Will deep learning discover new medicines? Startups — and big-pharma partners — are betting on it. The problem: In theory, there’s a pharmacological cure for just about any ailment. In practice, discovering those therapies takes years and billions of dollars.

The wearable revolution is helping doctors figure out what’s troubling your ticker — thanks to deep learning. The problem: Arrhythmias, a range of conditions in which the heart beats too fast, too slow, or erratically, can cause heart attack or stroke.

Are your scientist friends intimidated by machine learning? They might be inspired by a primer from one of the world’s premier tech titans. Former Google CEO Eric Schmidt and Cornell PhD candidate Maithra Raghu school scientists in machine learning in a sprawling overview.

AI experts convened to discuss how to combat the coronavirus crisis. An online conference hosted by Stanford University’s Institute for Human-Centered AI explored how machine learning is being deployed to address this pandemic — and prepare for the next one.

Chemists typically develop new antibiotics by testing close chemical relatives of tried-and-true compounds like penicillin. That approach becomes less effective, though, as dangerous bacteria evolve resistance to those very chemical structures. Instead, researchers enlisted neural networks.

Every second counts when a patient’s skull is open in the operating room. A new technique based on deep learning can shorten some brain surgeries. During brain cancer operations, surgeons must stop in mid-operation for up to a half hour while a pathologist analyzes the tumor tissue.

Chinese tech giants have opened their AI platforms to scientists fighting coronavirus. Alibaba Cloud and Baidu are offering a powerful weapon to life-science researchers working to stop the spread of the illness officially known as Covid-19: free access to their computing horsepower and tools.

A drug designed by AI has been approved for testing in humans. A UK startup focused on automated drug discovery teamed up with a Japanese pharmaceutical company to produce a new medicine for obsessive compulsive disorder.

A protein’s biological function depends largely on its three-dimensional shape, but deducing its shape from its sequence of amino acids has been a longstanding problem. Researchers at DeepMind reveal how they used deep learning to solve the puzzle.

Computer vision has potential to spot cancer earlier and more accurately than human experts. A new system surpassed human accuracy in trials, but critics aren’t convinced.

Artificial intelligence has moved from the age of discovery to the age of implementation. Among our invested portfolios, primarily in China, we see flourishing applications using AI and automation in banking, finance, transportation, logistics, supermarkets, restaurants, warehouses, factories...

Weak supervision is the practice of assigning likely labels to unlabeled data using a variety of simple labeling functions. Then supervised methods can be used on top of the now-labeled data.

Drugs undergo rigorous experimentation and clinical trials to gain regulatory approval, while dietary supplements get less scrutiny. Even when a drug study reveals an interaction with supplements, the discovery tends to receive little attention.

Skin conditions are the fourth-largest cause of nonfatal disease worldwide, but access to dermatological care is sparse. A new study shows that a neural network can do front-line diagnostic work.

Microscopes outfitted with AI-driven augmented reality could improve the accuracy of cancer diagnoses. Google Health developed an attachment for analog microscopes that outlines signs of breast and prostate cancer in real time.