Research
Stanford Researchers Use AI To Empower Environmental Regulators
Like superheroes capable of seeing through obstacles, environmental regulators may soon wield the power of all-seeing eyes that can identify violators anywhere at any time, according to a new Stanford University-led study. The paper, published the week of April 19 in Proceedings of the National Academy of Sciences (PNAS), demonstrates how artificial intelligence combined with …
Assessing Regulatory Fairness Through Machine Learning
The perils of machine learning – using computers to identify and analyze data patterns, such as in facial recognition software – have made headlines lately. Yet the technology also holds promise to help enforce federal regulations, including those related to the environment, in a fair, transparent way, according to a new study by Stanford researchers. …
Machine Learning Aids In Simulating Dynamics Of Interacting Atoms
Automated data set generation provides a highly diverse sampling of atomic positions for training an accurate and general machine learning model. A revolutionary machine-learning (ML) approach to simulate the motions of atoms in materials such as aluminum is described in this week’s Nature Communications journal. This automated approach to “interatomic potential development” could transform the …
AI Gets Better Every Day. Here’s What That Means For Stopping Hate Speech
The numbers Facebook released today in our latest Community Standards Enforcement Report are evidence of the many ways technology is delivering the kind of progress our world demands. In the final three months of 2020, we did better than ever before to proactively detect hate speech and bullying and harassment content — 97 percent of …
Lab Researchers Explore ‘Learn-By-Calibration’ Approach To Deep Learning To Accurately Emulate Scientific Process
Lawrence Livermore National Laboratory (LLNL) computer scientists have developed a new deep learning approach to designing emulators for scientific processes that is more accurate and efficient than existing methods. In a paper published by Nature Communications, an LLNL team describes a “Learn-by-Calibrating” (LbC) method for creating powerful scientific emulators that could be used as proxies …
IBM Researchers Check AI Bias With Counterfactual Text
From recruitment to credit risk apps, or use in the healthcare and criminal justice system, AI unreliability has been giving researchers headaches for years. We’ve tackled the issue by flipping it upside down. Our team has developed an AI that verifies other AIs’ “fairness” by generating a set of counterfactual text samples and testing machine …
IBM RXN: New AI Model Boosts Mapping Of Chemical Reactions
Just like an astronomer investigates outer space, a chemist explores chemical space — a theoretical territory with all possible known (and unknown) chemical compounds. Researchers estimate chemical space to contain up to 10180 compounds — more than twice the magnitude of the number of atoms in the universe. Currently, the largest public database of molecules synthesized so …
MIT Continues AI Collaboration With Toyota Research Institute
The Toyota Research Institute (TRI) announced that it will be extending its AI research collaboration with MIT. TRI, which also has existing relationships with Stanford and the University of Michigan, has selected 13 additional academic institutions to participate in the next five-year phase of its research initiative. TRI’s next five-year phase involves investing more than …
A New Open Data Set For Multilingual Speech Research
What it is: Facebook AI is releasing Multilingual LibriSpeech (MLS), a large-scale, open source data set designed to help advance research in automatic speech recognition (ASR). MLS is designed to help the speech research community’s work in languages beyond just English so people around the world can benefit from improvements in a wide range of …
Model Analyzes How Viruses Escape The Immune System
One reason it’s so difficult to produce effective vaccines against some viruses, including influenza and HIV, is that these viruses mutate very rapidly. This allows them to evade the antibodies generated by a particular vaccine, through a process known as “viral escape.” MIT researchers have now devised a new way to computationally model viral escape, …