Aug 12, 2020

6 Posts

Different Apple products using augmented reality
Aug 12, 2020

Apple Kicks AI Into High Gear

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.
2 min read
Apple's AI Strategy, Retail Surveillance, Clothes That Fight Face Recognition, Suboptimal Optimizers
Aug 12, 2020

Apple's AI Strategy, Retail Surveillance, Clothes That Fight Face Recognition, Suboptimal Optimizers

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:
10 min read
Images and data related to a t-shirt that tricks a variety of object detection models into failing to spot people
Aug 12, 2020

Hidden in Plain Sight

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.
2 min read
Data related to AI technology capable of spotting birds with sound and sight
Aug 12, 2020

Birdwatching With AI

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.
1 min read
Rite-Aids face recognition system
Aug 12, 2020

Retail Surveillance Revealed

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.
1 min read
Series of images with graphs and data related to optimization algorithms
Aug 12, 2020

When Optimization is Suboptimal

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.
2 min read

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