Artificial general intelligence (AGI) is the ability of an intelligent agent to understand or learn __any__ intellectual task that a human being can.
LLMs are nowhere near this. Not even close.
But let's get even more restrictive by looking at the actual required characteristics to declare a system an AGI:
There is wide agreement among artificial intelligence researchers that intelligence is required to do the following:
- reason, use strategy, solve puzzles, and make judgments under uncertainty;
- represent knowledge, including common sense knowledge;
- plan;
- learn;
- communicate in natural language;
- and integrate all these skills towards common goals.
Other important capabilities include:
- input as the ability to sense (e.g. see, hear, etc.), and
- output as the ability to act (e.g. move and manipulate objects, change own location to explore, etc.)
Once again, LLMs are not even scratching the surface of AGI.
Of course if you look at the current version of the page, where the bar has been massively lowered, it might look like AGI is achieved, but that's because the definition has changed, not the technology.
This is not AGI.
> Let's take an old version of the Wikipedia page about AGI, from end of 2022
sure, its not AGI by old wikipedia definition, which imo is human-centric and more definition of superintelligence (requires ability to exceed all existing humans in all tasks). But it is AGI by current wikipedia definition.
That is literally my point... The definition of AGI has been twisted so much by the ones that claim to be on the verge of achieving it that it is not anymore in line with what AGI has always meant.
Reading wikipedia about history of the term, it sounds like term was popularized by this book: https://www.amazon.com/Artificial-General-Intelligence-Cogni... which says that general means "ability so solve variety of tasks in variety of domains", not "all tasks in all domains". So "always meant" is easily challengeable here.
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that definition likely not their's but came from Microsoft when they dumped 10B into OAI and was a condition for revenue sharing clause.
One can argue that AGI is already achieved, LLMs are more proficient and general in knowledge tasks than any specific individual.
This is not AGI.
Let's take an old version of the Wikipedia page about AGI, from end of 2022, before the ChatGPT craze: https://en.wikipedia.org/w/index.php?title=Artificial_genera...
LLMs are nowhere near this. Not even close.
But let's get even more restrictive by looking at the actual required characteristics to declare a system an AGI:
Once again, LLMs are not even scratching the surface of AGI.
Of course if you look at the current version of the page, where the bar has been massively lowered, it might look like AGI is achieved, but that's because the definition has changed, not the technology.
sure, its not AGI by old wikipedia definition, which imo is human-centric and more definition of superintelligence (requires ability to exceed all existing humans in all tasks). But it is AGI by current wikipedia definition.
That is literally my point... The definition of AGI has been twisted so much by the ones that claim to be on the verge of achieving it that it is not anymore in line with what AGI has always meant.
Reading wikipedia about history of the term, it sounds like term was popularized by this book: https://www.amazon.com/Artificial-General-Intelligence-Cogni... which says that general means "ability so solve variety of tasks in variety of domains", not "all tasks in all domains". So "always meant" is easily challengeable here.