Over the past few days, I’ve watched my productivity drop (don’t tell my boss) a fairly huge amount owing to a sudden explosion of consumer-friendly and highly memeable artificial intelligence (AI) machine learning (ML) tools [… Read more ]
According to observations, children with autism frequently speak more slowly than similarly developing kids. They differ in their speech in other ways, most notably in tone, intonation, and rhythm. It is very challenging to consistently [… Read more ]
With the massive growth of machine learning (ML)-backed services, the term MLops has become a regular part of the conversation — and with good reason. Short for “machine learning operations,” MLops refers to a broad set of [… Read more ]
A study published in The Lancet Digital Health led by UNC School of Medicine’s Emily R. Pfaff, PhD, shows how the National COVID Cohort Collaborative used XGBoost machine learning models to better define long COVID [… Read more ]
Google is integrating AR into many Google products, from Google Lens to multisearch, scene exploration, and Live and immersive views in Maps. Google I/O 2022, Google’s largest developer conference, kicked off with a keynote speech [… Read more ]
Federated learning is a machine learning technique that trains a model over several dispersed nodes or hosts, as the name suggests. Each node utilizes its own training data. If the model parameters are shared between [… Read more ]
Researchers create a mathematical framework to evaluate explanations of machine-learning models and quantify how well people understand them. Modern machine-learning models, such as neural networks, are often referred to as “black boxes” because they are [… Read more ]
MIT research scientists Pablo Rodriguez-Fernandez and Nathan Howard have just completed one of the most demanding calculations in fusion science — predicting the temperature and density profiles of a magnetically confined plasma via first-principles simulation [… Read more ]
Data limitations, evaluation issues, and publishing incentives may be slowing the clinical progress of machine learning in medical imaging, a new study finds. April 13, 2022 – Though research on machine learning use in medical imaging has [… Read more ]
The base rate fallacy is a kind of fallacy that is also known as base rate bias and base rate neglect. This kind of fallacy has information about the base rate and specific information. There [… Read more ]
Reinforcement learning is one of the fascinating fields of computer science, and it has proven useful in solving some of the toughest challenges of artificial intelligence and robotics. Some scientists believe that reinforcement learning will [… Read more ]
The growing digitization of nearly every aspect of our world and lives has created immense opportunities for the productive application of machine learning and data science. Organizations and institutions across the board are feeling the need to [… Read more ]
Most workers want AI to help them get their jobs done. But attitudes toward how they experience AI in their lives, where they prefer to find it and who they trust to sell them its [… Read more ]
Many machine learning tasks require high-quality data, such as assessing damage in a satellite that negatively affects a model’s performance. Datasets can cost millions of dollars to create if useable data exists, and even the [… Read more ]
Traditional algorithms power complicated computational tools like machine learning. A new approach, called algorithms with predictions, uses the power of machine learning to improve algorithms. lgorithms — the chunks of code that allow programs to [… Read more ]
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