AI Economic Pit Is An Illusion

The Great Convergence And Scientific Breakthroughs

The Great Convergence

While headlines track the billions invested in artificial intelligence, the real story lies not in quarterly earnings but in something the public discourse often overlooks: the profound shifts that AI and Machine Learning are causing in fundamental science. These exciting discoveries, emerging across all fields, will forge a new paradigm for life on earth.

We stand at the edge of a generational inflection. The coming twenty‑five years may reshape our understanding of life, mind, and matter as profoundly as any of the past great shifts. When Copernicus unsettled the heavens, Newton revealed hidden laws, and Einstein bent time, each moment widened the frame of reality. Today, propelled by artificial intelligence and quantum discovery, we sense another fracture.

What was once dismissed as speculation, machines that do science, cells programmed like software, consciousness measured and perhaps replicated, is now edging from possibility to probability. The question is no longer whether the old certainties will fracture, but how soon, and how profoundly.

This cluster of near-horizon advances, in fields once considered separate provinces, physics, biology, mathematics, computer science, cognitive science, are now edging toward one another, like tectonic plates. Their collision threatens to remake the continent of knowledge.

Fundamental

Artificial intelligence is the leading edge of this shift. What began as a statistical parlor trick, stochastic parrots, has become a general instrument of discovery. Rich Sutton, during his Turing Award acceptance speech, framed the underlying philosophy clearly:

“The main idea of reinforcement learning is that a machine might discover what to do on its own, without being told, from its own experience, by trial and error.”

AlphaFold embodied that ethos in 2020, stunning the biological community by predicting the 3D structures of proteins with uncanny accuracy and solving a 50-year-old grand challenge in biology. Its impact echoed the 1953 discovery of the DNA double helix, when Watson and Crick redefined biology by revealing its hidden architecture.

Over 2 million researchers in more than 190 countries use the AlphaFold Protein Structure Database and related tools to study protein structures, with this number continuing to grow as AlphaFold becomes an essential tool for accelerating scientific research, particularly in fields like drug development, vaccine development, and understanding diseases.

Some doctors and medical science researchers even claim “It’s unethical for doctors not to use AI. Soon it will be malpractice” not to use AI for certain diagnosis.

Today, AI systems are proposing mathematical conjectures, predicting protein interactions, designing drugs, and in some cases devising experiments beyond the imagination of their human handlers. “The end of theory” was once a glib New Yorker headline; today, it begins to feel literal. Science is building a machine that can do science. The implications are not only practical (shorter drug pipelines, new materials) but existential. When intelligence ceases to be a uniquely human monopoly, the Enlightenment’s quiet assumption, that reason is our species’ birthright, collapses.

Biology, meanwhile, is undergoing its own Copernican shift. For centuries, we imagined life as vital and ineffable, resistant to reduction. Now, researchers at MIT and Stanford program yeast cells to produce entirely new compounds, like biological factories. CRISPR edits genomes with precision, while synthetic biologists at the J. Craig Venter Institute assembled the first fully synthetic organism. And in the UK, chemists recently coaxed protocells from inanimate chemistry, hinting at plausible pathways for life’s origins. The frontier is not just medical but ontological: when life can be written, edited, and rebooted, the line between the animate and the synthetic grows thin. What does “nature” mean when it can be assembled from scratch?

Sentience

Cognitive science is converging with both. Competing theories of consciousness, Integrated Information Theory, Global Workspace, predictive processing, once floated in a fog of speculation. Now, armed with multimodal brain imaging and computational modeling, researchers are designing experiments that can adjudicate among them. At UCSF, paralyzed patients using brain-computer interfaces have learned to translate thought into text at 78/80 words per minute. Implants by Neuralink have led to humans being able to control a computer with their mind by intention alone.

Just as Broca’s discovery of speech centers in the 19th century reframed the brain as a mappable landscape rather than a black box, these modern breakthroughs suggest that consciousness itself may one day be localized, measured, perhaps even replicated. The moral map of the species will have to be redrawn. What rights belong to an entity whose consciousness can be demonstrated? What responsibilities to a machine that passes not only the Turing test but the test of suffering?

Mathematics is not immune. In 2021, mathematicians and AI researchers announced new conjectures in knot theory, discovered by machine learning systems trawling through the vast forests of algebraic data. Proof assistants like Lean are increasingly used to formalize entire areas of mathematics, ensuring correctness beyond human fallibility. The Langlands program, once considered the Mount Everest of modern mathematics, is now being chipped away by an odd alliance of human intuition and machine suggestion. The shift feels reminiscent of the 17th century, when Newton and Leibniz independently conjured calculus, an alien symbolic language that restructured science overnight. When an AI proposes a conjecture no human can parse, yet proves it within a formal system, is that mathematics, or something new, an alien branch of thought that merely shares our symbols?

Paradox

I use paradox here to mean that we observe something that defies common sense; not that we get different, contradictory answers using logic.

Physics remains the most resistant frontier, yet cracks are showing. In recent years, researchers working on the holographic principle have shown how spacetime geometry might emerge from patterns of quantum entanglement. The famous AdS/CFT correspondence, a mathematical duality between a gravity theory and a quantum field theory, suggests that our universe may be describable as a kind of hologram, reality projected from information encoded elsewhere. Experiments at Google’s quantum lab have begun to simulate such holographic wormholes on quantum computers. To watch this unfold is to recall Galileo’s telescope once more: where he saw mountains on the moon, today we glimpse geometry emerging from information. If true, then the cosmos is not a container but a process, a computation that begets geometry as a by-product. The distinction between physics and information science begins to dissolve.

Cambrian Explosion

Individually, these revolutions would be disorienting. Taken together, they suggest a deeper convergence: reality as fundamentally informational, computational, and emergent. Life, mind, and matter appear less like separate kingdoms than different scales of the same unfolding process.

The consequences are both pragmatic and existential. Pragmatically, we will harness these advances to extend lives, program matter, accelerate discovery, and perhaps tame energy. But existentially, we will confront a more unnerving prospect: that the categories we have relied on, human versus machine, natural versus artificial, physical versus mental, are artifacts of our ignorance. We are poised to glimpse a unified picture, but one that strips us of the privilege of centrality.

How should we spend our hours and years? The next twenty-five years will decide how we navigate this convergence. We can cling to old certainties and retreat into nostalgia, or we can live as transitional creatures, inhabiting the liminal space between ignorance and knowledge, biology and technology, matter and meaning.

We are on the cusp of a Cambrian explosion in scientific discovery; human ingenuity, amplified by AI, is the skeleton key. The task is not to own the truth but to steward it, to stay curious, provisional, and unafraid of what we might discover.

Stay curious

Colin

Note: I do believe that some VC investments are chasing illogical investments into so called AI ‘wrappers’ and there will be bankruptcies. I always advise users to choose the AI tools with major tech backers.

Image credit - Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems