Recurrent neural networks (RNNs) are a class of artificial neural networks for sequential data processing. Unlike feedforward neural networks, which process data in a single pass, RNNs process data across multiple time steps, making them well-adapted for modelling and processing text, speech, and time series. https://en.wikipedia.org/wiki/Recurrent_neural_network

TensorFlow is a free and open-source software library for machine learning and artificial intelligence. It can be used across a range of tasks but has a particular focus on training and inference of deep neural networks.[4][5] TensorFlow was developed by the Google Brain team for internal Google use in research and production. https://en.wikipedia.org/wiki/TensorFlow

In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a model inspired by the structure and function of biological neural networks in animal brains.[1][2] An ANN consists of connected units or nodes called artificial neurons, which loosely model the neurons in the brain. These are connected by edges, which model the synapses in the brain. Each artificial neuron receives signals from connected neurons, then processes them and sends a signal to other connected neurons. https://en.wikipedia.org/wiki/Neural_network_(machine_learning) (more)

Simon Wardley: Maps as Code. Why the fuss about conversational programming? Part II. (2023-01-30) Wardley Why The Fuss About Conversational Programming (more)

Jon Udell: Elevating the Conversation with LLM Assistants. Here is some CSV data that created a problem for Steampipe’s CSV plugin. Can you see what’s wrong? Last week several of us failed to see, at first glance, what was wrong. Excel was happy with the data... ChatGPT-4 had a better idea. (more)

what seems like Elite Overproduction is really Midwit Overproduction

Gary Marcus on AI (GenAI). ...a new article on LLMs from six AI researchers at Apple: "we found no evidence of formal reasoning in language models .... Their behavior is better explained by sophisticated pattern matching--so fragile, in fact, that changing names can alter results by ~10%!" (more)

Gary Marcus: AGI by 2027? Apparently OpenAI’s internal roadmap alleged that AGI would be achieved by 2027, according to the suddenly ubiquitous Leopold Aschenbrenner (recently fired by OpenAI, previous employed by SBF), who yesterday published the math to allegedly justify it. ((2024-06-01) Leopold Aschenbrenner's AGI Situational Awareness Paper) (more)

The Algebraic Mind: Integrating Connectionism and Cognitive Science, by Gary Marcus; ISBN: 9780262632683 (more)

Gary Fred Marcus (born 8 February 1970) is an American psychologist, cognitive scientist, and author, known for his research on the intersection of cognitive psychology, neuroscience, and artificial intelligence (AI). Marcus is professor emeritus of psychology and neural science at New York University. In 2014 he founded Geometric Intelligence, a machine learning company later acquired by Uber.[3][4] His books include Guitar Zero[5] and Kluge. https://en.wikipedia.org/wiki/Gary_Marcus

Elite overproduction is a concept developed by Peter Turchin, which describes the condition of a society which is producing too many potential elite-members relative to its ability to absorb them into the power structure.[1][2][3] This, he hypothesizes, is a cause for social instability, as those left out of power feel aggrieved by their relatively low socioeconomic status. https://en.wikipedia.org/wiki/Elite_overproduction (more)

The word "mid-witted" was popularized by far-right activist and writer Vox Day. On February 17th, 2012, Vox Day[1] published the blog post "The tragedy of the mid-witted" in which he commented on a life story article "Lessons of a very sexy pirate costume" by Jennifer Wright... The term "midwit," meaning a person of average intelligence, saw use on 4chan starting in late 2013... On January 1st, 2017, an anonymous 4chan[6] user made the earliest found post which used the IQ bell curve diagram to argue about the similarity of political views of groups with low and high intelligence... On June 24th, 2019, an anonymous /pol/[11] user posted a Manlet meme referencing the horseshoe theory interpretation of the IQ bell curve... The viral popularity of the format began on March 10th, 2010, when an anonymous 4chan[15] user posted a meme about Ted Kaczynski and the anarcho-primitivistic ideology. https://knowyourmeme.com/memes/iq-bell-curve-midwit (cf Middle Mind) (more)

see Personal Data Server

component of BlueSky architecture (more)

Portable Identity for ActivityPub. I want to focus on: portable digital identity. The idea that I should be able to take all of my data, everything that my identity consists of, and move wholesale to a new instance/server/PDS/whatever you call it. Bluesky permits this. Mastodon and most (all?) other ActivityPub implementations do not. But that doesn’t have to be the case, nothing about ActivityPub—architecturally speaking—is incompatible with this vision. (more)

Zvi Mowshowitz: AI #73: Openly Evil AI. What do you call a clause explicitly saying that you waive the right to whistleblower compensation, and that you need to get permission before sharing information with government regulators like the SEC? (more)

artificial super-intelligence - AGI but way smarter/faster than humans

Leopold Aschenbrenner's AGI Situational Awareness Paper. https://situational-awareness.ai/ The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace many college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence (ASI), in the true sense of the word. Along the way, national security forces not seen in half a century will be unleashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.

Neuro-symbolic AI is a type of artificial intelligence that integrates neural and symbolic AI architectures to address the weaknesses of each, providing a robust AI capable of reasoning, learning, and cognitive modeling. As argued by Leslie Valiant[1] and others,[2][3] the effective construction of rich computational cognitive models demands the combination of symbolic reasoning and efficient machine learning. Gary Marcus argued, "We cannot construct rich cognitive models in an adequate, automated way without the triumvirate of hybrid architecture, rich prior knowledge, and sophisticated techniques for reasoning."[4] Further, "To build a robust, knowledge-driven approach to AI we must have the machinery of symbol manipulation in our toolkit. Too much useful knowledge is abstract to proceed without tools that represent and manipulate abstraction, and to date, the only known machinery that can manipulate such abstract knowledge reliably is the apparatus of symbol manipulation.".. Henry Kautz,[6] Francesca Rossi,[7] and Bart Selman[8] also argued for a synthesis. Their arguments attempt to address the two kinds of thinking, as discussed in Daniel Kahneman's book Thinking Fast and Slow. It describes cognition as encompassing two components: System 1 is fast, reflexive, intuitive, and unconscious. System 2 is slower, step-by-step, and explicit. System 1 is used for pattern recognition. System 2 handles planning, deduction, and deliberative thinking. In this view, deep learning best handles the first kind of cognition while symbolic reasoning best handles the second kind. Both are needed for a robust, reliable AI that can learn, reason, and interact with humans to accept advice and answer questions.... Implementations of neuro-symbolic approaches include: AllegroGraph: an integrated Knowledge Graph based platform for neuro-symbolic application development.[25][26][27]; Scallop: a language based on Datalog that supports differentiable logical and relational reasoning. Scallop can be integrated in Python and with a PyTorch learning module; .... https://en.wikipedia.org/wiki/Neuro-symbolic_AI

Micah Sifry: Inside the Fall of Obama’s Grassroots Army. Christopher Edley had invited them to join a “Movement 2.0 Brainstorming Group.” Together, they would ponder a crucial question: how to “sustain the movement” should Barack Obama, who was still a month away from accepting the Democratic nomination, go on to win the White House. (more)