New NVIDIA AI Blueprints for building agentic AI applications are poised to help enterprises everywhere automate work.
With the blueprints, developers can now build and deploy custom AI agents. These AI agents act like “knowledge robots” that can reason, plan and take action to quickly analyze large quantities of data, summarize and distill real-time insights from video, PDF and other images.
The team found that the sharing of information that defines entanglement occurs across whole groups of fundamental particles called quarks and gluons within a proton.
“Before we did this work, no one had looked at entanglement inside of a proton in experimental high-energy collision data,” team member and Brookhaven Lab physicist Zhoudunming Tu said in a statement. “For decades, we’ve had a traditional view of the proton as a collection of quarks and gluons, and we’ve been focused on understanding so-called single-particle properties, including how quarks and gluons are distributed inside the proton.
Now, with evidence that quarks and gluons are entangled, this picture has changed. We have a much more complicated, dynamic system.
Advances in technology raise questions about the need to send people to space — and the risks and cost.
Studying a diverse and peculiar genus of mice offers researchers a window into the genetic and neural underpinnings of behavior.
Summary: A new study has identified a biomarker, DTI-ALPS, which connects glymphatic system dysfunction to vascular dementia. By analyzing over 3,750 participants, researchers found that lower DTI-ALPS scores correlated with worse executive function, highlighting the glymphatic system’s role in clearing brain waste.
The study also uncovered a potential pathway linking impaired waste clearance to cognitive decline, mediated by free water accumulation in white matter. These findings provide a robust tool for clinical trials and potential interventions, including lifestyle changes and medications, to enhance glymphatic function and treat vascular dementia.
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Multimodal retrieval-augmented generation (RAG) is transforming how AI applications handle complex information by merging retrieval and generation capabilities across diverse data types, such as text, images, and video.
Unlike traditional RAG, which typically focuses on text-based retrieval and generation, multimodal RAG systems can pull in relevant content from both text and visual sources to generate more contextually rich, comprehensive responses.
This article outlines examples of where AI has been utilized to predict disease outbreaks and how AI models could help inform future strategies for controlling the spread of infectious diseases to prevent possible pandemics.
AI’s contribution to pandemic preparedness
In August 2024, the World Health Organization (WHO) updated its list of pathogens that could spark the next pandemic, which grew to include more than 30 pathogens. The microorganisms were selected based on available evidence showing them to be highly transmissible and virulent, with limited access to vaccines and treatments. While some pathogens on the list may never cause an epidemic, the growing number of pathogens of concern highlights the need for new tools to help predict and control the spread of infectious diseases.
John Larison’s new novel The Ancients suggests some societies are built for cataclysm.
