Prophet Security Secures Investments from Amex Ventures and Citi Ventures
Funding advances the adoption of the Prophet Agentic AI SOC Platform, enabling security teams to respond to threats faster and with greater accuracy. Prophet Security, Inc., a pioneer in Agentic AI for Security Operations, today announced strategic investments from Amex Ventures and Citi Ventures. T...
TELUS Digital Research Reveals a Hidden Risk in AI Model Behavior
Study shows the use of persona prompting can cause shifts in LLMs’ moral judgements,leading to unexpected and inconsistent responses For enterprises, this means careful model selection, rigorous testing and ongoing evaluation are essential to ensure consistent,reliable AI behavior in production A ne...
Nous Research Releases ‘Hermes Agent’ to Fix AI Forgetfulness with Multi-Level Memory and Dedicated Remote Terminal Access Support
In the current AI landscape, we’ve become accustomed to the ‘ephemeral agent’—a brilliant but forgetful assistant that restarts its cognitive clock with every new chat session. While LLMs have become master coders, they lack the persistent state required to function as true teammates. Nous Research ...
Latent Context Compilation: Distilling Long Context into Compact Portable Memory
arXiv:2602.21221v1 Announce Type: new
Abstract: Efficient long-context LLM deployment is stalled by a dichotomy between amortized compression, which struggles with out-of-distribution generalization, and Test-Time Training, which incurs prohibitive synthetic data costs and requires modifying model ...
ACAR: Adaptive Complexity Routing for Multi-Model Ensembles with Auditable Decision Traces
arXiv:2602.21231v1 Announce Type: new
Abstract: We present ACAR (Adaptive Complexity and Attribution Routing), a measurement framework for studying multi-model orchestration under auditable conditions. ACAR uses self-consistency variance (sigma) computed from N=3 probe samples to route tasks across...
AngelSlim: A more accessible, comprehensive, and efficient toolkit for large model compression
arXiv:2602.21233v1 Announce Type: new
Abstract: This technical report introduces AngelSlim, a comprehensive and versatile toolkit for large model compression developed by the Tencent Hunyuan team. By consolidating cutting-edge algorithms, including quantization, speculative decoding, token pruning,...
Group Orthogonalized Policy Optimization:Group Policy Optimization as Orthogonal Projection in Hilbert Space
arXiv:2602.21269v1 Announce Type: new
Abstract: We present Group Orthogonalized Policy Optimization (GOPO), a new alignment algorithm for large language models derived from the geometry of Hilbert function spaces. Instead of optimizing on the probability simplex and inheriting the exponential curva...
A Dynamic Survey of Soft Set Theory and Its Extensions
arXiv:2602.21268v1 Announce Type: new
Abstract: Soft set theory provides a direct framework for parameterized decision modeling by assigning to each attribute (parameter) a subset of a given universe, thereby representing uncertainty in a structured way [1, 2]. Over the past decades, the theory has...
A Hierarchical Multi-Agent System for Autonomous Discovery in Geoscientific Data Archives
arXiv:2602.21351v1 Announce Type: new
Abstract: The rapid accumulation of Earth science data has created a significant scalability challenge; while repositories like PANGAEA host vast collections of datasets, citation metrics indicate that a substantial portion remains underutilized, limiting data ...
Beyond Refusal: Probing the Limits of Agentic Self-Correction for Semantic Sensitive Information
arXiv:2602.21496v1 Announce Type: new
Abstract: While defenses for structured PII are mature, Large Language Models (LLMs) pose a new threat: Semantic Sensitive Information (SemSI), where models infer sensitive identity attributes, generate reputation-harmful content, or hallucinate potentially wro...
ARLArena: A Unified Framework for Stable Agentic Reinforcement Learning
arXiv:2602.21534v1 Announce Type: new
Abstract: Agentic reinforcement learning (ARL) has rapidly gained attention as a promising paradigm for training agents to solve complex, multi-step interactive tasks. Despite encouraging early results, ARL remains highly unstable, often leading to training col...
Power and Limitations of Aggregation in Compound AI Systems
arXiv:2602.21556v1 Announce Type: new
Abstract: When designing compound AI systems, a common approach is to query multiple copies of the same model and aggregate the responses to produce a synthesized output. Given the homogeneity of these models, this raises the question of whether aggregation unl...
You don’t know what your agent will do until it’s in production
You can't monitor agents like traditional software. Inputs are infinite, behavior is non-deterministic, and quality lives in the conversations themselves. This article explains what to monitor, how to scale evaluation, and how production traces become the foundation for continuous improvement.
Gushwork bets on AI search for customer leads — and early results are emerging
Gushwork has raised $9 million in a seed round led by SIG and Lightspeed. The startup has seen early customer traction from AI search tools like ChatGPT.
Anthropic acquires computer-use AI startup Vercept after Meta poached one of its founders
Seattle-based Vercept developed complex agentic tools, including a computer-use agent that could complete tasks inside applications like a person with a laptop would.
Scaling Feature Engineering Pipelines with Feast and Ray
Utilizing feature stores like Feast and distributed compute frameworks like Ray in production machine learning systems
The post Scaling Feature Engineering Pipelines with Feast and Ray appeared first on Towards Data Science.
Mixing generative AI with physics to create personal items that work in the real world
To help generative AI models create durable, real-world accessories and decor, the PhysiOpt system runs physics simulations and makes subtle tweaks to its 3D blueprints.
Breaking the Host Memory Bottleneck: How Peer Direct Transformed Gaudi’s Cloud Performance
Engineering RDMA-like performance over cloud host NICs using libfabric, DMA-BUF, and HCCL to restore distributed training scalability
The post Breaking the Host Memory Bottleneck: How Peer Direct Transformed Gaudi’s Cloud Performance appeared first on Towards Data Science.
See the whole picture and find the look with Circle to Search
Google Search interface featuring AI-powered tools including an "AI Overview" that breaks down an outfit's components and a virtual "Try it on" button that visualizes apparel on diverse body types.
Seemplicity Introduces Seema for Conversational Exposure Intelligence
Seema transforms how security teams interact with exposure data by converting complex questions into real-time answers based on live operational insight Seemplicity today announced the launch of Seema, an AI-powered conversational assistant that makes it easier for cybersecurity teams to gain clarit...
Red Hat AI Factory with NVIDIA Accelerates the Path to Scalable Production AI
New co-engineered offering combines Red Hat AI Enterprise and NVIDIA’s accelerated computing software to provide a unified foundation for building, deploying, and scaling AI-enabled applications Red Hat, the world’s leading provider of open source solutions, today announced the Red Hat AI Factory wi...