Leading Computer Scientists Debate the Next Steps for AI in 2021
An Anonymous Coward writes:
Leading computer scientists debate the next steps for AI in 2021:
The 2010s were huge for artificial intelligence, thanks to advances in deep learning, a branch of AI that has become feasible because of the growing capacity to collect, store, and process large amounts of data. Today, deep learning is not just a topic of scientific research but also a key component of many everyday applications.
But a decade's worth of research and application has made it clear that in its current state, deep learning is not the final solution to solving the ever-elusive challenge of creating human-level AI.
What do we need to push AI to the next level? More data and larger neural networks? New deep learning algorithms? Approaches other than deep learning?
This is a topic that has been hotly debated in the AI community and was the focus of an online discussion Montreal.AI held [in December 2020]. Titled AI debate 2: Moving AI forward: An interdisciplinary approach," the debate was attended by scientists from a range of backgrounds and disciplines.
Approaches discussed include "hybrid artificial intelligence" (deep learning combined with preprogrammed rules), taking "inspiration from evolution," using "reinforcement learning," and adding to AI "world knowledge and common sense."
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