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Home » Noubar Afeyan Delivers Notions Of Polyintelligence For AI In Life Science
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Noubar Afeyan Delivers Notions Of Polyintelligence For AI In Life Science

Press RoomBy Press Room14 January 20254 Mins Read
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Noubar Afeyan Delivers Notions Of Polyintelligence For AI In Life Science

We can really understand the world better through the application of AI.

All over the world, there’s a sense that we’re at the edge of a precipice, or perhaps more accurately, at the foot of a great ladder, ascending into new echelons of wisdom and capability.

I was reading a recent essay by Noubar Afeyan on the rise of a new kind of intelligence called ‘polyintelligence’ and the context of how we got here.

Afeyan is the founder of Flagship Pioneering who spoke at the MIT graduation last year. He has some very interesting things to say about the application of history to a new era.

The Polymath Principle

Near the beginning of his piece, Afeyan illustrates how Individuals and teams embrace a sort of “renaissance” approach to knowledge, using Leonardo da Vinci as an example.

“The term polymath is fitting for his unique intellect: someone with insatiable curiosity, a capacity to synthesize information from diverse areas, and a knack for connecting seemingly unrelated concepts to create groundbreaking ideas,” he writes. “Polymath seems to only suitably describe human intelligence, but if Leonardo teaches anything, it is that nature is intelligent, too, providing a wellspring of innovation and wisdom.”

Expounding on what it means to be a polymath, Afeyan remarks on the interconnection of different disciplines, and a unified approach to analysis, and then posits a sort of intersection between AI, human intelligence, and the intelligence of the natural world, or “nature‘s intelligence.”

History of AI and Human Intelligence

Midway through the essay, Afeyan goes back to the origins of knowledge – in fact, back to human striving to attain unified knowledge, in the book of Genesis, and then (much) later, the dramatic rise of computing and everything that it represents for human capabilities.

He specifically references the Dartmouth conference in 1956, which I have written about in the past as a landmark in the 20th century, directing us toward the future that we are now in.

Then there’s the human genome project in the 2000s, and other stations in this quickly evolving world where we’re starting to use the products of LLMs and neural networks as independent cognitive agents.

A New Chapter

“Polyintelligence creates the potential to unify the organic, the human, and the technological,” Afeyan writes, describing processes of applying AI and human intelligence to life science. “It invites us to reimagine intelligence as a network of connections that transcends boundaries, enabling us to think, create, and innovate at a depth and scale that can produce solutions to some of the world’s most intractable, contemporary challenges.”

As concrete examples, he references sperm whales, and the application of AI to their communications, and I’ve also written about this based on some of the experts I’ve heard at conferences.

Another example is very different, and impacted our world immensely. It was the struggle for a Covid vaccine as the pandemic ravaged global society.

In his graduation speech, which I heard, Afeyan talks about his work on vaccines at Moderna, and how leveraging state-of-the-art capabilities led to a quicker process to inoculate people against the dreaded respiratory disease.

That should stand as an example of why this kind of work is important.

He talks about “mission impossible,” and embracing these big tasks, using all of the tools that are disposal.

The Rise of Agentic AI

Later on, Afeyan also talks about agentic workflows, which is front and center in the research that many teams are doing now. I’ve been hearing about single-agent and multi-agent AI systems more as 2025 begins. Part of this has to do with game theory – computers understanding how humans work – but other aspects of it involve tackling complex tasks, and being able to create sophisticated results without human prompting or detailed human oversight.

Ruminating on such developments, Afeyan tells us to “buckle up” and talks about “what if” scenarios.

“The ultimate reward,” he writes, “is a collaborative future in which the boundaries of knowledge continuously expand, reshaping human health, planetary health, and the very nature of discovery itself.”

All of this is worth thinking about as we move into a new year that’s going to be its own fulcrum for cutting-edge technologies and their impact on our world.

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