"You don't see radio changing gradually and suddenly become radar. #Darwin's theory doesn't work for #technology, and we have to make a new observation."
Unlike the two-parent #inheritance typical to (but not ubiquitous among) #complex organisms, #technology inherits features from n parents - a "vast ancestral #network" more like horizontal gene transfer networks in #bacteria.
W Brian Arthur on sumulating #invention on a chip:
Output = "a combinatorial explosion" or #singularity, albeit one that arguably occurred millions of years ago, or in the distant future (since the model doesn't specify t = 0):
"We can't have universal models if organisms differ. But most of our models are universal. So how do our models need to differ for species-specific #search?"
Theorizing the #AdjacentPossible in evolutionary systems, Walter Fontana of @Harvard suggests a mechanism for The Baldwin Effect at the intersection of genetic plasticity and mutation.
Evolvability points to a link between the non-hereditary and the hereditary, without Lamarck:
"The legal system becomes more complex as strategies & precedents proliferate in a combinatorial explosion that was not pre-statable."
"While we cannot control precisely how the law develops, we *can* enable the development of the law..."
- Attorney Caryn Devins Strickland at SFI
"A totally new approach to biomarker discovery & drug delivery discovery."
"For many diseases, your genetic risk is going to determine how you get treated."
Lee Hood of @isbsci at SFI on a multi-omics approach to teasing apart complex correlations for innovative #medicine:
A fate worse than #death: ~2/3 surveyed said they'd rather accept an #obesity intervention w/ higher mortality rates than one that would forbid sweets (pic 4).
Yet patient preference gets ignored, leading to clashes between #healthcare companies & regulators.
Bennett Levitan:
"Models aren't just used to predict things; it's how people present their worldviews to one another."
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