Women continue to be severely underrepresented in AI. A meta-analysis of research conducted by Synced Review for Women’s History Month found that female participation in various aspects of AI typically hovers between 10 and 20 percent.
Women continue to be severely underrepresented in AI. A meta-analysis of research conducted by Synced Review for Women’s History Month found that female participation in various aspects of AI typically hovers between 10 and 20 percent.
AI is good at tracking objects in two dimensions. A new model processes video from a camera with a depth sensor to predict how objects move through space.
AI is good at tracking objects in two dimensions. A new model processes video from a camera with a depth sensor to predict how objects move through space.
Wouldn’t it be great to see around corners? Deep learning researchers are working on it. Researchers developed deep-inverse correlography, a technique that interprets reflected light to reveal objects outside the line of sight.
Wouldn’t it be great to see around corners? Deep learning researchers are working on it. Researchers developed deep-inverse correlography, a technique that interprets reflected light to reveal objects outside the line of sight.
School teachers may not like to hear this, but sometimes you get the best answer by peeking at your neighbor’s paper. A new language model framework peeks at the training data for context when making a prediction.
School teachers may not like to hear this, but sometimes you get the best answer by peeking at your neighbor’s paper. A new language model framework peeks at the training data for context when making a prediction.
Computer scientists are struggling to purge bias from one of AI’s most important datasets. ImageNet’s 14 million photos are a go-to collection for training computer-vision systems, yet their descriptive labels have been rife with derogatory and stereotyped attitudes toward race, gender, and sex.
Which countries are ahead in AI? Many, in one way or another, and not always the ones you might expect. The Stanford Institute for Human-Centered Artificial Intelligence published its 2019 Artificial Intelligence Index, detailing when, where, and how AI is on the rise.
Computer scientists are struggling to purge bias from one of AI’s most important datasets. ImageNet’s 14 million photos are a go-to collection for training computer-vision systems, yet their descriptive labels have been rife with derogatory and stereotyped attitudes toward race, gender, and sex.
Which countries are ahead in AI? Many, in one way or another, and not always the ones you might expect. The Stanford Institute for Human-Centered Artificial Intelligence published its 2019 Artificial Intelligence Index, detailing when, where, and how AI is on the rise.
Many people in the AI community focus on achieving flashy results, like building an agent that can win at Go or Jeopardy. This kind of work is impressive in terms of complexity.
Many people in the AI community focus on achieving flashy results, like building an agent that can win at Go or Jeopardy. This kind of work is impressive in terms of complexity.
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?
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