Today’s most advanced AI models have many flaws, but decades from now, they will be recognized as the first true examples of artificial general intelligence.
LLMs are not chatbots, they’re models. ChatGPT/Claude/Bard are chatbots which use LLMs as part of their implementation. I would argue in favor of the article because, while they aren’t particularly intelligent, they are general-purpose and exhibit some level of intelligence and thus qualify as “general intelligence”. Compare this to the opposite, an expert system like a chess computer. You can’t even begin to ask a chess computer to explain what a SQL statement does, the question doesn’t even make sense. But LLMs are capable of being applied to virtually any task which can be transcribed. Even if they aren’t particularly good, compared to GPT-2 which read more like a markov chain they at least attempt to complete the task, and are often correct.
LLMs are capable of being applied to virtually any task which can be transcribed
Where “transcribed” means using any set of tokens, be it extracted from human written languages, emojis, pieces of images, audio elements, spatial positions, or any other thing in existence that can be divided and represented by tokens.
PS: actually… why “in existence”? Why not throw in some “customizable tokens” into an LLM, for it to come up with whatever meaning it fancies for them?
LLMs are not chatbots, they’re models. ChatGPT/Claude/Bard are chatbots which use LLMs as part of their implementation. I would argue in favor of the article because, while they aren’t particularly intelligent, they are general-purpose and exhibit some level of intelligence and thus qualify as “general intelligence”. Compare this to the opposite, an expert system like a chess computer. You can’t even begin to ask a chess computer to explain what a SQL statement does, the question doesn’t even make sense. But LLMs are capable of being applied to virtually any task which can be transcribed. Even if they aren’t particularly good, compared to GPT-2 which read more like a markov chain they at least attempt to complete the task, and are often correct.
Where “transcribed” means using any set of tokens, be it extracted from human written languages, emojis, pieces of images, audio elements, spatial positions, or any other thing in existence that can be divided and represented by tokens.
PS: actually… why “in existence”? Why not throw in some “customizable tokens” into an LLM, for it to come up with whatever meaning it fancies for them?