Data science teams working with artificial intelligence and machine learning (AI/ML) face a growing challenge as models become more complex. While Amazon Deep Learning Containers (DLCs) offer robust baseline environments out-of-the-box, customizing them for specific projects often requires significant time and expertise. In this post, we explore how to useContinue Reading
This post is co-written with Zhanghao Wu, co-creator of SkyPilot. The rapid advancement of generative AI and foundation models (FMs) has significantly increased computational resource requirements for machine learning (ML) workloads. Modern ML pipelines require efficient systems for distributing workloads across accelerated compute resources, while making sure developer productivity remainsContinue Reading
Fraud detection remains a significant challenge in the financial industry, requiring advanced machine learning (ML) techniques to detect fraudulent patterns while maintaining compliance with strict privacy regulations. Traditional ML models often rely on centralized data aggregation, which raises concerns about data security and regulatory constraints. Fraud cost businesses over $485.6Continue Reading
Sticking to an exercise routine is a challenge many people face. But a University of Mississippi research team is using machine learning to uncover what keeps individuals committed to their workouts. The team — Seungbak Lee and Ju-Pil Choe, both doctoral students in physical education, and Minsoo Kang, professor ofContinue Reading
This post is co-written with Qing Chen and Mark Sinclair from Radial. Radial is the largest 3PL fulfillment provider, also offering integrated payment, fraud detection, and omnichannel solutions to mid-market and enterprise brands. With over 30 years of industry expertise, Radial tailors its services and solutions to align strategically withContinue Reading
MIT researchers have created a periodic table that shows how more than 20 classical machine-learning algorithms are connected. The new framework sheds light on how scientists could fuse strategies from different methods to improve existing AI models or come up with new ones. For instance, the researchers used their frameworkContinue Reading
Researchers at Rice University have developed a new machine learning (ML) algorithm that excels at interpreting the “light signatures,” or optical spectra, of molecules, materials and disease biomarkers, potentially enabling faster and more precise medical diagnoses and sample analysis. “Imagine being able to detect early signs of diseases like Alzheimer’sContinue Reading
The low-threshold, playful communication of complex scientific content is a challenge. A team from the Game Lab Graz at the Institute of Human-Centred Computing at Graz University of Technology (TU Graz) has developed a solution for this. The learning environment Project Chimera, implemented as a computer game, enables gamified, story-basedContinue Reading
As one of the fastest sports in the world, almost everything is a race in Formula 1® (F1), even the pit stops. F1 drivers need to stop to change tires or make repairs to damage sustained during a race. Each precious tenth of a second the car is in theContinue Reading
Headquartered in São Paulo, Brazil, iFood is a national private company and the leader in food-tech in Latin America, processing millions of orders monthly. iFood has stood out for its strategy of incorporating cutting-edge technology into its operations. With the support of AWS, iFood has developed a robust machine learningContinue Reading
