As AI evolves, experts debate the timeline and implications of achieving superintelligence, with concerns about risks and the need for safe development strategies.
In 2014, the British philosopher Nick Bostrom published a book about the future of artificial intelligence with the ominous title. It proved highly influential in promoting the idea that advanced AI systems — “superintelligences” more capable than humans — might one day take over the world and destroy humanity.Different kinds of AITheir framework lists six levels of AI performance: no AI, emerging, competent, expert, virtuoso and superhuman.
Many recent successes in AI have come from the application of a technique called “deep learning”, which, in simplistic terms, finds associative patterns in gigantic collections of data. Indeed, ” Geoffrey Hinton, for their invention of Hopfield Networks and Boltzmann machine, which are the foundation for many powerful deep learning models used today.
Existing foundation models are not trained in an open-ended way, and existing open-ended systems are quite narrow. This paper also highlights how either novelty or learnability alone is not enough. A new type of open-ended foundation model is needed to achieve superintelligence.So what does all this mean for the risks of AI? In the short term, at least, we don’t need to worry about superintelligent AI taking over the world.
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