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

class MetaAgent: def __init__(self, llm: Optional[LocalLLM] = None): self.llm = llm or LocalLLM() def _capability_heuristics(self, task: str) -> Dict[str, Any]: t = task.lower() needs_data = any(k in t for k…

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…

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

class AgentAnalyzer: @staticmethod def plot_response_distribution(result: Dict): fig, axes = plt.subplots(2, 2, figsize=(14, 10)) fig.suptitle(‘Agent Response Analysis’, fontsize=16, fontweight=”bold”) responses = result[‘all_responses’] scores = result[‘critic_scores’] uncertainty = result[‘uncertainty’] selected_idx = result[‘selected_index’]…

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,…

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…

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…

The ‘Bayesian’ Upgrade: Why Google AI’s New Teaching Method is the Key to LLM Reasoning

Large Language Models (LLMs) are the world’s best mimics, but when it comes to the cold, hard logic of updating beliefs based on new evidence, they are surprisingly stubborn. A…

A Coding Guide to Build a Complete Single Cell RNA Sequencing Analysis Pipeline Using Scanpy for Clustering Visualization and Cell Type Annotation

In this tutorial, we build a complete pipeline for single-cell RNA sequencing analysis using Scanpy. We start by installing the required libraries and loading the PBMC 3k dataset, then perform…

Andrej Karpathy Open-Sources ‘Autoresearch’: A 630-Line Python Tool Letting AI Agents Run Autonomous ML Experiments on Single GPUs

Andrej Karpathy released autoresearch, a minimalist Python tool designed to enable AI agents to autonomously conduct machine learning experiments. The project is a stripped-down version of the nanochat LLM training…

Beyond Accuracy: Quantifying the Production Fragility Caused by Excessive, Redundant, and Low-Signal Features in Regression

At first glance, adding more features to a model seems like an obvious way to improve performance. If a model can learn from more information, it should be able to…