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In 1956 a Dartmouth University Workshop coined the term Artificial Intelligence (AI) as it explored machine learning and thinking computers. This endeavor coincided with the massive evolution of computers from vacuum tubes and transistors to integrated circuits (ICs) in the late 1950s and microprocessors in the 1960s. While ICs have rapidly enhanced computing speed, power, and deductive reasoning, the modern concept of AI grew slowly, despite its sentient portrayal in movies. However, over the past decade, IC power and the affordability of cloud computing ushered in a parabolic explosion of AI projects and graphics processing units (GPUs). Nvidia’s GPUs comprise 95% of the market for machine learning and massively accelerated neural network processing. Data Centers and GPUs using Nvidia appear to have reached an inflection point this year with a rush of orders from start-ups and large enterprises. Enterprise demand is dominated by rapidly growing mega-cap tech companies such as Amazon, Apple, Alphabet, Meta, Microsoft, AMD, and Adobe. These major customers have strong growth trends and deep pockets accounting for over $10 trillion in market value. This new stage of the AI revolution will generate intense competition as the AI marketplace grows from $200 billion today to an estimated $1.5 trillion by the end of the decade. While the sudden hype requires a caution label near term, Nvidia is in the pole position of dominance as Tesla was for Electric Vehicles (EVs) 10 years ago. 

Just seven months ago Nvidia’s market value was not in the top 20 of public companies. Today it’s number 5 after appreciating 250% since last October to hit the $1 trillion valuation club. After single-handedly propelling the rest of the mega-tech stocks higher last week due to Nvidia forecast revisions, it may appear too late for investors to add these stocks to the portfolio. However, the surprise jump in forward expectations has created pent up demand for Nvidia stock and its brethren upon any pullback towards the breakout gap of May 24th/25th. Unless one assumes AI is a flash in the pan, it’s unlikely Nvidia stock can fall back to its 305-318 breakout as we see investors increasingly snapping up shares in the 340 to 380 zone. Nvidia will continue to lead tech up and down over the short term as buyers keep values above $300/share where the AI gold rush began. With Nvidia’s 2024 guidance jumping 50% on a 50 multiple, the new consensus is in the $450 to 500 range. We have been expecting prices of tech and the general stock market to peak in the short term this week with a modest mid-June swoon that could test the mid $300’s for Nvidia before further seasonal gains into July.

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The caveat for the newly emerging Bull investors is liquidity. While stocks can ignore contracting monetary liquidity for months, it warrants some vigilance as the Fed continues to drain $120 billion from the banking system each month combined with a pent-up supply of Treasury debt issuance it must now dump onto the market since the Debt Ceiling was passed last week. This could add some upward pressure to the long end of the Treasury yield curve, even as short-term rates ease.

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Our outline for the stock market continues to track well despite the May bifurcation of mega tech outperformance versus the rest of the universe. Nvidia carried the market last week and Apple’s product announcement is adding to the frenzy today. All the mega-tech companies have a long runway of growth ahead, but hype is the major catalyst short term. Overly optimistic Call option buying and Advance-Decline issue breadth divergence should cap the SP in the low to mid 4300s in June, but the trend remains higher. Our forecast was for a June climax this week followed by a modest correction into mid-to-late June before one more rally phase into July where portfolio cash positions should be increased. The June – August peak will likely mark the end of this leg of the Bull market until much later in the year as consensus Q4 earnings forecasts get revised lower on worries over falling inflation and softer employment data.

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