Aug 11, 2021

6 Posts

Series of images showing AI research labs' campuses
Aug 11, 2021

Fresh Funds for U.S. Research: The U.S. plans to build new civilian AI research labs.

The U.S. plans to build nearly a dozen new civilian AI research labs. The U.S. National Science Foundation (NSF) committed $220 million to fund 11 National Artificial Intelligence Research Institutes, complementing seven other AI research institutes that were established last year.
Math equations
Aug 11, 2021

The Batch: AI Recognizes Race in X-Rays, Robots Do Bees' Work, Transformers Pay Closer Attention, New Research Centers

How much math do you need to know to be a machine learning engineer? It’s always nice to know more math! But there’s so much to learn that, realistically, it’s necessary to prioritize.
Different x-rays and CT scans displayed
Aug 11, 2021

AI Sees Race in X-Rays

Researchers from Emory University, MIT, Purdue University, and other institutions found that deep learning systems trained to interpret x-rays and CT scans also were able to identify their subjects as Asian, Black, or White.
Graph showing Expire-span which enables attention to ignore tokens that aren’t useful to the task at hand
Aug 11, 2021

Sharper Attention: NLP transformer technique for more Efficient token usage.

Self-attention enables transformer networks to track relationships between distant tokens — such as text characters — in long sequences, but the computational resources required grow quadratically with input size.
Video showing how robots from Israeli startup Arugga Farming work
Aug 11, 2021

To Bee or Not to Bee: AI farm robots help to pollinate tomatoes.

Insects that spread pollen to fruiting plants are in trouble. A possible alternative: Robots. Farmers in Australia and the U.S. are using robots from Israeli startup Arugga Farming to pollinate greenhouse tomatoes.
Board with math equations
Aug 11, 2021

How to Learn Math for Machine Learning

How much math do you need to know to be a machine learning engineer? It’s always nice to know more math! But there’s so much to learn that, realistically, it’s necessary to prioritize.

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