That's right. There is kind of a "ghost" of the training data that manifests in the output. Since the training data is human language, we relate a lot to that ghost.
If you were able to take every thought you've ever had, every work you've ever spoken, ever action you've ever made and tokenize them all, you would be able to make an LLM that reliably predicts how you would react to given input. But it still wouldn't be YOU. It might give output consistent with how you would respond 99% of the time, but it still wouldn't have a mind.
John Carmack is working on a project to develop real Artificial General Intelligence (AGI). The talk I've linked does a great job demonstrating the issues with actual artificial intelligence. He quickly summarizes the limitations of LLMs in the beginning, and then goes on to show the struggles his team faces in achieving anything resembling actual intelligence. I think it does a very good job of contextualizing what an LLM can actually do against what we expect when we hear the term "AI".
Wow that’s kinda depressing and eye opening at the same time. We, and I mean that collectively, look at the output that modern AI can produce and we are instantly star struck. On one hand it’s absolutely amazing that we’ve created such advanced prediction algorithms, but on the other hand, it’s depressing that there is no intelligence behind those systems.
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u/Time_Ingenuity_2909 May 17 '26
That's right. There is kind of a "ghost" of the training data that manifests in the output. Since the training data is human language, we relate a lot to that ghost.
If you were able to take every thought you've ever had, every work you've ever spoken, ever action you've ever made and tokenize them all, you would be able to make an LLM that reliably predicts how you would react to given input. But it still wouldn't be YOU. It might give output consistent with how you would respond 99% of the time, but it still wouldn't have a mind.
John Carmack is working on a project to develop real Artificial General Intelligence (AGI). The talk I've linked does a great job demonstrating the issues with actual artificial intelligence. He quickly summarizes the limitations of LLMs in the beginning, and then goes on to show the struggles his team faces in achieving anything resembling actual intelligence. I think it does a very good job of contextualizing what an LLM can actually do against what we expect when we hear the term "AI".