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While writers like me struggle to make ends meet, Hollywood studios get rich off the content we create.

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AI can be terrifying when used in horrible ways.

Machine-learning systems with far-reaching potential application in medicine, agriculture, materials science and more from Google sister-company DeepMind and from a rival academic group are now open source and freely accessible.

I expect AlphaFold2 and its progeny will soon be the methods of choice to determine protein structures before resorting to experimental techniques that require painstaking, laborious work on expensive instrumentation.

Brilliant at what they do, taken into unfamiliar terrain Deep Neural Networks are fundamentally brittle. AI researchers say they are making progress in fixing the flaws, but acknowledge that they’re still groping for new techniques.

Google will not pursue Project Maven because the backlash has been terrible for the company. Thousands of employees have signed a petition asking Google to cancel the contract and dozens of employees have resigned in protest.

A new idea called the “information bottleneck” is helping to explain the puzzling success of today’s artificial-intelligence algorithms — and might also explain how human brains learn.