- Story turbulence - how quickly a new story fizzled-out as new stories popped
- Narrative control - how often someone else retweets your tweet shows how much you control the story
- Collective chronopathy - the rate at which a population’s stories for a subject seem to change over time
Wednesday, August 3, 2022
Collective Chronopathy
Friday, July 9, 2021
Writing Robots 3
Semantic Scholar is notable for achieving the greatest compression rate of all summarizing tools; powered by AI and used for scientific research. With its new summarization feature, it surveys massive numbers of scientific research papers and reduces them to one-sentence summaries.
The lab gave the algorithm to select researchers who applied for a private beta, with the goal of gathering their feedback and commercializing the technology by the end of the year.Porr submitted an application. He filled out a form with a simple questionnaire about his intended use. But he also didn’t wait around. After reaching out to several members of the Berkeley AI community, he quickly found a PhD student who already had access. Once the graduate student agreed to collaborate, Porr wrote a small script for him to run. It gave GPT-3 the headline and introduction for a blog post and had it spit out several completed versions. Porr’s first post (the one that charted on Hacker News), and every post after, was copy-and-pasted from one of the outputs with little to no editing.The trick to generating content without the need for much editing was understanding GPT-3’s strengths and weaknesses. “It's quite good at making pretty language, and it's not very good at being logical and rational,” says Porr. So he picked a popular blog category that doesn’t require rigorous logic: productivity and self-help. [hilarious]Porr says his experiment also shows a more mundane but still troubling alternative: people could use the tool to generate a lot of clickbait content. “It's possible that there's gonna just be a flood of mediocre blog content because now the barrier to entry is so easy,” he says. “I think the value of online content is going to be reduced a lot.”
A team of researchers at OpenAI, a San Francisco artificial intelligence development company, has added a new module to its GPT-3 autoregressive language model. Called DALL·E, the module excerpts text with multiple characteristics, analyzes it and then draws a picture based on what it believes was described.The system is able to create images by using a corpus of information consisting of internet pages. Each part of the text is researched in an attempt to learn what it should look like. For the previous example, it would search for and analyze thousands of pictures of dogs. Then it would study cats, and what their claws look like, and then birds and their tails. Then, it combines the results into several graphic images to give users a variety of results.via OpenAI: DALL·E: Creating Images from Text: openai.com/blog/dall-e/
Thursday, January 14, 2021
Exposure Science
Precipitating the Noosphere
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| Nikon Small World 2020 - Single Neuron - Nadia Efimova |
Sunday, August 16, 2020
Sociothermodynamics and Predictive Analytics
Investigating dynamics of democratic elections using physics theory
Feb 2020, phys.org
Sometimes, physics theories and models can be used to study seemingly unrelated phenomena, such as social behaviors or social dynamics.
While human beings are not exactly similar to individual physical particles, theories or techniques that physicists use to analyze "behavioral patterns" in atoms or electrons may aid the general understanding of large-scale social behaviors, as long as these behaviors do not depend on small-scale details.
Based on this idea, some researchers use physics theories to investigate social behaviors that take place during democratic elections, for example.
The very idea of a quantifiable social network was unknown to the average person prior to the year 2000. (Check out Barabasi's Links for a reminder of what the world was like at that time.) Now, the idea is clear as day, with the trademark "nodes-and-links" emblazoned into the retina of any 21st century citizen. We all understand what a social network is, and being that a social network is the marriage of sociology and network science, we can all understand these models and their implications.
Below is a list of articles related to sociothermodynamics, although I tend to use this term as a synonym for predictive analytics as well, so there are other articles about using all kinds of big data (like semantic analysis) to make sense out of the sloppy sociobiological mess that we spread all over the planet. And speaking of spreading all over, the last article uses biological data from slime molds to describe human social behavior.
The physics that drives periodic economic downturns
Mar 2020, phys.org
There exist universal mechanisms that give rise to laws governing the growth of economics.
