Lifeboat Foundation

Top quarks and antiquarks produced in the Large Hadron Collider are entangled, a study shows.

Scientists are using ever more sophisticated AI algorithms trained on vast, unlabeled datasets to develop models that can ‘interpret’ biological data to help guide biomolecule design.

Share your videos with friends, family, and the world.

A summary of an argumentative paper by Litt, Eliasmith, Kroon, Weinstein and Thagard.

Randal Koene discusses Whole Brain Emulation on the H+ Magazine podcast. He touches on the subjects of connectomics, neural mapping, optogenetics, and neural prosthesis.

Muir et al. explore threat discrimination in male and female mice and find that, despite similar behavioral acquisition, there are surprising sex differences in the neural encoding that drives suppression of reward seeking under threat.

Single-cell profiling in the human cortex reveals aging-associated transcriptomic changes across all brain cell types, which overlap with effects with Alzheimer’s disease and show a convergent signature with psychopathology across multiple cell types.

The brain dynamically transforms cognitive information. Here the authors build task-performing, functioning neural network models of sensorimotor transformations constrained by human brain data without the use of typical deep learning techniques.

To expand its GPT capabilities, OpenAI released its long-anticipated o1 model, in addition to a smaller, cheaper o1-mini version. Previously known as Strawberry, the company says these releases can “reason through complex tasks and solve harder problems than previous models in science, coding, and math.”

Although it’s still a preview, OpenAI states this is the first of this series in ChatGPT and on its API, with more to come.

The company says these models have been training to “spend more time thinking through problems before they respond, much like a person would. Through training, they learn to refine their thinking process, try different strategies, and recognize their mistakes.”