The Edge of the Cyber World See the latest
CISA developed this guidance to help defensive teams at varying levels of cybersecurity maturity plan and implement cyber decoy strategies that strengthen their detection and response capabilities. Many organizations struggle to detect adversaries who use legitimate credentials, native tools, and living off the land (LOTL) techniques to conduct discovery, move laterally, and access data. Cyber…
Conversational Large Language Models are post-trained on language that expresses specific behavioural traits, such as curiosity, open-mindedness, and empathy, and values, such as helpfulness, harmlessness, and honesty. This is done to increase utility, ensure safety, and improve the experience of the people interacting with the model. However, values are complex and inter-related – inducing one…
Discrete flow matching generates text by iteratively transforming noise tokens into coherent language, but may require hundreds of forward passes. Distillation uses the multi-step trajectory to train a student to reproduce the process in a few steps. When the student underperforms, the usual explanation is insufficient capacity. We argue the opposite: the trajectory is the…
Diffusion large language models are a compelling alternative to autoregressive models, yet existing RL methods for diffusion treat all denoising steps as equally important and rely on biased, high-variance likelihood estimates. We identify two fundamental weaknesses: the absence of temporal credit assignment across the denoising trajectory, and the systematic bias of mean-field likelihood estimates used…
Enterprise data lakes accumulate tables faster than human stewards can document or classify them, leaving columns with missing descriptions and unassigned governance labels. This documentation debt undermines data discovery, access control, and regulatory compliance. We present Glyph, a production system that frames two coupled problems, column description generation and column type annotation for data classification,…
Long-simmering worries about the technology’s potential dangers have exploded into the global consciousness since Jacob Coxon’s dire warning.
Senior administration officials have gathered almost daily in recent months to plot potential guardrails.
The Meta CEO says companies have strong incentive to build safe agents and models.
The company said it hopes to inspire competitors to greater transparency as public fears about AI dangers mount.
The U.S. achieved dominance by taking big chances. Where has that ethos gone?
