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I think a reasonable definition of intelligence is the application of reason on knowledge. An example of a system that is highly knowledgeable but has little to
by Zambyte 2y ago
I think a reasonable definition of intelligence is the application of reason on knowledge. An example of a system that is highly knowledgeable but has little to no reason would be an encyclopedia. An example of a system that is highly reasonable, but has little knowledge would be a calculator. Intelligent systems demonstrate both.
Systems that have general intelligence are ones that are capable of applying reason to an unbounded domain of knowledge. Examples of such systems include: libraries, wikis, and forums like HN. These systems are not AGI, because the reasoning agents in each of these systems are organic (humans); they are more like a cyborg general intelligence.
Artificial general intelligence are just systems that are fully artificial (ie: computer programs) that can apply reason to an unbounded domain of knowledge. We're here, and we have been for years. AGI sets no minimum as to how great the reasoning must be, but it's obvious to anyone who has used modern generative intelligence systems like LLMs that the technology can be used to reason about an unbounded domain of knowledge.
If you don't want to take my word for it, maybe Peter Norvig can be more convincing: https://www.noemamag.com/artificial-general-intelligence-is-already-here/ https://www.noemamag.com/artificial-general-intelligence-is-...
- jimbokun 2y agoExcellent article and analysis. Surprised I missed it. It is very hard to argue with Norvig’s arguments that AGI has been around since at least 2023.
- littlestymaar 2y agoIt's not: whatever the way you define AGI, you cannot just ignore the key letter of the three letters acronym: G stands for “General”. You can argue that for the first time in the history we have an AI that deserves its name (unlike Deep blue or AlphaGo which aren't really about intelligence at all) but you cannot call that Artificial GENERAL Intelligence before it overcomes the “jagged intelligence” syndrome.
- Zambyte 2y agoIt sounds like you have a different definition of "general" in the context of intelligence from the one I shared. What is it?
- Jensson 2y agoGeneral intelligence means it can do the same intellectual tasks as humans can, including learning to do different kinds of intellectual jobs. Current AI can't learn to do most jobs like a human kid can, so its not AGI. This is the original definition of AGI. Some data scientists try to move the goalposts to something else and call something that can't replace humans "AGI". This is a very simple definition that is easy to see when it is fulfilled because then companies can operate without humans.
- Zambyte 2y agoWhat intellectual tasks can humans do that language models can't? Particularly agentic language model frameworks.
- Jensson 2y agoA normal software engineering job? You have access to email and can send code etc. No current model manages anything close to that. Even much simpler jobs can't be automated like that by them. So basically any form of longer term tasks cannot be done by them currently. Short term tasks with constant supervision is about the only things they can do, and that is very limited, most tasks are long term tasks.
- Zambyte 2y ago> You have access to email and can send code etc. No current model manages anything close to that. This is an issue of tooling, not intelligence. Language models absolutely have the power to process email and send (push?) code, should you give them the tooling to do so (also true of human intelligence). > So basically any form of longer term tasks cannot be done by them currently. Short term tasks with constant supervision is about the only things they can do, and that is very limited, most tasks are long term tasks. Are humans that have limited memory due to a condition not capable of general intelligence, xor does intelligence exist on a spectrum? Also, long term tasks can be decomposed into short term tasks. Perhaps automatically, by a language model. Have you actually tried agentic LLM based frameworks that use tool calling for long term memory storage and retrieval, or have you decided that because these tools do not behave perfectly in a fluid environment where humans do not behave perfectly either, that it's "impossible"?
- conception 2y agoI think the thing missing would be memory. The knowledge of current models is more or less static save for whatever you can cram into their context window. I think if they had memory and thus the ability to learn - “oh hey, I’ve already tried to solve a bug in these ways maybe I won’t get stuck in loop on them!” Would be the agi push for me. Real time incorporating new knowledge into the model is the missing piece.
- casey2 2y agoIt needs some kind of low latency world model. Or at least more agent inspired pretraining (I did x and it failed, I did y and It failed, I should try z now) GOOD (I did x and it failed, I did y and it failed, I should try x now) BAD
- fragmede 2y agoWith MCP/tool use you can tell it to save state into an MD file, simulating this. How much that counts is left as an exercise to the reader.
- conception 2y agoIt actually works really well in my experience. But it eats up context. Using 500-600k token windows per inquiry isn’t cheap.
- barrenko 2y agoWe don't have this for humans either, other than the vague pseudoscience of IQ. As I've travelled more, and just grown older in general, I've come to accept a lot of humans as barely sentient.
- literalAardvark 2y agoMore like all humans, most of the time. Actual sentience takes energy that our brain really doesn't like to use. It hardcodes switch statements for behaviours as fast as it can and then coasts until something doesn't match.