Today's talk is with neuroscientist #KarlFriston of @ucl, who will offer a heuristic proof suggesting that life is an inevitable emergent property of any weakly mixing random dynamical system that possesses a #Markov blanket.
...and because it's 2020 and nothing is ever simple, we are having technical issues with the stream. The talk is recorded and we will upload it across all of our platforms ASAP. Our apologies!
Spatial boundaries are statistical boundaries: #KarlFriston on #MarkovBlankets, the reciprocal interfacing between internal and external states.
Follow this thread for more highlights from the talk and stay tuned for the video link...
"If a system has an attracting set, we'd see a behavior where [a drop of ink] would gather together, as if it were UP a concentration gradient.
#KarlFriston on formalisms for the inevitable emergence of self-organizing biological processes, right now at SFI:
"It would look, if I were trying to minimize my expected #surprise, as if I were trying to minimize my #entropy."
"We're just talking about self-evidencing Lorenz Attractors as self-evidencing in a mindless way...in a moment it's going to get much more interesting. But in the sense of beliefs, these are not propositional beliefs. It's a very deflationary definition."
"Heuristically, what we can now do is ask, do internal states appear to infer the cause of their sensory states based on this gradient flow [into an attractor]?"
"The external states are also making their inferences and learning about you...I would normally speak about this as the #Bayesian#brain predicting and being predicted by the outside world."
#KarlFriston of @UCL speaking at SFI now — stay tuned for links to the full video...
"It looks as if your job is to infer the causes out there that made these impressions on your sensory blanket."
"The actual cause of your sensations you will never know. They are on the other side of your #MarkovBlanket."
#KarlFriston of @UCL on the mathematical formalisms supporting a true ontological #Other while also arguing for the inevitability of biological self-organization:
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@aeonmag@C4COMPUTATION@MelMitchell1 "Simple cause-effect reasoning, to which the human mind can default, is not a good policy tool. Instead of attempting to narrowly forecast and control outcomes, we need to design systems that are robust and adaptable enough to weather a wide range of possible futures."
@aeonmag@C4COMPUTATION@MelMitchell1 "All human societies are collective & coupled. Collective, meaning our combined behaviour gives rise to society-wide effects. Coupled, in that our perceptions & behaviour depend on the perceptions & behaviour of others & on the social & economic structures we collectively build."
"Really baseline testing doesn't give you enough information. If it tells you there is 5% infection in a nursing home it doesn't tell you if the virus is increasing. But serological testing can. These are complementary tools."
Follow this thread for insights from today's SFI Seminar by Juan Pérez-Mercader (SFI + @Harvard), which you can watch live on our FB page. Recording will be saved for later viewing at this link, as well as YT:
What properties characterize life? The search for a fundamental theory of #biology continues to face some serious challenges:
• n = 1
• no unified math
• can't modify carbon experimentally
• biology is still process-description
BUT: ✨ info-metabolism-replication-evolution ✨
The proportion of #neuroscience papers with woman first or last authors grew from 1995 to 2018, but the undercitation of female authors actually *increased* in that time.
Undercitation of #neuroscience research with first or last woman authors appears to be driven predominantly by the reference lists of papers written by male-male teams.
This is not to say, however, that all men undercite women, or that women do not also undercite women:
Some background from Lauren Ancel Meyers @meyerslab about the #epidemiology modeling community's efforts to produce #pandemic projections for the @CDC — first about #influenza and then, suddenly and with the models incomplete, pivoting to #COVID19:
Aggregate data from travel in and out of #Wuhan in early 2020. To infer the pace of the #epidemic, @meyerslab and colleagues used info on timing & location from first cases in other areas, travel volume to/from Wuhan, and gave an early doubling rate for #COVID19: