AI Agents

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Nvidia is reportedly planning its own open source OpenClaw competitor

Chipmaker Nvidia is preparing to launch its own open source AI agent platform to compete with the likes of OpenClaw, according to a recent Wired report. The magazine cites “people familiar with the company’s plans” in reporting that Nvidia has been pitching the platform, which it is calling NemoClaw, to various corporate partners ahead of […]

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How to Build a Self-Designing Meta-Agent That Automatically Constructs, Instantiates, and Refines Task-Specific AI Agents

In this tutorial, we build a Meta-Agent that designs other agents automatically from a simple task description. We implement a system that analyzes the task, selects tools, chooses a memory architecture, configures a planner, and then instantiates a fully working agent runtime. We go beyond static agent templates and instead build a dynamic, self-configuring architecture

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NVIDIA AI Releases Nemotron-Terminal: A Systematic Data Engineering Pipeline for Scaling LLM Terminal Agents

The race to build autonomous AI agents has hit a massive bottleneck: data. While frontier models like Claude Code and Codex CLI have demonstrated impressive proficiency in terminal environments, the training strategies and data mixtures behind them have remained closely guarded secrets. This lack of transparency has forced researchers and devs into a costly cycle

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Meta acquires Moltbook, the AI agent social network

Meta has acquired Moltbook, the Reddit-esque simulated social network made up of AI agents that went viral a few weeks ago. The company will hire Moltbook creator Matt Schlicht and his business partner, Ben Parr, to work within Meta Superintelligence Labs. The terms of the deal have not been disclosed. As for what interested Meta

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How to Build a Risk-Aware AI Agent with Internal Critic, Self-Consistency Reasoning, and Uncertainty Estimation for Reliable Decision-Making

In this tutorial, we build an advanced agent system that goes beyond simple response generation by integrating an internal critic and uncertainty estimation framework. We simulate multi-sample inference, evaluate candidate responses across accuracy, coherence, and safety dimensions, and quantify predictive uncertainty using entropy, variance, and consistency measures. We implement risk-sensitive selection strategies to balance confidence

How to Build a Risk-Aware AI Agent with Internal Critic, Self-Consistency Reasoning, and Uncertainty Estimation for Reliable Decision-Making Read More »

ByteDance Releases DeerFlow 2.0: An Open-Source SuperAgent Harness that Orchestrates Sub-Agents, Memory, and Sandboxes to do Complex Tasks

The era of the ‘Copilot’ is officially getting an upgrade. While the tech world has spent the last two years getting comfortable with AI that suggests code or drafts emails, ByteDance team is moving the goalposts. They released DeerFlow 2.0, a newly open-sourced ‘SuperAgent’ framework that doesn’t just suggest work; it executes it. DeerFlow is

ByteDance Releases DeerFlow 2.0: An Open-Source SuperAgent Harness that Orchestrates Sub-Agents, Memory, and Sandboxes to do Complex Tasks Read More »

Andrew Ng’s Team Releases Context Hub: An Open Source Tool that Gives Your Coding Agent the Up-to-Date API Documentation It Needs

In the fast-moving world of agentic workflows, the most powerful AI model is still only as good as its documentation. Today, Andrew Ng and his team at DeepLearning.AI officially launched Context Hub, an open-source tool designed to bridge the gap between an agent’s static training data and the rapidly evolving reality of modern APIs. You

Andrew Ng’s Team Releases Context Hub: An Open Source Tool that Gives Your Coding Agent the Up-to-Date API Documentation It Needs Read More »

Anthropic Introduces Code Review via Claude Code to Automate Complex Security Research Using Advanced Agentic Multi-Step Reasoning Loops

In the frantic arms race of ‘AI for code,’ we’ve moved past the era of the glorified autocomplete. Today, Anthropic is double-downing on a more ambitious vision: the AI agent that doesn’t just write your boilerplate, but actually understands why your Kubernetes cluster is screaming at 3:00 AM. With the recent launch of Claude Code

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Agentic AI in health care and life sciences: autonomy, accountability and the architecture of trust

With all the change that’s happened in the past decade, a few key things remain the same across health care and life sciences. Clinical trials remain the engine behind every new therapy, care delivery systems determine whether patients receive timely and effective treatment and health care payers must steward finite […] The post Agentic AI

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Nanochat Can Now Train a GPT-2 Level Model in Just 2 Hours

AI development is accelerating fast. Advances in hardware, software optimization, and better datasets now allow training runs that once took weeks to finish in hours. A recent update from AI researcher Andrej Karpathy shows this shift clearly: the Nanochat open-source project can now train a GPT-2 model on a single node with 8× NVIDIA H100

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