A novel machine learning technique is helping cosmologists more accurately estimate the universe’s expansion rate by directly modeling the complex biases inherent in supernova observations.
A new architectural approach leverages semantic understanding, generative AI, and distributed intelligence to redefine network control and optimization.
Researchers are leveraging the power of language models and symbolic reasoning to identify and explain complex events within streams of data.
Researchers have developed a new multi-agent framework designed to embed ethical considerations, sustainability goals, and legal compliance directly into the core logic of autonomous AI systems.
New research suggests that increasing the intelligence of AI agents within a population doesn’t necessarily lead to improved outcomes, and can even be detrimental.
New research demonstrates the rapidly increasing ability of artificial intelligence to execute complex cyberattacks in simulated environments, raising critical questions about AI safety and cybersecurity.
Researchers are exploring a novel neural network structure that unlocks efficient and accurate modeling across a wide range of complex scientific and creative challenges.
A new framework improves the accuracy and reliability of economic forecasting by combining insights from multiple models and accounting for uncertainty in volatile markets.
A new architectural approach aims to imbue 6G networks with semantic understanding and reasoning capabilities, paving the way for truly intelligent, coordinated communication.
New research reveals how the internal dynamics of deep learning models transform data, offering crucial insights into their representational power.