The way spilled milk spreads across the floor can explain why economic downturns regularly occur, as a natural feature of physics, rooted in the time-dependent movement of spreading over an area. Growth of the innumerable spreading phenomena over time follows the shape of an "S curve" otherwise known as the sigmoid function.
A bottle of milk spilled on the floor will have a small initial footprint, followed by a rapid finger-shaped expansion across the kitchen's tiles, followed by a final phase of slow creep.
This same history of slow, fast, slow can be seen in chemical reactions, population growth, the adoption of new technology and even the spreading of new ideas.
-Adrian Bejan et al, Energy theory of periodic economic growth, International Journal of Energy Research (2020). DOI: 10.1002/er.5267
Secularism and tolerance of minority groups predicts future prosperity of countries
Feb 2020, phys.org
Changes in culture generally come before any improvements in wealth, education and democracy, rather than the other way around.
Promoting democracy, whether through economic exchange or regime change, will only succeed if combined with promoting openness and tolerance of minority groups.
(In the 20th Century) places which had the greatest improvement also tended to have pre-existing secular and tolerant cultures.
Study of 62 countries finds people react similarly to everyday situations
June 2020, phys.org
The world is a much more similar and unified place than we once thought.
[Because at the right scale, we are all just particles banging around on the surface of the planet.]
This project is unprecedented. Very few international studies look at relationships between more than two countries, let alone 62," Lee, a doctoral researcher in the lab of UCR Distinguished Professor David Funder, and the lead author of the paper.
Facebook users change their language before an emergency hospital visit - study
Mar 2020, phys.org
Researchers from the Perelman School of Medicine at the University of Pennsylvania and Stony Brook University's Computer Science Department compared patients' Facebook posts to their medical records, which showed that a shift to more formal language and/or descriptions of physical pain, among other changes, reliably preceded hospital visits.
Wikipedia visits to disease outbreak pages show impact of news media on public attention
Mar 2020, phys.org
During the 2016 Zika outbreak, news exposure appears to have had a far bigger impact than local disease risk on the number of times people visited Zika-related Wikipedia pages in the U.S.
Previous research has explored how public opinion responds to media exposure during an emerging outbreak, but has mostly relied on surveys rather than observational data.
The analysis showed that Zika-related Wikipedia page view counts during the outbreak were highly synchronized with mentions of the virus in web and national TV news at both the national and state level.
What do 'Bohemian Rhapsody,' 'Macbeth,' and a list of Facebook friends all have in common?
June 2020, phys.org
I almost forgot to mention -- network science is rapidly evolving into a useful tool for understanding our world, and there's a possibility that it can go even further than physics in modeling human dynamics; I saw earlier this year a that network science could do a better job than physics of describing what happens inside the sun. [The link to that study is probably on this weblog somewhere].
New research published in Nature Physics uses tools from network science to explain how complex communication networks can efficiently convey large amounts of information to the human brain. Conducted by postdoc Christopher Lynn, graduate students Ari Kahn and Lia Papadopoulos, and professor Danielle S. Bassett, the study found that different types of networks, including those found in works of literature, musical pieces, and social connections, have a similar underlying structure that allows them to share information rapidly and efficiently.
The researchers evaluated 40 real-world communication networks to see what features were crucial for communicating information. They looked at works of English literature, including the canon of Shakespeare and Jane Austen's "Pride and Prejudice," along with musical pieces such as Mozart's Sonata No 11 and Queen's "Bohemian Rhapsody." They also studied networks of social relationships, including co-authorship networks in science and Facebook friend connections.
After looking at this diverse group of networks, the researchers found that the large-scale structure of a network was essential to that network's ability to convey information. What was surprising was just how similar this structure was across the different networks, whether the network was representing noun transitions in a work of literature or melodic progressions in a piece of music.
What makes these networks both information-rich and efficient is a balance between two key network features known as "community" structure and "heterogeneous" structure. Community structure occurs when nodes clump together and form clusters that evoke related concepts. Saying the word "dog" might bring to mind "ball," "Frisbee," or "bone," for example. Such community structure helps make networks more efficient because a person can anticipate what word or idea might come next.
