Efficient technique improves machine-learning models’ reliability

Powerful machine-learning models are being used to help people tackle tough problems such as identifying disease in medical images or detecting road obstacles for autonomous vehicles. But machine-learning models can make mistakes, so in high-stakes settings it’s critical that humans know when to trust a model’s predictions. source: https://news.mit.edu/2023/improving-machine-learning-models-reliability-0213

Future of AI: Machines are Intelligent Enough to Execute Complex Tasks Themselves

AI is already powering search engines, online translators, virtual assistants, and numerous marketing and sales decisions Artificial Intelligence (AI) essentially means developing machines with the ability to think strategically and act for them. AI is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI Read more…

Machine Learning to Optimize Product Quality Measurement

Researchers have used machine learning and two experimental designs to optimize a common critical quality attribute of biological therapies. Eliza Yeung, PhD, associate director of process characterization at contract manufacturer Cytovance Biologics, and another researcher relied on statistical software to create two experimental designs to analyze glycosylation, a critical quality Read more…