Large genome model: Open source AI trained on trillions of bases

Late in 2025, we covered the development of an AI system called Evo that was trained on massive numbers of bacterial genomes. So many that, when prompted with sequences from a cluster of related genes ...
eLife

Boosting the signal: Expectation-driven gain modulation of preparatory spatial attention

The evidence is solid but not definitive, as the conclusions rely on the absence of changes in spatial breadth and would benefit from clearer statistical justification and a more cautious ...

How to use AI response patterns to build better content

LLM answers vary widely. Here’s how to extract repeatable structural, conceptual, and entity patterns to inform optimization and positioning.
GitHub

A real-time demonstration of learning Adaptable World Models with Latent Actions using the Agno framework.

The development of this repository was inspired by the paper "AdaWorld: Learning Adaptable World Models with Latent Actions". To read the entire paper, visit https ...
IEEE

A Novel Clustering Method for Extracting Representative Photovoltaic Scenarios Considering Power, Energy, and Variability

Abstract: Due to the significant uncertainty in photovoltaic (PV) power generation, grid operation scenarios with a high proportion of PV integration are complex and varied. To accurately extract ...
GitHub

bethington/cheat-engine-server-python

This server operates in READ-ONLY mode for safety. It can read and analyze memory but cannot modify it. All operations are logged for security auditing.
IEEE

Contrastive Learning-Based Deep Embedded Clustering and the TCN-DMAttention Model for Traffic Congestion Prediction

Abstract: With the increasing number of motor vehicles per capita, the problem of road traffic congestion is becoming increasingly prominent. Intelligent transportation systems are playing an ...