orchestration, data management, real-time execution, moving work between steps. That’s CPU work.

More CPUs means more memory modules, and each module comes with a Rambus chipset.

Meanwhile, the upgrades to the new module formats, MRDIMM and SOCAMM2, which I talked about in Part I , means more Rambus content per module.

Why Rambus ranks #6

Rambus scores very high on strategic positioning and management execution. It also has a durable moat. But it scores low on growth because of the nature of what it sells.

What I mean is that Rambus is a unit- or volume-driven business. It makes more money when more memory ships. It doesn’t really benefit from the pricing supercycle that defines this sector right now.

Plus, the same shortage that’s allowing the memory makers like Micron and SK Hynix to charge insane prices is constraining total unit volumes of the conventional modules that use Rambus’s interface chips.

I should also note that Rambus and the other two companies I mentioned earlier that make memory interface chipsets (Montage Technology and Renesas) are currently the subject of a DOJ investigation for collusion on pricing. So the limited pricing power we just talked about could become even more limited.

See my other names in my rankings here .

Uber Cut 3,300 Jobs This Morning. That Is Why I Own the Stock:Headcount is going back to 2021 levels while revenue has nearly tripled. This is what disciplined operators look like, and at 16x next year's GAAP earnings, I am staying with my Buy.

$UBER announced this morning it is cutting about 3,300 jobs, roughly 10% of the company, taking headcount back to where it stood in 2021. Here is the part that matters: since 2021, revenue has nearly tripled and GAAP operating margins swung from minus 22% to almost positive 11%. This is the discipline that made Uber my favorite Buy of the mobility stocks, and at $76.49, about 16.5x 2027 GAAP earnings, I am staying put.

1. The market read this morning's news correctly.

This Wednesday morning, first reported by Bloomberg, Uber said it is cutting about 3,300 roles, roughly 10% of the company. The highlights:

• 1)Manager ranks shrink by 20%, with some managers moving back to individual contributor work.
• 2)The number of employees sitting seven or more layers from the CEO drops by 20%, and "micro-teams" of one or two people get cut nearly in half.
• 3)The three separate delivery operations teams, covering restaurants, retail, and direct, get combined into single teams at the global, regional, and country levels.

The stock is up about 2% on the news. I think investors are always more forgiving of layoffs that appear to help fund growth vs those that appear to come from a place of weakness.

2. Doing more with less is the entire Uber story.

Longtime readers will know that I am not a day trader. I love taking the long view to help give me more perspective on the present. Well, over the last seven years, Uber has been a master at 'trying to make a dollar out of 15 cents' as the saying goes. Somehow they've kept headcount relatively FLAT. $UBER went from 26,900 employees at year-end 2019, to 34,000 by YE 2025, and now down to roughly 30,000 after these cuts.

3. The proof is already in the margins.

When I say $UBER is run by skilled operators, this is what I mean.Look at this chart below I made that shows the big swing in GAAP operating margin from losses to profits. Pre-covid EBIT margins were -60% and swung to almost +11% in just 6 years. I am old enough to remember when there was a legit debate on whether or not Uber would stop burning cash.

4. With Uber trading near $76, this discipline is still on sale.

Using the consensus GAAP estimates from my TMT Multiple Tracker, Uber at $76.49 trades at 23.2x 2026 earnings of $3.29 and just 16.5x 2027 earnings of $4.64.

Read the full article on Accrued Interest.

https://www.accruedint.com/p/uber-layoffs-3300-jobs-buy

Why GE Stock Looks Priced to Perfection

With GE (GE) still changing hands at a rather high valuation and facing significant, longer-term threats to its main business from the situation in the Mideast, the shares look priced to perfection at this point. Consequently, I do not believe that the name is especially attractive for investors.

In a previous column , published last October, I noted that the company’s forward price-earnings ratio, which was then 44, was rather elevated, especially because analysts on average expected the firm’s “revenue growth to slow markedly to 10.8% (in 2026) from 15.7% in 2025 “

Since that piece was published, the shares rose about 8%, significantly underperforming the S&P 500’s increase of 13.5% during the same time period.

Boding well for the name’s outlook, its forward P/E ratio has dropped significantly to 36,  and analysts on average now expect its sales to climb 18.8% this year.

But on the other hand, GE is facing significant potential threats from the situation in the Middle East, and analysts’ mean estimate calls for its top-line growth to fall to 10.7% in 2027.

This time, because of the hostilities between America and Israel on the one hand and Iran on the other, their call for next year may very well turn out to be correct.

The Iran Conflict Could Significantly Slow GE’s Growth

GE obtains about 75% of its revenue from commercial aviation entities, and much of these funds come from maintaining and repairing airplane engines.

