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COOPERATIVE EVOLUTION. “If RNA fragments self-ligate into self-replicating ribozymes they constitute networks. For example, three-membered networks represent highly cooperative growth behavior. If such networks compete directly with selfish autocatalytic cycles, the former grow faster. This clearly indicates the ability of RNA populations to evolve into higher complexity through cooperation which clearly outruns selfishness.” https://lnkd.in/dWwkKpD View in LinkedIn

SOCIAL EMERGENCE. “Evolution of identity implies emergence of self/non-self differentiation competence. This is a crucial step from single RNA stem loops to RNA stem loop groups.” https://lnkd.in/dWwkKpD View in LinkedIn

TRANSITION TO LIFE. “If stem-loop groups build complex consortia, biological selection and social interactions emerge that are not present in a purely chemical world.” https://lnkd.in/dWwkKpD View in LinkedIn

BOLTS VS JELLY. "Brain emulation requires cells. Machines can match us in many tasks, but they work differently from networks of nerve cells." (Google Deepmind). https://lnkd.in/daaAAYt View in LinkedIn

MOBILE AGENTS. “Such populations determine regulations in many ways and may newly adapt different functions. The use of a natural language or code depends on consortia of living agents, because natural languages and codes function according to rules.” https://lnkd.in/dWwkKpD View in LinkedIn

NEW THINKING. "Now those metaphors and models pervade explanations of how the brain ‘computes’. But these binary abstractions do not capture all the complexities inherent in the brain. So now I see circles before my eyes. The brain has become a digital computer; yet we are still trying to make our machines intelligent. Should those machines be modelled on the brain, given that our models of the brain are performed on such machines? That will probably not be enough." (Google Deepmind). https://lnkd.in/daaAAYt View in LinkedIn

ECOLOGY OF MOBILE ELEMENTS. “Or they interact as suppression-relevant silencers or as infection-derived modular tools of non-coding RNAs that have built consortia of complementary agents that function together such as retrovirus-derived remnants, such as LTRs, non-LTRs, group II introns, rRNAs, tRNAs, spliceosomes, editosomes, and other counterbalancing modules.” https://lnkd.in/dWwkKpD View in LinkedIn

CATCH-22. "I believe that we are in an intellectual cul-de-sac, in which we model brains and computers on each other, and so prevent ourselves from having deep insights that would come with new models. The first step in this back and forth was made by Alan Turing." (Rodney Brooks, Emeritus professor of robotics, Massachusetts Institute of Technology)." (Google Deepmind). https://lnkd.in/daaAAYt View in LinkedIn

DNA AS HABITAT. “This change in perspective from molecules to agent-based behaviour will look at interactions of RNA viruses, DNA viruses, RNA-DNA viruses, viral swarms, and sub-viral groups like any ligated RNA stem loop groups that cooperate and coordinate (regulate) within cellular genomes as replication-relevant co-players.” https://lnkd.in/dWwkKpD View in LinkedIn

MEDICAL APPLICATION. “We announced a partnership with the NHS a couple of weeks ago but that was really just to start building a platform that machine learning can be used in. I think the sort of things you’ll see this kind of AI do is medical diagnosis of images and then maybe longitudinal tracking of vital signs or quantified self over time, and helping people have healthier lifestyles. I think that’ll be quite suitable for reinforcement learning.” https://lnkd.in/dT88xiV View in LinkedIn