14 Posts
After years of trailing other tech giants in AI, Apple has a new ambition: to become the industry’s leading purveyor of products powered by machine learning. In an interview with Ars Technica, the company’s AI chief argues that its pro-privacy.
After years of trailing other tech giants in AI, Apple has a new ambition: to become the industry’s leading purveyor of products powered by machine learning. In an interview with Ars Technica, the company’s AI chief argues that its pro-privacy.
Earlier this week, I asked a question on social media: What is the most important problem that the AI community should work on? Thousands of you responded. The most frequently mentioned themes included...
Earlier this week, I asked a question on social media: What is the most important problem that the AI community should work on? Thousands of you responded. The most frequently mentioned themes included...
Bias arises in machine learning when we fit an overly simple function to a more complex problem. A theoretical study shows that gradient descent itself may introduce such bias and render algorithms unable to fit data properly.
A major retailer’s AI-powered surveillance program apparently targeted poor people and minorities. Rite-Aid, a U.S.-based pharmacy chain, installed face recognition systems in many of its New York and Los Angeles stores.
A major retailer’s AI-powered surveillance program apparently targeted poor people and minorities. Rite-Aid, a U.S.-based pharmacy chain, installed face recognition systems in many of its New York and Los Angeles stores.
Earlier this week, I asked a question on social media: What is the most important problem that the AI community should work on? Thousands of you responded. The most frequently mentioned themes included...
Neural networks learned to tell one bird from another, enabling scientists to study their behavior in greater detail. Researchers from universities in Europe and Africa trained eural networks to recognize individual birds with up to 90 percent accuracy.
With the rise of AI-driven surveillance, anonymity is in fashion. Researchers are working on clothing that evades face recognition systems and designed a t-shirt that tricks a variety of object detection models into failing to spot people.
Earlier this week, I asked a question on social media: What is the most important problem that the AI community should work on? Thousands of you responded. The most frequently mentioned themes included...
Neural networks learned to tell one bird from another, enabling scientists to study their behavior in greater detail. Researchers from universities in Europe and Africa trained eural networks to recognize individual birds with up to 90 percent accuracy.
With the rise of AI-driven surveillance, anonymity is in fashion. Researchers are working on clothing that evades face recognition systems and designed a t-shirt that tricks a variety of object detection models into failing to spot people.
Bias arises in machine learning when we fit an overly simple function to a more complex problem. A theoretical study shows that gradient descent itself may introduce such bias and render algorithms unable to fit data properly.
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