AI-based screening method could boost speed of new drug discovery

Developing life-saving medicines can take billions of dollars and decades of time, but researchers are aiming to speed up this process with a new artificial intelligence-based drug screening process they’ve developed. Using a method that models drug and target protein interactions using natural language processing techniques, the researchers achieved up to 97% accuracy in identifying …

Using AI and robots to speed up optimization of new battery development

A team of researchers at Carnegie Mellon University has developed a new approach to speeding up the process of creating ever more optimized batteries. In their paper published in the journal Nature Communications, the group describes how they paired a unique type of robot with an AI learning system to create ever more useful non-aqueous …

PhysioMTL: Personalizing Physiological Patterns using Optimal Transport Multi-Task Regression

Heart rate variability (HRV) is a practical and noninvasive measure of autonomic nervous system activity, which plays an essential role in cardiovascular health. However, using HRV to assess physiology status is challenging. Even in clinical settings, HRV is sensitive to acute stressors such as physical activity, mental stress, hydration, alcohol, and sleep. Wearable devices provide …

Toward Supporting Quality Alt Text in Computing Publications

While researchers have examined alternative (alt) text for social media and news contexts, few have studied the status and challenges for authoring alt text of figures in computing-related publications. These figures are distinct, often conveying dense visual information, and may necessitate unique accessibility solutions. Accordingly, we explored how to support authors in creating alt text …

From principles to actions: building a holistic approach to AI governance

Today AI permeates every aspect of business function. Whether it be financial services, employee hiring, customer service management or healthcare administration, AI is increasingly powering critical workflows across all industries. But with greater AI adoption comes greater challenges. In the marketplace we have seen numerous missteps involving inaccurate outcomes, unfair recommendations, and other unwanted consequences. …

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Quantization for Fast and Environmentally Sustainable Reinforcement Learning

Posted by Srivatsan Krishnan, Student Researcher, and Aleksandra Faust, Senior Staff Research Scientist, Google Research, Brain Team Deep reinforcement learning (RL) continues to make great strides in solving real-world sequential decision-making problems such as balloon navigation, nuclear physics, robotics, and games. Despite its promise, one of its limiting factors is long training times. While the …