![]() ![]() ![]() 。 The Hall Monitors Are Winning the AI Wars, Part 1: ChatGPT 。 What Does It Mean to “Create” Something With Generative AI? 。 AI content generation series: Part 1, Part 2, Part 4 If you want to know more about how generative ML models work and you have some time, read the following pieces: This family also includes Stable Diffusion and all the other prompt-driven, text-to-whatever models that are daily doing fresh miracles on everyone’s feeds right now. So what follows is my effort to help others get closer to the target in their thinking and writing about this new category of technology.Īt the heart of ChatGPT is a large language model (LLM) that belongs to the family of generative machine learning models. That said, I’m certainly far enough along that I can help others who are a few steps behind. (Speaking of, if you run a shop that sells dedicated ML workstations and would like to publicly sponsor this newsletter by sending me one, do get in touch.) Like everyone else, including active researchers in machine learning, I’m still on my own journey with getting my head around it at multiple levels. To be clear, I do not know everything I’d like to know about this topic. To put it another way, there are some can-opener problems manifesting in the ChatGPT conversation, and lowering the quality of The Discourse. Rather, what I mean is that they’re not working with a practical, productive understanding of what the bot’s main parts are and how they fit together. ![]() And by “unhelpful ways,” I don’t just mean that they’re anthropomorphizing (though they are doing that). In articles and podcasts, people are talking about this chatbot in unhelpful ways. The story so far: Most of the discussion of ChatGPT I’m seeing from even very smart, tech-savvy people is just not good. ![]()
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