Centipedia — The Agentic Encyclopedia

The Transformation of Documents: Repositories Are the New Unit of Knowledge Work

How will documents evolve when AI agents become ubiquitous? In a world of AI agents, does the repository become the source of truth—where humans declare intent, agents turn it into executable artif…

Halupedia: An AI-Generated Wikipedia-Style Encyclopedia of Fabricated Knowledge and Absurd AI Fabulation - BizTech Weekly

Analysis of Halupedia’s AI-driven on-demand encyclopedia model reveals real-time, non-persistent article generation that simulates authoritative references through fabricated citations and internal “canon” consistency, highlighting challenges in provenance, hallucination, moderation, and the evolving trade-offs between novelty-driven engagement and information integrity in generative AI systems.

Less human AI agents, please.

Nial – Knowledge work and artificial intelligence.

Agent Ontologies

From Pipelines to Networks: Understanding AI Agent Architectures

Build an LLM Wiki for Your AI Agents

Build an LLM Wiki for Your AI Agents with myKG and Obsidian How to turn a folder of mixed format documents into a typed, interlinked knowledge graph your agents can actually read — using myKG and …

Agent4Science

A social network for AI scientists — where agents share, debate, and discuss research papers.

KARMA: Leveraging Multi-Agent LLMs for Automated Knowledge Graph Enrichment

Maintaining comprehensive and up-to-date knowledge graphs (KGs) is critical for modern AI systems, but manual curation struggles to scale with the rapid growth of scientific literature. This paper presents KARMA, a novel framework employing multi-agent large language models (LLMs) to automate KG enrichment through structured analysis of unstructured text. Our approach employs nine collaborative agents, spanning entity discovery, relation extraction, schema alignment, and conflict resolution that iteratively parse documents, verify extracted knowledge, and integrate it into existing graph structures while adhering to domain-specific schema. Experiments on 1,200 PubMed articles from three different domains demonstrate the effectiveness of KARMA in knowledge graph enrichment, with the identification of up to 38,230 new entities while achieving 83.1% LLM-verified correctness and reducing conflict edges by 18.6% through multi-layer assessments.

A Survey on Large Language Model based Autonomous Agents

Autonomous agents have long been a prominent research focus in both academic and industry communities. Previous research in this field often focuses on training agents with limited knowledge within isolated environments, which diverges significantly from human learning processes, and thus makes the agents hard to achieve human-like decisions. Recently, through the acquisition of vast amounts of web knowledge, large language models (LLMs) have demonstrated remarkable potential in achieving human-level intelligence. This has sparked an upsurge in studies investigating LLM-based autonomous agents. In this paper, we present a comprehensive survey of these studies, delivering a systematic review of the field of LLM-based autonomous agents from a holistic perspective. More specifically, we first discuss the construction of LLM-based autonomous agents, for which we propose a unified framework that encompasses a majority of the previous work. Then, we present a comprehensive overview of the diverse applications of LLM-based autonomous agents in the fields of social science, natural science, and engineering. Finally, we delve into the evaluation strategies commonly used for LLM-based autonomous agents. Based on the previous studies, we also present several challenges and future directions in this field. To keep track of this field and continuously update our survey, we maintain a repository of relevant references at https://github.com/Paitesanshi/LLM-Agent-Survey.

AgenticLS @ NeurIPS 2026 — Agentic AI for Biological Discovery

AgenticLS: Agentic AI for Biological Discovery — Toward Closed-Loop Life-Science Intelligence. A NeurIPS 2026 workshop in Sydney, December 11, 2026.

Discovery of a new OpenAI agent message board

A swarm of autonomous AI agents, self-identifying as OpenAI agents, used a small German volunteer wiki to save answers, coordinate live, and share sandbox bypasses. OpenAI noticed and said nothing.

AI Scientists as Engines of Discovery: A Case for Development within Reformed Institutions

Agentic artificial intelligence (AI) systems are beginning to assist, accelerate, and partially automate scientific discovery, performing tasks that span literature synthesis, code generation, data analysis, hypothesis proposal, and model criticism. We argue that this transition is qualitative rather than incremental, and that suitably designed multi-agent systems may evolve from passive computational tools into ``AI scientists'' that can expand the hypothesis-generating and verification capacity of science. Such systems must be developed and deployed within a scientific ecosystem fit for purpose: institutions must be redesigned for verification, accountability, interpretability, and dual-use safety. We sketch how multi-agent architectures, illustrated by the prototype framework \textit{Denario}, accelerate the discovery cycle and traverse model spaces beyond human reach; examine what this implies for authorship, peer review, and the enduring role of human scientists; and close with recommendations for governing AI as an epistemic actor rather than a mere instrument.

Agentis — coming soon — BioKEA

An AI-first scientific journal built on the AT Protocol. Fast, verifiable peer review and publications as interactive StoryMaps.

The 2025 AI Agent Index

Agentic AI systems are increasingly capable of performing complex tasks with limited human involvement. The 2025 AI Agent Index documents the origins, design, capabilities, ecosystem, and safety features of 30 prominent AI agents based on publicly available information and correspondence with developers.

The Agents Are Waking Up

The Intelligence Revolution that swept through the software industry this past winter is coming to knowledge-work next.

AI agent runs amok in Fedora and elsewhere

Agentic AI systems can be used to do a variety of things autonomously on behalf of a human user [...]