Donald Clark hints - pretty accurately, to my mind - at what generative AI really means for learning. "Most people want a 'working knowledge' of things they want to do, not over-engineered, PPT-led, abstract courses. This new era of PedAIgogy may herald a more dynamic way of formal teaching and learning. It may also swing us quickly toward performance support in the workplace, where the technology responds to needs. A demand driven, not supply-driven model." Just for fun, I think it is interesting to look back at the model of learning proposed by connectivism and to compare it with what Clark is describing here. Related: generative AI as edtech, slides from Shum, Kocaballi & Shibani.
Some more AI updates. Rich Heimann inverts Polanyi: "Polyani is careful to say, "we know more than we can tell," not that we don't know because we cannot tell. However, ChatGPT is Polanyi's paradox in reverse. It can tell, but it doesn't know. " Multimodal LLMs Are Here: "Microsoft revealed Kosmos-1, a large language model "capable of perceiving multimodal input." Or as Ars Technica put it, it can "analyze images for content, solve visual puzzles, perform visual text recognition, pass visual IQ tests, and understand natural language instructions." ChatGPT in More Apps: "we've achieved 90% cost reduction for ChatGPT since December; we're now passing through those savings to API users." Invisible doors in neural networks: "Hey, this is how you should slightly perturb your data to get favorable treatment."
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