REGISTER HERE tO WATCH THE RECORDING
How can we assess artificial intelligence (aka applied statistics) and the externalization of thought? What is the Turing Test? Who are the players — OpenAI, Ray Kurzweil, Jaron Lanier, and John Searle’s Chinese room? What is the difference between strong AI and weak AI? Memory vs. storage. What is the difference between representation thought (Kantian critical idealism) and grasping a thought in the Goethean sense? The experience of observing your own thinking vs. machine representation.How does an artificial intelligence play chess?move generator,static evaluation,recursive search for a high score to a given level of depth —> it plays this move. How does chatGPT work? Training on a large corpus of text (almost half the Internet! Project Gutenberg, Steiner elib, Wikipedia, Facebook posts, GitHub, Twitter it all goes in — a Generative Pre-trained Transformer — it is a Statistical Mimic it breaks down these texts into smaller tokens that statistically complete any given pattern of previous tokens — giving the appearance of answers which are statistically similar to the answers provided by other humans in the corpus of human literature on which it has been trained.How do robots create images? Just like the rubber stamp tool in Photoshop — midjourney and other stable diffusion methods micro-sample an enormous library of human-labelled images and then iteratively diffusely-dithers samples from multiple images requested by the user to create a believable synthesis of their request.After Deep Blue beat Gary Kasparov in 1996 — it was like a human trying to outrun a lawnmower engine or use pencil and paper to out-compute a calculator — Kasparov’s vision of the future was that a human with a computer could beat a computer alone. He saw that the game could continue to progress by leveraging the tools we have built ourselves. Man is a clever animal — yet in so many ways, we are just more busy beavers (using colloquialisms to bridge the techno and Anthro worlds here, and the busy beavers to add some humour to the delivery).
About the Presenter
John Roland Penner graduated from the Waldorf teacher training in Toronto in 2009 under the guidance of Diana Hughes and currently works in IT. He worked previously as a technical writer for the 3D animation company SideFX and did technical support for the architectural CAD firm Graphisoft. His main area of study is Goethean Science, Rudolf Steiner’s epistemological works, and artificial intelligence. To this end, he has written three of his own ‘artificial intelligences’ — a chess engine, a connect4 engine, and a hnefatafl (Viking chess) engine, as well as an ELIZA (conversational robot). He wrote these computer programmes to answer his own epistemological investigations regarding intelligence and cognition, which has led to a knowledge of the subject without resorting to magical beliefs about machines.
REGISTER HERE tO WATCH THE RECORDING
Main image used for this webinar: A digital image generated by AI system DALL-E from the prompt: ‘Humanoid robot creating art on canvas with many colors in Art Nouveau style.’ December 2022. (Image generated with the assistance of DALL-E)
