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Jul 26, 2022 16 tweets 24 min read Read on X
"Argument-Making in the Wild"

Today's SFI Seminar by Simon DeDeo (@LaboratoryMinds), streaming now. Follow our thread for pull quotes and slides:

First, let's divide human history into three eras, or regimes of #knowledge #production and #consumption:

• #premodern/#archaic
• #modern + #postmodern
• the #egregore (online content sharing)

• The premodern era is defined by caloric restriction.
• The modern era is characterized by a small number of sellers of #information vs. a large number of consumers (see also #HerbertSimon's remarks on the "poverty of #attention")

In the third regime, there's a #feedback loop between #attention allocation and content production/consumption. We're living through a #phasetransition akin to the #originoflife, with respect to cultural #information:

Something has got to give: attentional #scaling is not indefinite. #ContentModeration

cc @GreatDismal

"It's sewage that is being processed and re-processed."
- Simon DeDeo re: @Twitter 🤣

(see also: "Your Catfish Friend" by Richard Brautigan:
poets.org/poem/your-catf…)

"We've never been in a situation where millions of people can respond to each other in minutes."

#media @Reddit
"This system is eating people, but it's not necessarily the same people every day."
And then with a shout to @MelMitchell1 and #ML #MachineLearning, the structure of the #perception/#reproduction cycle:
Re: work with @_c_perry and the #RedPill movement, a runaway #misogynist #ConspiracyTheory, and regarding it in terms of #metabolic closure – an #egregore on @Reddit fed by #attention and dissected with #TopicModeling (yay #Bayesian)
"In general, something like 90% of the people [in #RedPill] post once and disappear forever. Most people are tourists. Our question here is about #semantics. How do people flow through this space?"

Re: #Attention #Metabolism
"We're interested in how people make arguments online...for @hugoreasoning @dansperber, #arguments are fundamentally public and shareable #objects."

"It's a taxonomic question. There's a standard answer from philosophers: #inductive, #deductive, #abductive"
DOES anyone change their view on r/#ChangeMyView?

"Yes. About 1% of the time."

Re: #adoption, #abortion, #argument (on @reddit)
There are six patterns of #argument extracted from the #TopicModeling data on r/#ChangeMyView

"The most powerful argument you can make is a pattern of #causation. The second is from personal experience."
This structure checks out on @lesswrong:
@lesswrong "The point at which I start getting #deductive with you probably suggests a #breakdown in #assumptions."

"We're just looking at how people #convince each other. They MAY be #convincing each other of the #truth."
The after-party: Simon DeDeo holds court at SFI afternoon tea with our 2022 Undergraduate Complexity Research cohort, discussing the relative timescales of biological and cultural evolution in humans and how we are flying off the adaptive treadmill...
#ErrorCatastrophe
📈🥳☕

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More from @sfiscience

Mar 10, 2023
🧵 "The Smell of Inhibition. A Code in the Nose?"

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?"
Read 8 tweets
Mar 10, 2023
🧵 "#Possibility Architectures: Exploring Human #Communication with Generative #AI"

Today's SFI Seminar with ExFac Simon DeDeo @LaboratoryMinds (@CarnegieMellon), streaming now:
"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."

@LaboratoryMinds re: work led by @clairebergey:
Read 15 tweets
Mar 9, 2023
"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."
Read 4 tweets
Dec 14, 2022
"Compositionality in Vector Space Models of Meaning"

Today's SFI Seminar by @marthaflinders, streaming:


Follow this 🧵 for highlights!
"Scientists gather here
Santa Fe Institute, oh so near
Inquiring minds seek truth"

#haiku about SFI c/o @marthaflinders & #ChatGPT

...but still, #AI fails at simple tasks:
"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..."
Read 14 tweets
Dec 13, 2022
"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.”

- Stuart Russell (@UCBerkeley) as quoted by @MelMitchell1 in her latest @QuantaMagazine article
"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
Read 6 tweets
Dec 12, 2022
"Training Machines to Learn the Way Humans Do: an Alternative to #Backpropagation"

Today's SFI Seminar by Sanjukta Krishnagopal
(@UCBerkeley & @UCLA)

Starting now — follow this 🧵 for highlights:
Image
"When we learn something new, we look for relationships with things we know already."

"I don't just forget Calculus because I learned something else."

"We automatically know what a 'cat-dog' would look like, if it were to exist."

"We learn by training on very few examples." Image
1, 2) "[#MachineLearning] is fundamentally different from the way humans learn things."

3) Re: #FeedForward #NeuralNetworks

"You choose some loss function...maybe I'm learning the wrong weights. So I define some goal and then I want to learn these weights, these thetas." ImageImageImage
Read 13 tweets

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