humanlayer/12-factor-agents

What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers? - humanlayer/12-factor-agents

The Rise of Slopsquatting: How AI Hallucinations Are Fueling...

Slopsquatting is a new supply chain threat where AI-assisted code generators recommend hallucinated packages that attackers register and weaponize.

12-factor-agents: Principles to build LLM-powered software good enough to put in the hands of production customers

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An LLM Query Understanding Service

Doug Turnbull recently wrote about how [all search is structured now](https://softwaredoug.com/blog/2025/04/02/all-search-structured-now): Many times, even a small open source LLM will be able to turn a search query into reasonable …

How to respect OpenAI's rate limits in Rails

As it turns out, OpenAI’s rate limits are a little more complicated than other APIs.

The Man Out to Prove How Dumb AI Still Is

François Chollet has constructed the ultimate test for the bots.

The “S” in MCP Stands for Security - Elena Cross - Medium

MCP, short for Model Context Protocol, is the hot new standard behind how Large Language Models (LLMs) like Claude, GPT, or Cursor integrate with tools and data. It’s been described as the “USB-C for…

Topic 31: How to Reduce Memory Use in Reasoning Models

we explore how combining LightThinker and Multi-Head Latent Attention cuts memory and boosts performance

Topic 33: Slim Attention, KArAt, XAttention and Multi-Token Attention Explained – What’s Really Changing in Transformers?

A Blog post by Ksenia Se on Hugging Face

four advanced attention mechanisms which improve how models handle long sequences, cut memory use and make attention learnable

Self-Attention which lets each token “look” at all others

A look at the ARC-AGI exam designed by French computer scientist François Chollet to show the gulf between AI models' memorized answers and…

By Matteo Wong / The Atlantic. View the full context on Techmeme.

The Llama 4 herd: The beginning of a new era of natively multimodal AI innovation

We’re introducing Llama 4 Scout and Llama 4 Maverick, the first open-weight natively multimodal models with unprecedented context support and our first built using a mixture-of-experts (MoE) architecture.

Model Context Protocol (MCP) an overview

Overview of the Model Context Protocol (MCP) how it works, what are MCP servers and clients, and how to use it.

pydantic-ai/mcp-run-python at main · pydantic/pydantic-ai

Agent Framework / shim to use Pydantic with LLMs

Use MCP servers in VS Code (Preview)

Learn how to configure and use Model Context Protocol (MCP) servers with GitHub Copilot in Visual Studio Code.

From the Jupyter community on Reddit: Jupyter Notebook MCP: work as a professional data analyst

Explore this post and more from the Jupyter community

If Anthropic Succeeds, a Nation of Benevolent AI Geniuses Could Be Born

The brother goes on vision quests. The sister is a former English major. Together, they defected from OpenAI, started Anthropic, and built (they say) AI’s most upstanding citizen, Claude.

A Code Implementation to Building a Context-Aware AI Assistant in Google Colab Using LangChain, LangGraph, Gemini Pro, and Model Context…

From the JupyterNotebooks community on Reddit: Jupyter MCP.: AI to control Jupyter Notebooks

Posted by mehul_gupta1997 - 8 votes and 0 comments

Introduction to MCP: The Ultimate Guide to Model Context Protocol for AI Assistants

LLM Benchmarking: Fundamental Concepts | NVIDIA Technical Blog

The past few years have witnessed the rise in popularity of generative AI and large language models (LLMs), as part of a broad AI revolution.

A Comprehensive Guide to LLM Routing: Tools and Frameworks

Deploying LLMs presents challenges, particularly in optimizing efficiency, managing computational costs, and ensuring high-quality performance. LLM routing has emerged as a strategic solution to these challenges, enabling intelligent task allocation to the most suitable models…

punkpeye/awesome-mcp-servers

A collection of MCP servers

First Look at Reasoning From Scratch: Chapter 1

As you know, I've been writing a lot lately about the latest research on reasoning in LLMs. Before my next research-focused blog post, I wanted to offer something special to my paid subscribers as a thank-you for your ongoing support. So, I've started writing a new book on how…

How DeepSeek Rewrote the Transformer [MLA]

Thanks to KiwiCo for sponsoring today’s video! Go to https://www.kiwico.com/welchlabs and use code WELCHLABS for 50% off your first monthly club crate or for...

What is Q-learning? - Dataconomy

Q-learning is a model-free reinforcement learning algorithm that enables agents to learn optimal actions through interaction with their environment.

