Experimental support for the #hotsprings hypothesis for life's origin: David Deamer of @ucsc on nucleic acid polymerization in the wet-dry cycling of Darwin's "warm little pond," powered by #geothermal. Lab results confirmed in #hydrothermal pools.
From "boring statistical partitioning" in the fission of early protocells to the complex #homeostasis-driven #mitosis of the cells we know - Doron Lancet of @WeizmannInstSci on the gradient between closure of #autocatalysis#networks to complex regulatory mechanisms of #biology.
"Life is an integrated nested network of dynamic #kinetic cycles."
Addy Pross emphasizes the importance of motion to the persistent forms of self-organizing #complexsystems at SFI today
The #adjacentpossible: new possibilities emergent at the boundaries of an evolving system, ratcheting its way into more #novelty. @stevenstrogatz joins us remotely to explain the #math of how "one new thing leads to another"
On cells as attractors within the phase space of all possible interactions within gene regulatory networks: Sui Hang of @isbsci speaking on #cell types as literal basins into which #biology settles...
Stefan Bornholdt of @UniBremen at SFI today on the #emergence of synchrony in autonomous #Boolean networks, with implications for #attractor#scaling (# of cell types as function of gene regulatory network size).
Stefan Thurner of @CSHVienna on the #combinatorial-#coevolutionary-#critical model of #evolution, which starts from amazingly simple premises to make meaningful predictions of major evolutionary transitions, economic phase shifts, bursts of product/species #diversity, and more...
"What is the greatest source of #uncertainty in #climate forecast models? Us. Humans."
When it comes to living systems, #science ought to give up on the search for universal laws, says Maël Montévil at SFI today - the path-dependency and inability to prestate function means no entailment, *but enablement*, in #biology:
• • •
Missing some Tweet in this thread? You can try to
force a refresh
ICYMI, this week's SFI Seminar by Fractal Faculty Stuart Firestein (@Columbia) on "what started out ass a very simple-seeming problem [re: #olfaction] and turned out to be very complicated":
"Everything we know about the world comes through these little holes in our head and the skin covering our body, processed through tissue specialized to interpret it."
"The thing to notice about [sight and hearing] is that they're [processing] fairly low-dimensional stimuli."
"Even a simple smell is composed of a VARIETY of molecules, and these are high-dimensional from a chemical point of view. And it's also a somewhat discontinuous stimulus. How do we get from this bunch of molecules to this unitary perception of something like a rose?"
"A key feature of this is talk is that we make sense of what each other are saying IN PART by what they say, but ALSO by what we expect of them."
"Language transmits info against a background of expectations – syntactic, semantic, and this larger cultural spectrum. It's not just the choices of make but [how] we set ourselves up to make later choices."
"I think what really drives [the popularity of the #multiverse in #scifi] is regret... There's a line in @allatoncemovie where #MichelleYeoh is told she's the worst version of herself."
"I don't think we should resist melting brains. I think we should just bite the bullet."
"When you measure the spin of an electron, or the position...what happened to all of the other things you could have seen? Everett's idea is that they're all real. They all become real in that measurement."
- SFI Fractal Faculty @seanmcarroll at @guardian theguardian.com/science/audio/…
"At the level of the equations there is zero ambiguity, but the metaphors break down. The two universes it splits into aren't as big as the original universe. The thickness of the two new universes adds up to the thickness of the original universe."
"One way to represent the kind of #compositionality we want to do is with this kind of breakdown...eventually a kind of representation of a sentence. On the other hand, vector space models of #meaning or set-theoretical models put into a space have been very successful..."
"Humans are prone to giving machines ambiguous or mistaken instructions, and we want them to do what we mean, not what we say. To solve this problem we must find ways to align AI with human preferences, goals & values."
- @MelMitchell1 at @QuantaMagazine: quantamagazine.org/what-does-it-m…
“All that is needed to assure catastrophe is a highly competent machine combined with humans who have an imperfect ability to specify human preferences completely and correctly.”
"It’s a familiar trope in #ScienceFiction — humanity threatened by out-of-control machines who have misinterpreted human desires. Now a not-insubstantial segment of the #AI research community is concerned about this kind of scenario playing out in real life."
- @MelMitchell1