agentic ai

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Implementing Deep Q-Learning (DQN) from Scratch Using RLax JAX Haiku and Optax to Train a CartPole Reinforcement Learning Agent

In this tutorial, we implement a reinforcement learning agent using RLax, a research-oriented library developed by Google DeepMind for building reinforcement learning algorithms with JAX. We combine RLax with JAX, Haiku, and Optax to construct a Deep Q-Learning (DQN) agent that learns to solve the CartPole environment. Instead of using a fully packaged RL framework, […]

Implementing Deep Q-Learning (DQN) from Scratch Using RLax JAX Haiku and Optax to Train a CartPole Reinforcement Learning Agent Read More »

Meet GitAgent: The Docker for AI Agents that is Finally Solving the Fragmentation between LangChain, AutoGen, and Claude Code

The current state of AI agent development is characterized by significant architectural fragmentation. Software devs building autonomous systems must generally commit to one of several competing ecosystems: LangChain, AutoGen, CrewAI, OpenAI Assistants, or the more recent Claude Code. Each of these ‘Five Frameworks’ utilizes a proprietary method for defining agent logic, memory persistence, and tool

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MWC 2026: The Year the Smartphone Mutated into an AI Agent

We just wrapped up another exhausting, inspiring, and chaotic Mobile World Congress in Barcelona, and I’ve been standardizing my thoughts on what we saw. If you came looking for incremental updates to your favorite glass slab, you were probably disappointed. […] The post MWC 2026: The Year the Smartphone Mutated into an AI Agent appeared

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NVIDIA Releases Nemotron-Cascade 2: An Open 30B MoE with 3B Active Parameters, Delivering Better Reasoning and Strong Agentic Capabilities

NVIDIA has announced the release of Nemotron-Cascade 2, an open-weight 30B Mixture-of-Experts (MoE) model with 3B activated parameters. The model focuses on maximizing ‘intelligence density,’ delivering advanced reasoning capabilities at a fraction of the parameter scale used by frontier models. Nemotron-Cascade 2 is the second open-weight LLM to achieve Gold Medal-level performance in the 2025

NVIDIA Releases Nemotron-Cascade 2: An Open 30B MoE with 3B Active Parameters, Delivering Better Reasoning and Strong Agentic Capabilities Read More »

A Coding Implementation Showcasing ClawTeam’s Multi-Agent Swarm Orchestration with OpenAI Function Calling

In this comprehensive tutorial, we present the core architecture of ClawTeam, an open-source Agent Swarm Intelligence framework developed by HKUDS. We implement the fundamental concepts that make ClawTeam powerful: a leader agent that decomposes complex goals into sub-tasks, specialized worker agents that execute those tasks autonomously, a shared task board with automatic dependency resolution, and

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LlamaIndex Releases LiteParse: A CLI and TypeScript-Native Library for Spatial PDF Parsing in AI Agent Workflows

In the current landscape of Retrieval-Augmented Generation (RAG), the primary bottleneck for developers is no longer the large language model (LLM) itself, but the data ingestion pipeline. For software developers, converting complex PDFs into a format that an LLM can reason over remains a high-latency, often expensive task. LlamaIndex has recently introduced LiteParse, an open-source,

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AI 에이전트와 에이전틱 AI 활용 가이드

에이전틱 AI는 자동화와 의사결정을 위한 차세대 키워드로 주목받으며 큰 기대를 모으고 있습니다. 하지만 이러한 열기 이면에는 다소 조심스러운 전망이 자리 잡고 있습니다. 가트너(Gartner)는 비용 급증, 불분명한 비즈니스 가치, 부적절한 리스크 관리 등의 이유로 에이전틱 AI 프로젝트의 40% 이상이 2027년 말까지 중단될 것이라고 경고합니다. *이 글은 SAS 글로벌 공공 부문 전략 […] The post AI 에이전트와

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Google Colab Now Has an Open-Source MCP (Model Context Protocol) Server: Use Colab Runtimes with GPUs from Any Local AI Agent

Google has officially released the Colab MCP Server, an implementation of the Model Context Protocol (MCP) that enables AI agents to interact directly with the Google Colab environment. This integration moves beyond simple code generation by providing agents with programmatic access to create, modify, and execute Python code within cloud-hosted Jupyter notebooks. This represents a

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Visa prepares payment systems for AI agent-initiated transactions

Payments rely on a simple model: a person decides to buy something, and a bank or card network processes the transaction. That model is starting to change as Visa tests how AI agents can initiate payments. New work in the banking sector suggests that, in some cases, software agents may soon take on that role.

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Meet Mamba-3: A New State Space Model Frontier with 2x Smaller States and Enhanced MIMO Decoding Hardware Efficiency

The scaling of inference-time compute has become a primary driver for Large Language Model (LLM) performance, shifting architectural focus toward inference efficiency alongside model quality. While Transformer-based architectures remain the standard, their quadratic computational complexity and linear memory requirements create significant deployment bottlenecks. A team of researchers from Carnegie Mellon University (CMU), Princeton University, Together

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