Tracing the thoughts of a large language model

In a follow-up to the research that brought us the [delightful Golden Gate Claude](https://simonwillison.net/2024/May/24/golden-gate-claude/) last year, Anthropic have published two new papers about LLM interpretability: - [Circuit Tracing: Revealing Computational …

Anthropic can now track the bizarre inner workings of a large language model

What they found challenges some basic assumptions about how this technology really works.

10 Must-Know Python Libraries for LLMs in 2025

In this article, we explore 10 of the Python libraries every developer should know in 2025.

Function calling with Gemma

Google's Gemma 3 model (the 27B variant is particularly capable, I've been trying it out [via Ollama](https://ollama.com/library/gemma3)) supports function calling exclusively through prompt engineering. The official documentation describes two recommended …

Putting Gemini 2.5 Pro through its paces

There’s a new release from Google Gemini this morning: the first in the Gemini 2.5 series. Google call it “a thinking model, designed to tackle increasingly complex problems”. It’s already …

Introducing 4o Image Generation

At OpenAI, we have long believed image generation should be a primary capability of our language models. That’s why we’ve built our most advanced image generator yet into GPT‑4o. The result—image generation that is not only beautiful, but useful.

What is the hallucination index?

The Hallucination Index is a benchmark that measures the frequency of inaccuracies in large language models, indicating their reliability and contextual understanding.

Quickstart | Mistral AI Large Language Models

[platform_url]//console.mistral.ai/

Improving Recommender Systems & Search in the Age of LLMs

Model architectures, data generation, training paradigms, and unified frameworks inspired by LLMs.

Anthropic just gave Claude a superpower: real-time web search. Here’s why it changes everything

Anthropic launches real-time web search for Claude AI, challenging ChatGPT's dominance while securing $3.5 billion in funding at a $61.5 billion valuation.

Mistral Small 3.1 runs on a MacBook and beats giants - Dataconomy

Paris-based artificial intelligence startup Mistral AI has announced the open-source release of its lightweight AI model, Mistral Small 3.1, which the company

OpenTimes

Spectacular new open geospatial project by [Dan Snow](https://sno.ws/): > OpenTimes is a database of pre-computed, point-to-point travel times between United States Census geographies. It lets you download bulk travel time …

Mistral Small 3.1

Mistral Small 3 [came out in January](https://simonwillison.net/2025/Jan/30/mistral-small-3/) and was a notable, genuinely excellent local model that used an Apache 2.0 license. Mistral Small 3.1 offers a significant improvement: it's multi-modal …

https://www.r-bloggers.com/2025/03/the-ellmer-package-for-using-llms-with-r-is-a-game-changer-for-scientists-2/

The ellmer package for using LLMs with R is a game changer for scientists Why is ellmer a game changer for scientists? In this tutorial we’ll look at how we can access LLM agents through API calls. We’ll use this skill for created structued data fro...

What is catastrophic forgetting? - Dataconomy

Catastrophic Forgetting is a phenomenon where neural networks lose previously learned information when trained on new data, similar to human memory loss.

Top 7 Open-Source LLMs in 2025 - KDnuggets

These models are free to use, can be fine-tuned, and offer enhanced privacy and security since they can run directly on your machine, and match the performance of proprietary solutions like o3-min and Gemini 2.0.

What are model cards? - Dataconomy

Model cards are documentation tools in machine learning that provide essential information about models, promoting transparency, trust, and ethical considerations in AI systems.

How I use LLMs to help me write code

Plus CSS view transitions and a major update to llm-openrouter

Why extracting data from PDFs is still a nightmare for data experts

Countless digital documents hold valuable info, and the AI industry is attempting to set it free.

Cutting-edge web scraping techniques at NICAR

Here's the handout for a workshop I presented this morning at [NICAR 2025](https://www.ire.org/training/conferences/nicar-2025/) on web scraping, focusing on lesser know tips and tricks that became possible only with recent developments …

On GPT-4.5

It’s happening.

The State of LLM Reasoning Models

Part 1: Inference-Time Compute Scaling Methods

Mistral OCR

New closed-source specialist OCR model by Mistral - you can feed it images or a PDF and it produces Markdown with optional embedded images. It's available [via their API](https://docs.mistral.ai/api/#tag/ocr), or …

Mistral OCR | Mistral AI

Introducing the world’s best document understanding API.

Mistral’s new OCR API turns any PDF document into an AI-ready Markdown file

Large language models work particularly well with raw text. Companies that want to create their own AI workflow know that it has become extremely