Less supervision, better results: Study shows AI models generalize more effectively on their own
Training LLMs and VLMs through reinforcement learning delivers better results than using hand-crafted examples.
Machine learning and physics merge to enhance liquid-gas phase transition predictions
Combining concepts from statistical physics with machine learning, researchers at the University of Bayreuth have shown that ...
Electronic Design14h
Edge AI: Revolutionizing Real-Time Data Processing and Automation
As demand for real-time intelligence grows, edge AI is well-positioned to continue its substantial impact in many industries.
eLife1d
Bridging the Gap in Cancer Cell Behavior Against Matrix Stiffening: Insights from a Trizonal Model
Laboratory for Research on the Structure of Matter (LRSM), University of Pennsylvania, Philadelphia, United States ...
aha.org1d
Early Disease Detection: 3 Tech Trends to Watch
One trend CB Insights analysts are watching is how AI is helping patients engage with health systems before the diagnostic ...
Brain-inspired neural networks reveal insights into biological basis of relational learning
Humans and certain animals appear to have an innate capacity to learn relationships between different objects or events in ...
Techopedia2d
Diffbot’s AI Model Suggests “Smaller Is Better” for LLMs
Learn whether a smaller Diffbot’s AI model with an innovative GraphRAG AI training technology can solve AI hallucinations for ...
AI and neural networks can reduce wait times for lesion classification in breast cancer patients
One of the most agonizing experiences a cancer patient suffers is waiting without knowing: waiting for a diagnosis, waiting ...