But if a person can anticipate what comes next, there won't be much information conveyed because information is directly related to surprise. To provide information, networks have to have a "heterogeneous" mixture of both well-connected and sparsely connected nodes. Take the works of Shakespeare as an example. While "the" and "and" are used 28,944 and 27,317 times, respectively, there are also 12,493 word forms that only occur once. "At a hub like, 'the,' you can't anticipate where you are about to go," says Lynn. "It turns out that these hub nodes are really important for generating surprisal or, equivalently, information."
Evolution selects for 'loners' that hang back from collective behavior-at least in slime molds
Mar 2020, phys.org
Testing whether loners are random or a predictable quantity, possibly subject to natural or cultural selection:
Target system: cellular slime mold Dictyostelium discoideum
Evolution could indeed select for loner behavior in slime molds. Loners are both an ecological and an evolutionary insurance plan, a way to diversify a genetic portfolio to ensure the survival of the social, collective behavior:
Slime molds, when they are threatened by starvation, the tiny amoebae coalesce into slug-like creatures that then aggregate into a large, swaying tower that grows upward with a burgeoning slimy top—until that top sticks to an unwitting passing insect, the starvation-resistant spores hitchhiking out into the world, while all the individuals making up the base and stalk die.
But what caught Tarnita's eye were the slime mold loners, the amoebae that resist the biochemical call to form the tower.
Here and there, some scattered cells on the plate just didn't seem to react at all to this aggregation process.
They tested the loners to see if they were flawed in some way, but they couldn't find anything wrong with them.
It could make sense for some fraction of the slime mold population to remain behind in order to take advantage of any resources that might return in the environment while the rest of the cells are aggregating.
30% chose the loner life over collective action.
The proportion of solitary cells in the social amoeba Dictyostelium discoideum is not simply determined by each cell individually tossing a coin. It results instead from interactions between the [organism] and the environment.
The decision not to become part of the collective is, in fact, taken collectively. All the cells kind of talk to each other chemically: 'Oh, you're going? I guess I'm staying.' There's communication involved in becoming a loner.
-"Eco-evolutionary significance of 'loners'" by Fernando W. Rossine, Ricardo Martinez-Garcia, Allyson E. Sgro, Thomas Gregor and Corina E. Tarnita, appears in the Mar. 18 issue of the journal PLoS Biology.
Image source: Fernando Fornies Gracia, infrared photography
Saturday, July 11, 2020
Writing Robots 2
June 2020, phys.org
For scale and context:
Those concerns led OpenAI in February 2019 to take the unusual step of declining to release the early version, GPT-2, citing fears potential misuse could be dangerous.
GPT-3, about 100 times more powerful than GPT-2, has performed admirably in tests, according to the OpenAI report. It tackled reading compression exercises requiring filling in word blanks, tackling "on-the-fly reasoning," and generating compositions up to 500 words.
Partially Related Article:
Your brain shows if you are lonely or not
June 2020, phys.org
The closer participants felt to someone, the more similarly their brain represented them throughout the social brain.I mean if this doesn't say something about identity -- You are a collective of those closest to you, not a person so much as a multi-person chimera.
Friday, July 10, 2020
Neutral Networks
The image you see here is a partial map of the internet, circa 2005. It's a colorful organic explosion of lifewebs. It's the closest thing to seeing the noosphere that we have ever come. It's beautiful, and I think we need to see it once in a while, but it's totally unrelated to this post.
Study finds no media bias when it comes to story selection
Apr 2020, phys.org
Hassell's work on the study began in 2017 and embraced a number of research-gathering methods, including a survey of 6,000 journalists, election returns, Twitter data and a novel correspondence experiment design.
"There is an institutional set of norms that dictate newsworthiness," he said. "Lots of things drive those norms, but reporters' personal, ideological preferences about what they view as valuable is not one of them."
Notes:
Hans J. G. Hassell et al. There is no liberal media bias in which news stories political journalists choose to cover, Science Advances (2020). DOI: 10.1126/sciadv.aay9344









