Stephen Downes

I'm linking to this more as a data point about video-generation AI models than anything else, but it's worth taking note: "We're beginning to see models specialize across specific dimensions: there is no 'God Model' that's great at everything. Startups are finding new opportunities across two main dimensions: video models that excel at one key thing (Physics! Anime! Multiple shots!) and products that abstract away arduous workflows." This is a development that should be expected across all of AI. Different AI will be defined by different training, contexts and prompts to produce different outcomes and specialize in different areas. Some AI will be expert at medical diagnosis, for example, while others will be laughably bad. The question is: how do we optimize an AI to support learning? Will one model be enough? Or do we need different models for different learners in different scenarios?