A new mathematical model has brought together the physics and chemistry of highly promising lithium-metal batteries, providing researchers with plausible, fresh solutions to a problem known to cause degradation and failure.
Stanford Institute for Human-Centered Artificial Intelligence —
A novel jury learning system lets content moderators explicitly choose which people to listen to when training machine learning systems to recognize toxic speech.
Stanford Institute for Human-Centered Artificial Intelligence —
By comparing the most energy-efficient running speeds of recreational runners in a lab to the preferred, real-world speeds measured by wearable trackers, Stanford scientists found that runners prefer a low-effort pace – even for short distances.
Watch a discussion of the promise and pitfalls of using AI to bring life-saving drugs to market, including a look at justice and equity in drug research and access.
Autonomous drones that collect data based on scientific machine learning models could play a pivotal role in reducing the uncertainty of sea-level rise.
Using artificial intelligence to analyze vast amounts of data in atomic-scale images, Stanford researchers answered long-standing questions about an emerging type of rechargeable battery posing competition to lithium-ion chemistry.
A study examined the gap between the availability and accessibility of AI-enabled communication tools such as predictive texting, and found that internet access, age and user speech characteristics were barriers to use.
Stanford Institute for Human-Centered Artificial Intelligence —
