Comment by nphardon
Comment by nphardon 2 days ago
Still not clear to me what is meant by "ai" now? My sense is that it is a marketing term for LLM. Is that accurate? Do people now consider any ML project to be ai?
Comment by nphardon 2 days ago
Still not clear to me what is meant by "ai" now? My sense is that it is a marketing term for LLM. Is that accurate? Do people now consider any ML project to be ai?
It’s not clearly defined. Nowadays by default it means generative AI (https://en.wikipedia.org/wiki/Generative_artificial_intellig...).
AI is defined by algorithmic decision making. ML, a subset, is about using pattern matching with statistical uncertainty in that decision making. GenAI uses algorithms of classical ML, including deep learning based on neural networks, to encode the decode input to output, jargonized as a prompt. Whether diffusion or next token prediction, the patterns are learned during ML training.
AI is not totally encapsulated by ML. For example, reinforcement learning is often considered distinct in some AI ontologies. Decision rules and similar methods from the 1970s and 1980s are also included though they highlight the algorithmic approach versus the ML side.
There are certainly many terms used and misused by current marketing (especially the bitcoin bro grifters who saw AI as an out of a bad set of assets), but there actually is clarity to the terms if one considers their origins.
Statistics - stuff I can do in Excel as long as no one asks for an underlying proof involving integration.
Machine Learning - stuff I apply with some understanding.
AI - stuff I apply without understanding.