NVIDIA, Ineffable Intelligence Team Up to Build the Future of Reinforcement Learning Infrastructure
Reinforcement-learning agents — AI systems that learn by trial and error — can convert computation into new knowledge. That’s the focus of a new engineering-level collaboration between NVIDIA and Ineffable Intelligence, the London-based AI lab founded by AlphaGo architect David Silver in the wake of...
Hermes Unlocks Self-Improving AI Agents, Powered by NVIDIA RTX PCs and DGX Spark
Agentic AI is changing the way users get work done. Following the success of OpenClaw, the community is embracing new open source agentic frameworks. The latest is Hermes Agent, which crossed 140,000 GitHub stars in under three months.
Adaption aims big with AutoScientist, an AI tool that helps models train themselves
Adaption's new AutoScientist tool is designed to let models adapt to specific capabilities quickly through an automated approach to conventional fine-tuning.
Building an Evaluation Harness for Production AI Agents: A 12-Metric Framework From 100+ Deployments
A 12-metric evaluation framework for production AI agents — covering retrieval, generation, agent behavior, and production health. Drawn from 100+ enterprise deployments.
The post Building an Evaluation Harness for Production AI Agents: A 12-Metric Framework From 100+ Deployments appeared first on T...
Mira Murati’s Thinking Machines Lab Introduces Interaction Models: A Native Multimodal Architecture for Real-Time Human-AI Collaboration
Thinking Machines Lab has introduced a research preview of TML-Interaction-Small, a 276B parameter Mixture-of-Experts model with 12B active parameters, built around a multi-stream, time-aligned micro-turn architecture that processes 200ms chunks of audio, video, and text simultaneously — eliminating...
AI for Business Forecasting: Can It Improve My Bottom Line?
Few things are more valuable in business than seeing what’s coming next. Whether predicting sales, managing inventory, or allocating resources, the ability to forecast accurately can make the difference between thriving and surviving.Traditionally, forecasting has relied on spreadsheets, historical ...
QuIDE: Mastering the Quantized Intelligence Trade-off via Active Optimization
arXiv:2605.10959v1 Announce Type: new
Abstract: There is currently no unified metric for evaluating the efficiency of quantized neural networks. We propose QuIDE, built around the Intelligence Index I = (C x P)/log_2(T+1), which collapses the compression-accuracy-latency trade-off into a single sco...
Steering Without Breaking: Mechanistically Informed Interventions for Discrete Diffusion Language Models
arXiv:2605.10971v1 Announce Type: new
Abstract: Discrete diffusion language models (DLMs) generate text by iteratively denoising all positions in parallel, offering an alternative to autoregressive models. Controlled generation methods for DLMs, imported from autoregressive models, apply uniform in...
Vertex-Softmax: Tight Transformer Verification via Exact Softmax Optimization
arXiv:2605.10974v1 Announce Type: new
Abstract: Certified verification of transformer attention requires bounding the softmax function over interval constraints on the pre-softmax scores. Existing verifiers relax softmax ndependently of the downstream objective, leaving avoidable slack. We prove th...
EVOCHAMBER: Test-Time Co-evolution of Multi-Agent System at Individual, Team, and Population Scales
arXiv:2605.11136v1 Announce Type: new
Abstract: We argue that multi-agent test-time evolution is not single-agent evolution replicated N times. A single-agent learner can only evolve its own context and memory. A multi-agent system additionally evolves who collaborates, how they collaborate, and ho...
OLIVIA: Online Learning via Inference-time Action Adaptation for Decision Making in LLM ReAct Agents
arXiv:2605.11169v1 Announce Type: new
Abstract: Large language model agents interleave reasoning, action selection, and observation to solve sequential decision-making tasks. In deployed settings where agents repeatedly handle related multi-step tasks, small action-selection errors can accumulate i...
The Many Faces of On-Policy Distillation: Pitfalls, Mechanisms, and Fixes
arXiv:2605.11182v1 Announce Type: new
Abstract: On-policy distillation (OPD) and on-policy self-distillation (OPSD) have emerged as promising post-training methods for large language models, offering dense token-level supervision on trajectories sampled from the model's own policy. However, existin...
Medicare’s new payment model is built for AI, and most of the tech world has no idea
There is no governmental mechanism to pay for an AI agent that monitors a patient between visits, calls to check in, coordinates a housing referral, or makes sure someone picks up their medication. ACCESS creates that mechanism for the first time.
Build a Hybrid-Memory Autonomous Agent with Modular Architecture and Tool Dispatch Using OpenAI
In this tutorial, we begin by exploring the architecture behind a hybrid-memory autonomous agent. This system combines semantic vector search, keyword-based retrieval, and a modular tool-dispatching loop to create an agent capable of reasoning, remembering, and acting autonomously. We walk through e...
Meet AntAngelMed: A 103B-Parameter Open-Source Medical Language Model Built on a 1/32 Activation-Ratio MoE Architecture
MedAIBase has released AntAngelMed, a 103B-parameter open-source medical language model that uses a 1/32 activation-ratio Mixture-of-Experts (MoE) architecture to activate only 6.1B parameters at inference time, matching the performance of roughly 40B dense models while exceeding 200 tokens per seco...
Anthropic warns investors against secondary platforms offering access to its shares
The company named Open Doors Partners, Unicorns Exchange, Pachamama Capital, Lionheart Ventures, Hiive, Forge Global, Sydecar and Upmarket as companies that are not authorized to provide access to buy or sell its shares.
Everything Google announced at its Android Show, from Googlebooks to vibe-coded widgets
Google unveiled its new AI-first Googlebooks laptops, more agentic Gemini features, vibe-coded Android widgets, Gemini in Chrome, refreshed Android Auto, and more ahead of I/O.
A 4.5-hour journey from idea to working fitness app with LLM agents
The post From Vibe Coding to Spec-Driven Development appeared first on Towards Data Science.
Proxy-Pointer Framework for Structure-Aware Enterprise Document Intelligence
Hierarchical understanding and comparison of contracts, research papers, and more
The post Proxy-Pointer Framework for Structure-Aware Enterprise Document Intelligence appeared first on Towards Data Science.
Advancing AI for materials with MatterSim: experimental synthesis, faster simulation, and multi-task models
MatterSim is expanding what AI can do for materials science—from faster large-scale simulations to MatterSim-MT, a new multi-task model for simulating properties beyond potential energy surfaces alone.
The post Advancing AI for materials with MatterSim: experimental synthesis, faster simulation, and...