Anthropic’s new whitepaper outlines a Zero Trust framework for AI agents, detailing emerging threats, four key differences from traditional software, a three‑tier capability roadmap, eight concrete deployment phases, and operational practices needed to keep autonomous agents secure at machine speed.
The article presents a comprehensive C2 decision framework for underwater UUVs, defining core variables, rule‑based and game‑theoretic models, POMDP and Monte‑Carlo solutions, risk‑aware algorithms, multi‑UUV consensus, and practical three‑layer rule implementations to balance information gain against platform survivability.
The article explains how AI agents are reshaping product logic, breaks down the four core modules—Planner, Memory, Actor, and Tools—illustrates their interaction with a real‑world market‑report example, and offers design guidelines and pitfalls for product managers transitioning to intelligent, autonomous systems.
The article defines AI Agent self‑evolution as an autonomous loop of perception, learning, and optimization, outlines its three evolutionary levels, key characteristics, core development components, reviews leading frameworks such as EvoSkill and DGM‑Hyperagents, and discusses safety laws for controllable evolution.
The article provides an in‑depth analysis of the Skills mechanism that gives large language model agents reusable procedural memory, detailing its core components, seven design patterns, real‑world security threats, evaluation benchmarks, and the challenges of safely scaling autonomous AI systems.
This article explains AI agents as autonomous systems that perceive environments, set goals, and act, contrasting them with traditional AI, detailing their core definition, architecture, key components, practical applications, implementation steps, classification, technology stack, case studies, emerging trends, challenges, and future directions.
This article explains the fundamental differences between workflows and agents, introduces seven core design patterns—including three workflow patterns and four agent patterns—provides Python examples using Ollama, and shows how to combine these patterns to create robust, autonomous AI applications.
This report explores the fundamentals, core technologies, leading platforms, current state, and future outlook of AI Agents and Agentic AI, detailing how large language models and mature infrastructure enable autonomous, reactive, proactive, and adaptive agents, and examines prominent projects such as Manus, Genspark, and Lovart.
This article provides a comprehensive overview of AI Agents, tracing their evolution from traditional chatbots to LLM‑driven agents, explaining core components such as perception, reasoning, action, knowledge bases, learning and communication interfaces, and discussing practical use cases, interaction cycles, and future prospects.
This article surveys the rapid rise of AI agents powered by large language models, explaining their core perception‑planning‑action loop, memory architectures, tool‑use mechanisms, self‑reflection techniques, and real‑world case studies while highlighting current challenges and future prospects for autonomous intelligent systems.
Tracing AI agents from Aristotle’s and Zhuangzi’s philosophical notions through the coining of “agent” in computer science to today’s learning‑based systems powered by large language models, the article outlines key milestones, core components—LLM brain, memory, planning, tool use—and showcases applications such as AlphaGo, Siri, and autonomous platforms, while forecasting their expanding, industry‑wide ubiquity.
The article surveys the rise of LLM‑powered AI agents, defining them as LLM + memory + planning + tool use, contrasting fully autonomous agents with human‑guided autopilot/copilot variants, outlining their benefits, risks such as hallucinations and unsafe actions, and urging modular frameworks and oversight for reliable enterprise deployment.
The JD Group Technology Committee’s 2020 white paper analyzes five key future technology trends—Artificial Intelligence, Internet of Things, Blockchain, Autonomous Systems, and Next‑Generation Computing—detailing their breakthroughs, industry applications, and how they will reshape supply chains, retail, finance, healthcare, and smart cities.