But after jet fuel prices climbed a great deal due to the conflict between America and Israel on the one hand and Iran on the other, airlines are flying less as their ticket prices increase, lowering demand for flight.

Consequently, they are likely to need less maintenance and repairs over the longer term.

Showing that airlines are indeed curtailing their flying,. GE in April reduced its forecast for the increase in the number of departures of planes using its engines in 2026 to around 0%-3%. Previously, the company had expected an increase of roughly 5%.

If the conflict heats up again following the U.S. and Israeli elections, scheduled to take place in late October and early November, respectively, the price of jet fuel could surge again, causing airlines to further cut back their flying schedules and lowering GE’s service and maintenance revenue.

GE’s Valuation Is Not Low

The shares are not cheap, as they are changing hands at a forward price-to-earnings ratio of nearly 37 times.

For more information, please view my previous column .

I do not currently have a position in GE.

The Benefits of the CapEx Spent by the Hyperscalers Will Be Seen in 2030 (And short-sighted Mr. Market is clueless)

In my post back on August 17, "The Great AI Rotation: Looking Past the Infrastructure Hype to Buy What Wall Street Discards," we drew a hard line: we weren't talking about buying just any software blindly. You have to be surgical. The market has been indiscriminately thrashing the whole sector, but only elite platforms with locked-down corporate data, strict regulatory moats, and mission-critical workflows are worth touching. The generic wrappers and basic tools? They're heading straight for extinction.

While software has taken that brutal beating, the market treats the tech hyperscalers a bit differently—though it's still throwing a daily tantrum over their physical CapEx. But if you step back and look at the actual data and charts, these giants represent a massive, compounding multi-year opportunity. Provided, of course, you actually have the patience to look out 4 to 5 years.

To be fair, institutional research desks like Goldman Sachs and J.P. Morgan already map out the long-term math pointing straight toward 2030. But short-sighted Mr. Market? Totally clueless. He swings wildly between blind optimism and sheer panic over temporary cash burn every single quarter, completely missing the forest for the trees.

To see why this disconnect is basically a generational mispricing, we just need to look at what the latest data is telling us.

Investing Hugely Now to Reap the Benefits Tomorrow

Just look at how the physical infrastructure race has exploded. Annual capital expenditures for the major AI hyperscalers (Microsoft $MSFT , Alphabet $GOOG , Amazon $AMZN , Meta $META , and Oracle $ORCL ) went from a modest $71 billion back in 2019 to a staggering $416 billion in 2025—and they're projected to hit an incredible $904 billion by 2028.

If you examine the J.P. Morgan data on the right, the market is misinterpreting what’s happening underneath the hood. Look closely at the Operating Cash Flow(that blue line): it represents pure cash generated by core operations, completely independent of CapEx. Far from collapsing, operating cash flows are locked in a steady, secular uptrend.

This tells us something vital: the massive money poured in so far is already generating organic cash. The catch is that these returns still look tiny compared to the tidal wave of cash that's going to hit once this heavy building phase finally wraps up. Naturally, though, Mr. Market stays glued to the near-term CapEx spike, treating the resulting cash squeeze as a permanent flaw instead of the messy birth pangs of a brand-new tech era.

Navigating the FCF Valley: Why 2026–2027 Is Just a Pit Stop

Because of that aggressive wave of spending, Free Cash Flow (simply Operating Cash Flow minus CapEx) is heading into negative territory for the hyperscalers through 2026 and 2027.

As Exhibit 9 from Goldman Sachs shows, consensus models map out a brutal cash trough over the next couple of years—hitting a combined negative low before starting a slow recovery in 2028, and then breaking out explosively toward 2029 and 2030.

Mr. Market takes one look at this temporary cash valley and loses his mind, acting like it's the end of the world. But real long-term investors know that building digital infrastructure on this scale takes heavy upfront capital. Every dollar burned today is essentially buying a monopoly on the computing power of the next decade.

Will the CapEx Buildout Last Forever? The Highway Analogy and the 2030 Threshold

A huge blind spot for retail investors chasing hardware and memory suppliers (like SanDisk $SNDK or Micron $MU ) is assuming this frantic pace of spending will just keep compounding upward into infinity.

To see why that's a mathematical impossibility, think of it like building a "national highway" network:

• The Heavy Construction Phase (Now through 2027):Right now, the hyperscalers are in the brutal ground-breaking phase. Buying land, flattening terrain, pouring heavy asphalt, and hooking up massive electrical grids. This is why CapEx is surging toward $904 billion and why Free Cash Flow is plunging into a valley.
• The Maintenance Phase (Toward 2030):Once those digital highways are built and running, the nature of the game changes completely. That massive expansion CapEx drops off, turning into a much lower, predictable maintenance CapEx—patching up software potholes, minor hardware upgrades, and routine upkeep.

