Recurrent Neural Network (RNN)

Even if we manage to stop robots from taking over the world, they may still have the last laugh. Researchers at Kyoto University developed a series of neural networks that enable a robot engaged in spoken conversation to chortle along with its human interlocutor.

Let’s get this out of the way: A brain is not a cluster of graphics processing units, and if it were, it would run software far more complex than the typical artificial neural network. Yet neural networks were inspired by the brain’s architecture.

An Android app offers speech recognition model for speech impaired by cerebral palsy, Down syndrome, Parkinson’s disease, stroke, or traumatic brain injury.

In machine learning, an easy task and a more difficult version of the same task — say, a maze that covers a smaller or larger area — often are learned separately.

Neural networks translated a paralyzed man’s brainwaves into conversational phrases. Researchers trained a system to interpret electrical impulses from the brain of a man who had lost the ability to speak 15 years ago, and displayed them as words on a video screen.

IBM’s Watson question-answering system stunned the world in 2011 when it bested human champions of the TV trivia game show Jeopardy! Although the Watson brand has fallen on hard times, the company’s language-processing prowess continues to develop.

Bayes-optimal algorithms always make the best decisions given their training and input, if certain assumptions hold true. New work shows that some neural networks can approach this kind of performance.

Transformer networks are gaining popularity as a high-accuracy alternative to recurrent neural networks. But they can run slowly when they’re applied to long sequences.

AI has added an unlikely language to its catalog of translation capabilities: brain waves. Joseph Makin led a group from the University of California San Francisco to render a person’s neural signals as English text while the person while the person read a sentence aloud.

Are your scientist friends intimidated by machine learning? They might be inspired by a primer from one of the world’s premier tech titans. Former Google CEO Eric Schmidt and Cornell PhD candidate Maithra Raghu school scientists in machine learning in a sprawling overview.

As working from home becomes the new normal, AI may protect you from the sound of coworkers munching while they chat. No more smacking lips and rustling chip bags! Microsoft’s online collaboration platform Teams announced a feature that removes extraneous sounds from videoconferences.

The latest large, pretrained language models rely on trendy layers based on transformer networks. New research shows that these newfangled layers may not be necessary.

The future of machine learning may depend less on amassing ground-truth data than simulating the environment in which a model will operate. Deep learning works like magic with enough high-quality data. When examples are scarce, though, researchers are using simulation to fill the gap.

Reinforcement learning trains models by trial and error. In batch reinforcement learning (BRL), models learn by observing many demonstrations by a variety of actors. But what if one doctor is handier with a scalpel while another excels at suturing?

Amazon, watch your back. There’s a new player in the book business and, unlike Jeff Bezos, it doesn’t need eight hours of sleep a night. The online bookstore Booksby.ai is run entirely by AI. Neural networks write the books, create the cover art, price the merchandise, even write the reviews.