Protein structures predicted by artificial intelligence have charted the evolution of the virus family responsible for dengue and hepatitis C.

Researchers at the Cold Spring Harbor Laboratory (CSHL), headed by assistant professor Peter Koo, PhD, and his team, have developed an AI-powered virtual laboratory, cis-regulatory element model explanations (CREME), that allows geneticists to run thousands of virtual experiments with the click of a button. Using CREME, scientists can use the tool to begin identifying and understanding key regions of the genome.

... after having been lulled into a false sense of complacency after there was no AI progress beyond IQ 100 for the 6 months since I started tracking this...I also think all this makes clear that AIs are intelligent, and are reasoning.

GameGen-O represents a notable initial step forward in the realm of open-world video game generation via generative models. It underscores the potential of generative models to serve as an alternative to rendering techniques, which can efficiently combine creative generation with interactive capabilities.

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.

…introduce two new papers featuring our latest artificial intelligence (AI) advances in robot dexterity research: ALOHA Unleashed which helps robots learn to perform complex and novel two-armed manipulation tasks; and DemoStart which uses simulations to improve real-world performance on a multi-fingered robotic hand…ALOHA Unleashed and DemoStart, help robots learn to perform complex tasks that require dexterous movement

...For one, robots can’t come soon enough. For another, they shouldn’t look like us... concerns that Silicon Valley, with its focus on “minimum viable products” and VCs’ general aversion to investing in hardware, will be patient enough to win the global race to give AI a robot body. And much of the money that is being invested is focusing on the wrong things.

LG AI Research Open-Sources EXAONEPath: Transforming Histopathology Image Analysis with a 285M Patch-level Pre-Trained Model for Variety of Medical Prediction, Reducing Genetic Testing Time and Costs

…an experimental design that evaluates research idea generation while controlling for confounders and performs the first head-to-head comparison between expert NLP researchers and an LLM ideation agent. By recruiting over 100 NLP researchers to write novel ideas and blind reviews of both LLM and human ideas, we obtain the first statistically significant conclusion on current LLM capabilities for research ideation: we find LLM-generated ideas are judged as more novel (p < 0.05) than human expert ideas while being judged slightly weaker on feasibility.

New AI system designs proteins that successfully bind to target molecules, with potential for advancing drug design, disease understanding and more.