Book preaching: I want Computer Game creation to be decentralized. I want open access to the creative act for everyone. I want games as zines. (Network Economy, indie) (more)

aka Video Game, Interactive Game (more)

Zvi Mowshowitz: Childhood and Education Roundup #5. Bullying: Why do those who defend themselves against bullies so often get in more trouble than bullies? This is also true in other contexts but especially true in school. (more)

Zvi Mowshowitz: AI #84: Better Than a Podcast. Introduction: Andrej Karpathy continues to be a big fan of NotebookLM, especially its podcast creation feature. There is something deeply alien to me about this proposed way of consuming information, but I probably shouldn’t knock it (too much) until I try it? So I figured: What could be a better test than generating a podcast out of this post (more)

Zvi Mowshowitz: AI #85: AI Wins the Nobel Prize. Both Geoffrey Hinton and Demis Hassabis were given the Nobel Prize this week, in Physics and Chemistry respectively. Congratulations to both of them along with all the other winners. AI will be central to more and more of scientific progress over time. This felt early, but not as early as you would think. (more)

I've now slid into choosing now to be the time for making lots of changes to my Linode (more)

Nadia Asparouhova: Mapping out the tribes of climate. Climate is a gravity well for talent, but why don’t other, equally impactful topics attract talent in the same way? Why isn’t everyone dropping everything to work on homelessness, or global poverty, or curing cancer?... What I found instead is that while the media still portrays climate change as a simple question of beliefs, the climate field has long moved on to diversified solutions. Whether one believes in climate change is no longer the interesting question; now it’s “What do you think is the right approach?” (more)

Machine learning, a branch of Artificial Intelligence, concerns the construction and study of systems that can learn from data (Big Data). For example, a machine learning system could be trained on email messages to learn to distinguish between spam and non-spam messages (SpamWars). After learning, it can then be used to classify new email messages into spam and non-spam folders. http://en.wikipedia.org/wiki/Machine_learning (more)

Simon Wardley: Why open source AI matters? Why the fuss about conversational programming — Part III. ((2023-01-30) Wardley Why The Fuss About Conversational Programming) (more)

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)