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Alphabet, with its $3 trillion valuation, is not merely a rival but a quiet counterpoint to Nvidia’s flamboyance. Its assets-YouTube’s endless scroll of human expression, Google Search’s labyrinthine dominion-generate growth with the patience of a river carving stone. Yet its true power lies in what remains unseen: the algorithmic alchemy of Waymo’s robotaxis, now ferrying millions through cities like Los Angeles and San Francisco; the Veo 3 model, which transforms YouTube’s chaos into AI videos indistinguishable from reality. These are not mere products but the seeds of a future where Alphabet’s value is measured not in multiples but in inevitability.

But in the unblinking eye of the investing public, ever captivated by these heady promises, the likes of IonQ and D-Wave Quantum have seen their stock prices rise with a meteoric, almost absurd velocity. A stunning belief, no doubt-one that presupposes a speedier transformation of these theoretical breakthroughs into marketable products than even the most starry-eyed physicist might entertain. Alas, we find ourselves in the paradoxical position of watching these fledgling quantum enterprises thrive not through the rigor of their developments, but rather through the sheer weight of expectation, much like a magician’s illusion built upon misdirection.

Yet in the twilight of AI’s training epoch, where titanic GPUs devour watts like ambrosia, the humbler realm of inference beckons-a purgatory of diminished ambition but pragmatic utility. Here, where the infernal heat of matrix multiplications meets the frugality of edge deployments, Intel discerns its last crusade. Model training demands Promethean theft from the fire of computational gods; inference merely requires the tending of embers, the quiet labor of scribes copying neural weights upon the vellum of everyday devices.

And now, as the calendar turns yet another page, let us glance back, not with the excitement of those who delight in profits, but with the sober contemplation of those who wish to examine the truth.

The year opened with AI zealots chanting “progress!” as if it were a liturgy. But when President Trump’s tariff theatrics struck Wall Street like a farcical opera, the crowd’s faith wavered. How quaintly human: to flee the storm only to return when the sun reappears. Since April’s nadir, the index has vaulted 20%-a phoenix-like resurgence that proves markets, like fashion, thrive on reinvention.

Lilly’s tirzepatide is the current king of GLP-1/GIP agonists, and their triple agonist, Retatrutide, is the crown prince. It’s all very impressive, like watching a chess grandmaster set up a checkmate. But here’s the thing: Vikings didn’t just pillage; they innovated. Their VK2735 is a dual GLP-1/GIP beast, and they’re already toying with a quadruple agonist-GLP-1, GIP, Amylin, and Calcitonin. It’s the biotech equivalent of building a four-player co-op game where everyone wins… or everyone crashes. (And yes, I’m aware I just compared drug development to a video game. Don’t judge me.)

However, the trajectory of such rapid growth, though striking, cannot continue unchecked. In the next five years, two other companies stand poised to eclipse Palantir in market value, albeit through very different routes. One is a retail giant, ready to capitalize on a rebound in housing and infrastructure. The other is a semiconductor innovator, vying to disrupt the AI hardware market.