Due to the explosive growth of artificial intelligence, it is estimated that data centers will consume up to 12% of total U.S ...

Researchers have developed a feature selection-based solar irradiance forecasting method to improve the operation of stand-alone photovoltaic systems. The approach uses a bidirectional long short-term ...

At AACR 2026, researchers discussed the promise and challenges of bringing AI-powered tools into cancer research and clinical ...

AI buzz is everywhere—every company seems to be branding itself as AI-driven, and we continue to marvel at humanoids, ChatGPT-like LLM engines and the remarkable other feats machines are accomplishing ...

MIT and MIT-IBM Watson AI Lab researchers have developed EnergAIzer, a tool that predicts the energy use of AI workloads on GPUs in seconds, aiming to improve data center efficiency. The method could ...

Patients with myelodysplastic syndromes (MDS) exhibit diverse disease trajectories necessitating different clinical approaches ranging from watch-and-wait strategies to hematopoietic stem cell ...

Researchers at the Korea Advanced Institute of Science and Technology have developed a brain-inspired warmup training method that helps AI models better align their confidence with prediction accuracy ...

Use of AlphaFold 2 to predict stabilizing mutations for the R337H variant in the tetramerization domain of TP53. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract ...