A machine learning framework can distinguish molecules made by biological processes from those formed through non-biological ...
The study demonstrates machine learning's role in predicting compressive strength of rice husk ash concrete, aiding the shift ...
Treating annotation as a data understanding problem, rather than a labeling workflow challenge, can systematically drive down error rates and reduce the time and cost of producing high-quality data ...
By using reinforcement learning, researchers train virtual agent to determine the best time to administer medication based on ...
Yoshua Bengio, considered by many to be one of the godfathers of AI, has long been at the forefront of machine-learning ...
Ultrafiltration membranes used in pharmaceutical manufacturing and other industrial processes have long relied on separating molecules by size. Now, Cornell researchers have created porous materials ...
The whitepaper identifies three major pitfalls in modern bioinformatics: the compositional data trap, the mirage of feature importance, and the overreach of generative AI. Each contributes to the high ...
We show that, compared with surgeon predictions and existing risk-prediction tools, our machine-learning model can enhance ...
In two separate blog posts, the Menlo Park-based tech giant detailed the new AI models. There are three models in total. SAM 3 for image and video tracking and segmentation, SAM 3D Objects for ...
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