CEO of deepmind, also believes that best way to understand physics and universe is from a computational prespective and information being the fundamental unit of reality that can describe the universe (rather than matter or energy). This might mean that viewing physics in terms of information theoratic lens might be the best way to unlock the secrets of life and universe. i.e developing, Information processing machinery where we push universal turing machines or classic computation to its limits in order to tackle challenges of physics, biology and chemistry.

I read some quantum magazine articles on this, sharing a few excerpts below: Learning and information theory: Valiant won the A.M. Turing Award — often called the Nobel Prize of computing — for this contribution, which helped spawn the field of computational learning theory. he was one of the first to formalize what that relationship might look like in practice: In 1984, his “probably approximately correct” (PAC) model mathematically defined the conditions under which a mechanistic system could be said to “learn” information. In a 2013 book, also entitled “Probably Approximately Correct,” Valiant generalized his PAC learning framework to encompass biological evolution as well. (link)

Valiant’s self-stated goal is to find “mathematical definitions of learning and evolution which can address all ways in which information can get into systems.” If successful, the resulting “theory of everything” — a phrase Valiant himself uses, only half-jokingly — would literally fuse life science and computer science together. Furthermore, our intuitive definitions of “learning” and “intelligence” would expand to include not only non-organisms, but non-individuals as well. The “wisdom of crowds” would no longer be a mere figure of speech.

Similarly in physics we have quantum mechanics: quantum mechanics, treats information as the universe’s fundamental, indestructible currency, The theory is probably not complete, as discussion about information loss becomes interesting when we bring the blackhole phenomena into the discussion: if information gets destroyed in black holes, meaning that the probabilistic rules of quantum mechanics must be replaced by a more fundamental framework.

The Information Theory of Life

Christoph Adami does not know how life got started, but he knows a lot of other things. His main expertise is in information theory, a branch of applied

mathematics developed in the 1940s for understanding information transmissions over a wire. Since then, the field has found wide application, and few researchers have done more in that regard than Adami, who is a professor of physics and astronomy and also microbiology and molecular genetics at Michigan State University. He takes the analytical perspective provided by information theory and transplants it into a great range of disciplines, including microbiology, genetics, physics, astronomy and neuroscience. Lately, he’s been using it to pry open a statistical window onto the circumstances that might have existed at the moment life first clicked into place.

To do this, he begins with a mental leap: Life, he argues, should not be thought of as a chemical event. Instead, it should be thought of as information. The shift in perspective provides a tidy way in which to begin tackling a messy question. In the following interview, Adami defines information as “the ability to make predictions with a likelihood better than chance,” and he says we should think of the human genome — or the genome of any organism — as a repository of information about the world gathered in small bits over time through the process of evolution. The repository includes information on everything we could possibly need to know, such as how to convert sugar into energy, how to evade a predator on the savannah, and, most critically for evolution, how to reproduce or selfreplicate.

This reconceptualization doesn’t by itself resolve the issue of how life got started, but it does provide a framework in which we can start to calculate the odds of life developing in the first place. Adami explains that a precondition for information is the existence of an alphabet, a set of pieces that, when assembled in the right order, expresses something meaningful. No one knows what that alphabet was at the time that inanimate molecules coupled up to produce the first bits of information. Using information theory, though, Adami tries to help chemists think about the distribution of molecules that would have had to be present at the beginning in order to make it even statistically plausible for life to arise by chance. Read more: link:

David Sinclair who has an expert in longitivtiy research, wrote: “As a scientific definition, I'm proposing that aging is a loss of information—the information that keeps our cells healthy, the information that tells the cells which genes to read throughout our lives. And aging is a manifestation of cells losing their ability to read the right genes at the right time, which leads to cells losing their identity and tissues failing.”

Why should we car about this much theory? “biology as a field is completely under-theorized,” said Manfred Laubichler, a theoretical biologist at Arizona State University. “It’s very much still an empirically driven discipline.” “Twentieth-century biology was a biology of things,” he said. “Twenty-firstcentury biology is a biology of processes.” Krakauer and Flack, in collaboration with colleagues such as Nihat Ay of the Max Planck Institute for Mathematics in the Sciences, realized that they’d need to turn to information theory to formalize their principle of the individual “as kind of a verb.” To them, an individual was an aggregate that “preserved a measure of temporal integrity,” propagating a close-to-maximal amount of information forward in time.

1) The Moderna vaccine was made with the help of illumina genome sequencing. They were able to sequence the virus and send that sequence of nucleotides over to moderna for them to develop the vaccine - turning a classically biology problem, into a software problem, reducing the need for them to bring the virus in house. 2) Illumina has a cancer screening test called Galleri, that can identify a bunch of cancers from a blood test. It identifies mutated dna released by cancer cells. This is huge, if we can identify cancer before someone even starts to show symptoms, the chances of having a useful treatment dramatically go up.

Emergent autonomous scientific research capabilities of large language models - presents an agent that combines LLMs for autonomous design, planning, and execution of scientific experiments; shows emergent scientific research capabilities, including the successful performance of catalyzed cross-coupling reactions.

ChemCrow: Augmenting large-language models with chemistry tools - presents an LLM chemistry agent that performs tasks across synthesis, drug discovery, and materials design; it integrates 13 expert-design tools to augment LLM performance in chemistry and demonstrate effectiveness in automating chemical tasks. 

The flow from simulation to reality