- cross-posted to:
- technology@lemmy.ml
- cross-posted to:
- technology@lemmy.ml
cross-posted from: https://lemmy.ml/post/20858435
Will AI soon surpass the human brain? If you ask employees at OpenAI, Google DeepMind and other large tech companies, it is inevitable. However, researchers at Radboud University and other institutes show new proof that those claims are overblown and unlikely to ever come to fruition. Their findings are published in Computational Brain & Behavior today.
@ContrarianTrail
> A chess engine is intelligent in one thing: playing chess
No. That’s not how the adjective “intelligent” works, outside of marketing drivel of course (“intelligent washing machine” etc).
> Artificial General Intelligence (AGI) is the artificial version of human cognitive capabilities
Can you give a definition of “intelligence” or “human cognitive abilities” that would allow us to somehow unequivocably establish that “X is intelligent” or “X has human cognitive abilities”?
You’re right that we need a clear definition of intelligence if we are to make any predictions about achieving AGI. The researchers behind this article appear to mean “human-level cognition” which doesn’t seem to be a particularly objective or useful yardstick. To begin with, which human are we talking about? If they’re talking about an idealised maximally intelligent human, then I don’t think we should be surprised that we aren’t about to achieve that. The goal is not to recreate human cognition as if that’s some kind of holy grail. The goal is to make intelligent systems which can give results which are at least as good as what would be produced by a skilled and well-trained human working on the same problem.
Can I ask you how you would define intelligence? And in particular, how would you - if you would at all - differentiate intelligence from being clever, or from being well educated?
IIRC, within computer science, which is the field most heavily driving AI design and research forward, an ‘intelligent agent’ is essentially defined as any ‘agent’ which takes external stimulai from a collection of sensors in some form of environment, processes that stimulai in a dynamic fashion (one of the criteria IIRC is a branching decision tree based on the stimulai), and then applies that processing to a collection of affectors in the environment.
Yes, this definition is an extremely low bar and includes a massive amount of code, software and scripts. It also includes basic natural intelligences such as worms, ants, amoeba, and even viruses. One example of mechanical AI are some of Theo Jansen’s StrandBeasts
@JayDee so two things.
First: sure, we can redefine words in any way we want, but then:
talking about “AI” becomes much less interesting if it merely means “walking a decision tree based on data coming from external sensors”
the whole talk about “intelligence” becomes a bait-and-switch, as the conversation started with the term “intelligence” being used in the general sense we tend to apply to people and some animals.
I am not bait-and-switching here. The switchers were the business-minded grifters which made the term synonymous with LLMs and eventually destroyed its meaning completely.
The definition I gave is from the most popular and widely used CS textbook on AI and has been the meaning used in the field since the early 90s. It’s why videogame NPCs are always called AI, because they fit the conventional CS definition, and were one of the major things it was about the most.
As for your ‘1’, AI is a wide-but-very-specialized field and pertains from everything from robots to text autocomplete. If you want the most out of it, you need to get down into the nitty gritty and really research the field.
On a Seperate note, while AI safety, AGI, and the risk of the intelligence explosion are somewhat related to computer science’s pursuit of AI systems, they are much more philosophical currently, and adhere to much vaguer definitions of AI, Such as Alan Turing’s.