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Self-Taught AI Shows Similarities to How the Brain Works
Self-supervised learning allows a neural network to figure out for itself what matters. The process might be what makes our own brains so successful.
The Computer Scientist Challenging AI to Learn Better
Christopher Kanan is building algorithms that can continuously learn over time — the way we do.
By Exploring Virtual Worlds, AI Learns in New Ways
Intelligent beings learn by interacting with the world. Artificial intelligence researchers have adopted a similar strategy to teach their virtual agents new tricks.
Will Transformers Take Over Artificial Intelligence?
A simple algorithm that revolutionizes how neural networks approach language is now taking on image classification as well. It may not stop there.
AI Overcomes Stumbling Block on Brain-Inspired Hardware
Algorithms that use the brain’s communication signal can now work on analog neuromorphic chips, which closely mimic our energy-efficient brains.
Computer Scientists Prove Why Bigger Neural Networks Do Better
Two researchers show that for neural networks to be able to remember better, they need far more parameters than previously thought.
Researchers Build AI That Builds AI
By using hypernetworks, researchers can now preemptively fine-tune artificial neural networks, saving some of the time and expense of training.
What Does It Mean for AI to Understand?
It’s simple enough for AI to seem to comprehend data, but devising a true test of a machine’s knowledge has proved difficult.
AI Researchers Fight Noise by Turning to Biology
Tiny amounts of artificial noise can fool neural networks, but not humans. Some researchers are looking to neuroscience for a fix.