Claims of AGI imply that LLM's have intelligence. They don't, they are fancy probability machines. They don't THINK the way we do, they just do 200 matrix multiplications until their training data is massaged into what you need. They don't dream, they don't remember what you tell them. Even if you write one sentence, 'attention' means they will ignore half of what you say and key in on the wrong thing. This just happened to me today on a frontier model.
I'm not saying that AGI is impossible, but the focus on LLM's is probably not the right approach. I don't think we will ever make it until we understand the human mind better.
Do you think your brain doesn't do a type of gradient descent, trying to fit its little predictive algorithms to its senses? Do you think you aren't a fancy probability machine with overinflated self-esteem?
An average LLM of today has better reading comprehension than an average human, and the gap only grows release to release.
"Understand the human mind" turned out to be a distractor. The bitter lesson won: you can take a "good enough" AI architecture, burn a shitton of data into it with an unholy amount of training compute, and get halfway to AGI - no "understand the brain" required. LLMs are so fried in imitation learning on human-generated data they even inherit humanlike failure modes.
I mean I can write a non-llm program that "has better reading comprehension than an average human" depending on what you think reading comprehension means. Today I went to ask an LLM some very simple questions, stuff you can google and "do these lines have X word in it" and it failed to answer pretty spectacularly several times in a row, so I'm just not feeling the LLMs are superior intellgence today.
Because if so, I'm pretty sure any frontier LLM is better at evaluating AI capabilities than you are.