How ‘less-than-one-shot learning’ could open up new venues for machine learning research

If I told you to imagine something between a horse and a bird—say, a flying horse—would you need to see a concrete example? Such a creature does not exist, but nothing prevents us from using our imagination to create one: the Pegasus. The human mind has all kinds of mechanisms to create new concepts by combining abstract and concrete knowledge it has of the real world. We can imagine existing things that we might have never seen (a horse with a long neck — a giraffe), as well as things that do not exist in real life (a winged serpent… This story continues at The Next Web

How ‘less-than-one-shot learning’ could open up new venues for machine learning research

If I told you to imagine something between a horse and a bird—say, a flying horse—would you need to see a concrete example? Such a creature does not exist, but nothing prevents us from using our imagination to create one: the Pegasus. The human mind has all kinds of mechanisms to create new concepts by combining abstract and concrete knowledge it has of the real world. We can imagine existing things that we might have never seen (a horse with a long neck — a giraffe), as well as things that do not exist in real life (a winged serpent…

This story continues at The Next Web