Sen. Mark Warner’s AI AGENT Act discussion draft would require FTC-developed security and identity standards for AI agent providers, with certified bodies vetting vendors and the FTC deregistering violators from the list.
The Council gave final approval to an EU regulation amending the AI Act as part of the “Omnibus VII” simplification package. It updates application dates for high-risk AI, bans certain non-consensual intimate content/CSAM generation practices, adjusts sandbox and transparency deadlines, and clarifies AI Office competences for general-purpose AI models.
On June 2, 2026, President Trump signed an executive order titled “Promoting Advanced Artificial Intelligence Innovation and Security,” directing federal agencies to prioritize AI-enabled cybersecurity, create an AI cybersecurity clearinghouse, and develop a framework for “covered frontier models.”
New York’s FAIR News Act would require disclosure when news articles are substantially composed or authored with AI assistance, with potential fines for non-disclosure. The article says the bill was approved by the state legislature and awaits Gov. Kathy Hochul’s signature.
The Council formally adopted changes to simplify parts of the EU AI Act, including delayed application dates for high-risk AI obligations (2 Dec 2027 for stand-alone; 2 Aug 2028 for embedded in regulated products) and added certain AI-related prohibitions and transparency deadlines.
Trajectory representation learning (TRL) aims to encode raw trajectory data into low-dimensional embeddings for downstream tasks such as travel time estimation, mobility prediction, and trajectory similarity analysis. From a behavioral perspective, a trajectory reflects a sequence of route choices within an urban environment. However, most existing TRL methods ignore this underlying decision-makin
Credit exposure in Decentralized Finance (DeFi) is often implicit and token-mediated, creating a dense web of inter-protocol dependencies. Thus, a shock to one token may result in significant and uncontrolled contagion effects. As the DeFi ecosystem becomes increasingly linked with traditional financial infrastructure through instruments, such as stablecoins, the risk posed by this dynamic demands
Vision-Language-Action (VLA) models have shown strong potential for robotic manipulation, but real-time deployment on edge hardware remains challenging. In this work, we identify VLM visual and context tokens as a major source of deployment latency: for GEMM-dominated projection operators, computation grows linearly with the number of input tokens when model dimensions are fixed. Motivated by this
Vision-Language Models (VLMs) have been applied to a wide range of reasoning tasks, yet it remains unclear whether they can reason robustly under distribution shifts. In this paper, we study covariate shifts in which the perceptual input distribution changes while the underlying prediction rules do not. To investigate this question, we consider visual deductive reasoning tasks, where a model is re
Deep learning has demonstrated remarkable success in high-throughput histopathology image analysis. However, the performance of learning-based models critically depends on the quality and size of annotations by expert pathologists, which is a resource-intensive and time-consuming process. To address the limitations of data scarcity and annotation burden, several methods have been proposed to synth
Large checks continue to concentrate in AI-adjacent infrastructure and strategic platforms, with one public-market listing and two private financings anchoring the desk. The pattern points to capital favoring scale, supply-chain leverage, and backers with industrial or state-linked reach.
Large checks continue to concentrate in AI-adjacent infrastructure and strategic platforms, with one public-market listing and two private financings anchoring the desk. The pattern points to capital favoring scale, supply-chain leverage, and backers with industrial or state-linked reach.
Large checks continue to concentrate in AI-adjacent infrastructure and strategic platforms, with one public-market listing and two private financings anchoring the desk. The pattern points to capital favoring scale, supply-chain leverage, and backers with industrial or state-linked reach.
Named hires continue to reshape AI leadership benches, spanning telecom, robotics, and frontier research. The signal is less churn than positioning: companies are adding senior technical authority where product, research, and deployment now intersect.
Named hires continue to reshape AI leadership benches, spanning telecom, robotics, and frontier research. The signal is less churn than positioning: companies are adding senior technical authority where product, research, and deployment now intersect.
Named hires continue to reshape AI leadership benches, spanning telecom, robotics, and frontier research. The signal is less churn than positioning: companies are adding senior technical authority where product, research, and deployment now intersect.
A small set of scores updates the evaluation surface for a single large model across math, reasoning, and general knowledge. The value today is comparative: even modest benchmark movement helps track where capability is being measured most tightly.
A small set of scores updates the evaluation surface for a single large model across math, reasoning, and general knowledge. The value today is comparative: even modest benchmark movement helps track where capability is being measured most tightly.
A small set of scores updates the evaluation surface for a single large model across math, reasoning, and general knowledge. The value today is comparative: even modest benchmark movement helps track where capability is being measured most tightly.