If retail investors honestly think hyperscalers are going to keep building new "highways" at this insane pace forever, they're betting that these tech giants are fine with permanently negative or depressed cash flows. That's a total fantasy in a rational market. No company burns the majority of its operating cash on infrastructure indefinitely without destroying value.

The Institutional Ultimatum: Escaping the Inertial Trap

Skeptics often raise a very valid warning: Are Hyperscalers' CEOs simply falling into a herd mentality—spending heavily purely because their competitors are doing it, trapped in an endless cycle of corporate FOMO?

If this buildout were driven merely by blind inertial mimicry, institutional funds would flee en masse. Wall Street’s thesis, as mapped out by Goldman Sachs, is built on a strict timeline: the 2026–2027 FCF valley is an accepted pit stop, but it has an expiration date.Institutional investors are underwriting this cycle under the strict assumption that infrastructure spending will normalize. If a hyperscaler tries to drag this heavy cash burn into a third or fourth consecutive year without a structural rebound in Free Cash Flow, the market will brutally penalize the stock.

The hyperscaler's CEOs themselves defend their current sprints by pointing to severe, real-world capacity constraints—arguing that enterprise demand for AI compute continues to outstrip supply. Yet, structurally, that frantic pace cannot be permanent.

Two Possible Scenarios Toward 2030

How do we actually reach those booming FCF numbers projected by Goldman Sachs? It really comes down to two potential paths:

1. The Normalization Scenario:The frantic buildout hits a natural ceiling, CapEx drops back to normal maintenance levels, and Operating Cash Flow keeps climbing. The result? A hyper-parabolic FCF explosion—a massive wall of free cash.
2. The Permanent Buildout Scenario:AI demand proves so relentlessly insatiable that hyperscalers keep CapEx at record highs right through the decade. Even here, OCF surges, but the resulting FCF stays much tighter because the heavy spending baseline keeps soaking up a lot of the cash.

Which Scenario Wins, and Why It Explains Berkshire’s Bet on Alphabet

While both paths end up recovering, the first scenario—normalization paired with elite capital efficiency—is the ultimate holy grail. And that exact distinction unlocks the real reason behind Berkshire Hathaway's $BRK-A $BRK-B massive stake in Alphabet.

In fact, I seriously doubt Buffett would have poured billions into Alphabet — making it the fourth most important position in Berkshire's stock portfolio — if he expected years upon years of permanently elevated, sky-high CapEx. Even though Operating Cash Flow would still surge in that second scenario, the resulting Free Cash Flow would be significantly lower and far more constrained than in a world where CapEx growth cools off and settles back down into predictable maintenance levels.

Buffett understands that infrastructure has a terminal construction phase: there comes a point where the highway is fully built, and Alphabet’s sole job shifts to collecting the tolls while spending relatively little to keep the engines running.

As I broke down back on August 1 ( "Berkshire Hathaway’s Mystery: Who Made the Call on Alphabet—Buffett or Greg Abel?" ), Warren Buffett gets this dynamic better than anyone on Wall Street.

When Berkshire started aggressively building its position in Alphabet, the short-term crowd was scratching their heads, assuming Buffett would steer clear of a company pouring billions into a heavy CapEx cycle. But Buffett doesn't look at next quarter's EPS or sweat temporary cash outflows. He looks at Return on Invested Capital (ROIC)and long-term economic moats.

Buffett knows that unlike capital-draining hardware setups that need endless cash just to stay in place, Alphabet has the elite capital efficiency to glide smoothly through this infrastructure phase. When the CapEx cycle normalizes and those FCF floodgates blow wide open by 2030, the folks who bought the dip while Mr. Market panicked are going to reap the rewards.

Uncovering these structural dynamics requires looking far beyond the generalized noise of conventional platforms. While the rigor of my analysis can be reviewed on my Yahoo Finance Community profile, Quality Investments substack offers an even higher level of depth for investors focused on the long-term drivers of a company—drivers that are frequently overlooked by short-term, simplistic analysis. This is where the true edge of a sophisticated investor lies. Quality Investments is not a platform for casual financial entertainment; it is a serious private research space built for long-term investors, featuring institutional-grade theses, complete valuation models, and portfolio tracking.

Quality Investments | Mario Silva Arteta | Substack

Disclaimer: This post is for informational and educational purposes only and does not constitute financial, investment, or legal advice. The opinions expressed above are solely those of the author based on publicly available data. Always conduct your own independent due diligence.