American researchers from the University of Michigan have developed a new text recognition test, generated by AI and the one created by man.

Recognizing AI-generated content from human-generated content is not an easy task. There are no so many tools, that can effectively distinguish between the two, generated by AI from the human-made and avoid false accusations.

The new test by American researchers may be especially useful for scientists and students, who are increasingly faced with the fact that the works they create are perceived as generated by artificial intelligence. The developers have named their tool «Liketropy», as the theoretical basis of the method includes the statistical ideas of likelihood and entropy.

Dark days ahead, or perhaps already here.

A newly developed generative AI model is helping researchers explore protein dynamics with increased speed. The deep learning system, called BioEmu, predicts the full range of conformations a protein can adopt, modeling the structural ensembles that underlie protein function.

The work, in a paper titled “Scalable emulation of protein equilibrium ensembles with generative deep learning,” was published in Science. Researchers developed BioEmu as a high-speed emulator of protein motion, capable of generating thousands of conformational states in just one GPU-hour, significantly outperforming traditional molecular dynamics (MD) simulations.

Understanding protein function has been a challenge, often hinging not on a single structural component of the protein, but on the combined ensemble of shapes within the protein. Proteins frequently shift between different conformations depending on their interactions or environment, which has been a challenge for other methods to capture accurately.