Saved by Cullan Ash
Why I don’t think AGI is right around the corner
From chatbot to agent-coworker
What could ambitious unhobbling over the coming years look like? The way I think about it, there are three key ingredients:
1. Solving the “onboarding problem”
GPT-4 has the raw smarts to do a decent chunk of many people’s jobs, but it’s sort of like a smart new hire that just showed up 5 minutes ago: it doesn’t have a... See more
What could ambitious unhobbling over the coming years look like? The way I think about it, there are three key ingredients:
1. Solving the “onboarding problem”
GPT-4 has the raw smarts to do a decent chunk of many people’s jobs, but it’s sort of like a smart new hire that just showed up 5 minutes ago: it doesn’t have a... See more
SITUATIONAL AWARENESS - The Decade Ahead • I. From GPT-4 to AGI: Counting the OOMs
Why transformative artificial intelligence is really, really hard to achieve
thegradient.pub
LLMs are extremely good at a type of knowledge called tacit knowledge (knowledge about something as it pertains to something else) but are extremely poor at pretty much any other type as far as I can see. It just so happens that tacit knowledge also happens to be the type of knowledge that drives natural language so it makes them looks super smart,... See more
Column: These Apple researchers just showed that AI bots can't think, and possibly never will — Apple’s AI researchers gave these AI systems a simple arithmetic problem that schoolkids can solve. The bots flunked.
As we successfully apply simpler, narrow versions of intelligence that benefit from faster computers and lots of data, we are not making incremental progress, but rather picking low-hanging fruit. The jump to general “common sense” is completely different, and there’s no known path from the one to the other.
Erik J. Larson • The Myth of Artificial Intelligence: Why Computers Can’t Think the Way We Do
The many fallacies of 'AI won't take your job, but someone using AI will'
Sangeet Paul Choudaryplatforms.substack.com