Anchor Detection for RAG: Parallel Detectors, Then One LLM Call at the End
Enterprise Document Intelligence [Vol.1 #7B] - Retrieval is filtering on structured tables: keywords first, TOC second, embeddings last
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The emergence of the web data infrastructure layer for AI
AI is booming. New use cases are emerging each day. To capitalize on the technology’s potential, enterprises require data at scale. In many cases, though, the relevant information is blocked or unstructured, which limits its use by AI models. To understand this challenge, consider the foundation of...
Stop Getting Good at Protocols. Get Good at Agent Experience.
In 2025, if you weren’t building with MCP, you weren’t serious about agents. The Model Context Protocol dominated the agent conversation for the better part of the year. Conference talks, roadmaps, hiring plans, all of it revolved around MCP. Then late 2025 into 2026, AI Skills arrived and the backl...
Harness-1: The 20B Retrieval Subagent That Beats GPT-5.4 at Search
Most search agents try to handle too many jobs at once. They generate new queries, remember what they have already explored, collect evidence, and decide what is relevant as the search keeps expanding. That can make the whole process messy, expensive, and hard to control. Harness-1 takes a simpler a...
Explore the best local coding models for private AI coding, fast GGUF inference, agentic workflows, multimodal development, and running powerful open models on your own GPU.
Using Graphify and NetworkX to Map Python Codebase Structure with God Nodes, Communities, and Architecture Visualizations
In this tutorial, we build a fully offline Graphify pipeline that turns a multi-module Python application into a knowledge graph. We install Graphify, generate a connected sample app, and extract the graph locally using tree-sitter, with no API key or LLM backend. We load graph.json into NetworkX an...
Nous Research Adds /learn to Hermes Agent’s Skills System, Capturing Workflows as Slash Commands Without Hand-Writing SKILL.md
Nous Research has added /learn to the Hermes Agent Skills System. The command authors a standards-compliant SKILL.md from a local directory, a doc URL, a past conversation, or pasted notes. The live agent sources the material with its own tools, then writes the skill — no hand-writing and no separat...
DFlash Speculative Decoding Drafts Whole Token Blocks in Parallel for Up to 15x Higher Throughput on NVIDIA Blackwell
UC San Diego's DFlash replaces autoregressive drafting with a lightweight block diffusion model for speculative decoding. It drafts whole token blocks in a single forward pass and conditions on target hidden features through KV injection. The paper reports up to 6.08x lossless speedup on Qwen3-8B, w...
RIFT-Bench: Dynamic Red-teaming For Agentic AI Systems
arXiv:2606.23927v1 Announce Type: new
Abstract: Agentic AI systems powered by large language models (LLMs) are rapidly evolving into autonomous decision-making systems, exposing attack vectors beyond those of traditional LLM vulnerabilities. Existing security evaluations are often tied to specific ...
Neuro-Symbolic Drive: Rule-Grounded Faithful Reasoning for Driving VLAs
arXiv:2606.23938v1 Announce Type: new
Abstract: Driving VLA models incorporating Chain-of-Thought (CoT) reasoning are attractive because they leverage pretrained VLM representations and expose intermediate decisions in natural language, yet current rationales often lack the step-by-step decision se...
arXiv:2606.23991v1 Announce Type: new
Abstract: What is an agent? What constitutes agency? With the rise of Large Language Model (LLM) systems marketed as ``coding agents'', ``AI co-scientists'', and other ``agentic" tools that promise to drive up productivity, and at the same time, ``existential" ...
Safe and Generalizable Hierarchical Multi-Agent RL via Constraint Manifold Control
arXiv:2606.24010v1 Announce Type: new
Abstract: Multi-agent systems are widely used in safety-critical applications that require coordinated behavior under strict safety constraints. Existing approaches face a fundamental trade-off: learning-based methods achieve strong empirical performance but la...
Reinforcement Learning Towards Broadly and Persistently Beneficial Models
arXiv:2606.24014v1 Announce Type: new
Abstract: As AI systems are deployed across increasingly diverse and high-stakes settings, model alignment must generalize beyond the tasks and domains seen during training. This is especially important for reinforcement learning (RL), which can introduce unexp...
Systematic Exploration of 4-Expert Heterogeneous Mixture-of-Experts via Automated Pipeline Search
arXiv:2606.23739v1 Announce Type: new
Abstract: We present an automated large-scale search pipeline for heterogeneous 4-Expert Mixture-of-Experts (MoE4) architectures within the LEMUR neural network dataset ecosystem. Building on a hand-crafted heterogeneous MoE reference model, we replace manual d...
NVIDIA and AWS Collaborate to Bring AI to Production at Scale
Building AI systems at scale is demanding, requiring low-latency inference, fast vector search, strong GPU price-performance and infrastructure that can grow without multiplying operational complexity. NVIDIA’s latest work with Amazon Web Services (AWS) addresses each of those constraints. Across A...
Mistral OCR 4 Brings Citation-Ready Structured Output to RAG, Agentic, and Enterprise Search Pipelines
Mistral AI released OCR 4 on June 23, 2026, moving from clean text extraction to structured document output. Each block returns a bounding box, a typed classification, and per-page and per-word confidence scores. The model supports 170 languages, runs in a single self-hosted container, and feeds cit...
Datalab Releases lift: A 9B Open-Weights Vision Model That Extracts Structured JSON From PDFs Using Schemas
Datalab released lift, a 9B open-weights vision model that turns PDFs and images into schema-matching JSON. It uses schema-constrained decoding for valid structure and trained abstention to return null instead of hallucinating absent fields, scoring 90.2% field accuracy on a 225-document benchmark.
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Retrieval Is Filtering, Not Search: A Mental Model for Enterprise RAG
Enterprise Document Intelligence [Vol.1 #7A] - Stop searching strings. Filter line_df and toc_df. Pick anchors small, expand context large
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How Businesses Are Building Specialized AI They Can Trust
Companies are asking how to build specialized AI that fits with the way their workflows actually run. The first wave of enterprise AI was about access. Companies experimented with new frontier and open models, ran pilots and explored how AI can help. Now, specialized agents — systems of models tha...
OpenAI helps build shared standards for advanced AI, supporting evaluation frameworks, safety practices, and global cooperation through the Appia Foundation.
For years, AI progress has centered on scaling individual foundation models: larger parameters, longer context windows, stronger reasoning, and better tool use. Sakana AI’s Fugu points elsewhere, behaving like one model from the outside while coordinating multiple expert agents internally. A single ...