Nicholas Mitsakos

Investor, Entrepreneur, Writer, and Lecturer

Books
Articles

Articles

Current research and analysis on topics ranging from innovation, disruption, and opportunity, as well as hype, irrationality, and absurdity.

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Blog

Blog

Commentary about recent technological, market, economic, and geopolitical events

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Lectures

Lectures

Presentations about developments in technology, life sciences, digital assets, and other transformational businesses, as well as market, economic, and geopolitical developments

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Doomsday, AI, and a Response to Dario Amodei

Advanced Technology, Article, Artificial Intelligence, biotechnology, Class Material, Transformative Businesses, , , , , , ,

Must the AI frontier slow down? Perhaps. That’s not the right question. We should ask what, precisely, must slow; what risk that restraint would reduce; who could enforce it; and what would happen if careful firms paused while less careful actors did not.
Dario Amodei has published one of the most consequential essays yet written by a frontier AI company leader. He is candid, and he is reconsidering an earlier, more benign, position. But his argument is flawed: a model’s capability is not an application or an outcome.
He says the latest models can offer dramatically good or dramatically bad outcomes. On the one hand, AI may cure most major diseases within five to ten years. But it may also become an agent swarm capable of seizing the internet within six to twelve months.
Both are wrong. These extremes are oversimplifications and can undermine both AI’s benefits in many areas and our ability to regulate and monitor it appropriately. Simply saying “boo” and hoping everyone else is frightened isn’t an effective, comprehensive strategy for addressing a serious issue.
Any good or bad from an AI model only appears when that model is part of a system that enters the world through software, capital, organizations, machines, biological systems, and public institutions. Understanding this lets us unleash AI’s potential for good while also building the systems and processes to protect society.

The Total Perspective Vortex: Artificial Intelligence and Real-World Systems

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We are told that we have entered an unprecedented era. Perhaps. The more useful response is to step back. Perspective does not diminish technological achievement. It allows us to distinguish engineering from magic, capability from consequence, and a genuine inflection point from a fashionable narrative. This book is about that distinction.

Artificial intelligence is a powerful tool that can make tools. But capability is not destiny. Its value and its danger emerge only when it enters real systems: energy, software, capital, organizations, machines, biology, and political institutions.

AI and Human Intelligence

Advanced Technology, Article, Artificial Intelligence, Book Chapter, Software, Transformative Businesses, , , , , , ,

The future of AI will be systems that enter an environment, build memories, recognize gaps, ask questions, conduct experiments, model consequences, learn from people, and revise themselves under controlled conditions.
AI will become an experiential learning tool. This transition would reduce dependence on internet-scale data, redistribute competitive advantage, accelerate robotics and autonomous science, strengthen specialized and sovereign AI, and create entirely new governance challenges.
The next great advance in artificial intelligence may not be a machine trained on everything. It may be a machine that knows how to learn what matters.

AI is Not a Magic Bullet

Advanced Technology, Article, Artificial Intelligence, biotechnology, Book Chapter, Life Sciences, Science, , , , , ,

AI cures disease only if the cures already are within a set we have measured, waiting for a better approach. One problem: they do not. Most of human biology has never been observed with detail and understanding sufficient to target a therapy. No amount of inference recovers data that was never collected. The need for AI in life sciences and drug discovery is indisputable. Of roughly ten thousand known human diseases, the large majority have no approved therapy at all; among rare diseases, the figure approaches ninety-five percent. Most approved drugs slow a disease rather than stop it. For the bulk of human illness, medicine offers management or nothing. Humans are systems, and the hardest diseases are within human systems and unsolved. The constraint is not intelligence. It is understanding the system.

The New Fire: Artificial Intelligence, Geopolitics, and a Transformed World

Article, Artificial Intelligence, biotechnology, Book, Energy, geopolitics, globalization, Hard Tech, Lectures, Physical Intelligence, Public Policy, robotics, Science, space, Transformative Businesses, , , , , , , , , ,

Technological, geopolitical, and capital transformation are interconnected, with unprecedented impacts on a globally connected, directly entangled economic and geopolitical world. Choices are simultaneously investment decisions, national security decisions, and civilizational bets on which technological architecture will define the next century.

Understanding them requires insightful economic, strategic, and institutional thinking. More than ever, it requires intellectual courage and patience with complexity.

The Real World and AI

Article, Artificial Intelligence, Book Chapter, Lectures, , , ,

AI and real-world visual understanding remain unsolved. Machines can recognize a face, caption a photograph, describe a scene, and outperform radiologists on narrow diagnostic tasks. So, if machines can see what we see, they must be doing what we do. They don’t. Nature does not produce straight lines, perfect circles, or right angles. AI lacks comprehensive human visual reasoning.

The Computable Molecule

Advanced Technology, Article, Artificial Intelligence, biotechnology, Book Chapter, Class Material, Science, , , ,

Artificial intelligence is no longer a tool that the life sciences industry is adopting. It is a force that is relocating where value is created and who captures it. Three costs are collapsing at once: drug discovery, company independence, and the ability to reach the patient. Each of these costs was, for forty years, a moat protecting the incumbents who could afford to pay it. In addition, the capacity to discover and manufacture medicine has become a strategic infrastructure in the same category as energy, semiconductors, and compute. The molecule has become computable. The architecture of value creation in life sciences has changed.

The AI Molecule

Advanced Technology, Article, Artificial Intelligence, biotechnology, Life Sciences, Science, Software, Transformative Businesses, , , , , , , , ,

Artificial intelligence is reducing the time and cost required to discover new drug candidates. New forms of late-stage capital are allowing better companies to stay independent longer. Direct-to-patient distribution is weakening Pharma’s control of the commercial channel. Together, these changes alter the architecture of biotechnology. The molecule is being separated from the old machine that used to deliver it. This is a structural change in how drugs are discovered, financed, developed, negotiated, and delivered. Biotech companies will build discovery systems, develop clinical evidence, control proprietary data, preserve financing options, and reach patients more directly.

The Next Human Crisis

Article, Artificial Intelligence, Book Chapter, China, Class Material, Energy, geopolitics, globalization, Lectures, Life Sciences, Prediction, Public Policy, Science, Transformative Businesses, , , , , , ,

Albert Camus’s warning from nearly 80 years ago, that humanity is subordinate to abstraction, people are replaced by calculations, and the willingness to accept suffering as an administrative variable persists. We have industrialized the human crisis. We are at an inflection point where the consequences of our choices, both good and bad, will arrive faster, hit harder, and spread more widely than any prior moment in history. We have the proven capacity to recover from previous crisis. The question is whether the next crises potentially makes recovery impossible.

The Application Layer

Advanced Technology, Article, Class Material, Energy, Life Sciences, Physical Intelligence, robotics, Software, Transformative Businesses, , , , , , , , , , , , , ,

Artificial intelligence is a stack: energy, silicon, cloud, models, and applications. Each has its own economics, competitive dynamics, and challenges. Mistaking one layer for the whole industry causes confusion, misrepresentation, bad decisions, and misguided capital allocations. The infrastructure builders enable the platform; the application builders capture the value. The question is now, what value does all this deliver? Energy, silicon, cloud, and models only serve to deliver that product. There is a robust argument that we are at the beginning of an unprecedented value-creation curve. Built on the infrastructure and services provided by the other layers of the stack, the AI application layer will be globally transformative and disruptive. The constraints are imagination, execution, and the willingness to rebuild how work is done.