I added [schema support](https://simonwillison.net/2025/Feb/28/llm-schemas/) to this plugin which adds support for the [Mistral API](https://docs.mistral.ai/api/) to LLM. Release notes: - Support for LLM [schemas](https://llm.datasette.io/en/stable/schemas.html)…
This release of the `llm-ollama` plugin adds support for [schemas](https://simonwillison.net/2025/Feb/28/llm-schemas/), thanks to a [PR by Adam Compton](https://github.com/taketwo/llm-ollama/pull/36). Ollama provides very robust support for this pattern thanks to their…
Today, we’re announcing Claude 3.7 Sonnet, our most intelligent model to date and the first hybrid reasoning model generally available on the market.
OpenAI’s Deep Research is built for me, and I can’t use it. It’s another amazing demo, until it breaks. But it breaks in really interesting ways.
Solid techniques to get really good results from any LLM
OpenAI's president Greg Brockman recently shared this cool template for prompting their reasoning models o1/o3. Turns out, this is great for ANY reasoning… | 32 comments on LinkedIn
Comparison and ranking the performance of over 30 AI models (LLMs) across key metrics including quality, price, performance and speed (output speed - tokens per second & latency - TTFT), context window & others.
BERT is an open source machine learning framework for natural language processing (NLP) that helps computers understand ambiguous language by using context
I share my preferences for LLMs, image models, AI video, AI music, AI-powered research, and more. These are the AI tools I regularly use or recommend to others.
Do my tears surprise you? Strong CEOs also cry.
Neat open source project on the GitHub organisation for the UK government's Department for Business and Trade: a "Python virtual filesystem for SQLite to read from and write to S3." …
I just released llm-smollm2, a new plugin for LLM that bundles a quantized copy of the SmolLM2-135M-Instruct LLM inside of the Python package. This means you can now pip install …
In this article, I will describe the four main approaches to building reasoning models, or how we can enhance LLMs with reasoning capabilities. I hope this p...
I started running a basic link blog on this domain back in November 2003—publishing links (which I called “blogmarks”) with a title, URL, short snippet of commentary and a “via” …
Check out this comparison of 5 AI frameworks to determine which you should choose.
The Reinforcement Learning from Human Feedback Book
In our previous tutorial, we built an AI agent capable of answering queries by surfing the web. However, when building agents for longer-running tasks, two critical concepts come into play: persistence and streaming. Persistence allows you to save the state of an agent at any…
Aidan Bench attempts to measure in LLMs. - aidanmclaughlin/AidanBench
o3-mini is out today. As with other o-series models it’s a slightly difficult one to evaluate—we now need to decide if a prompt is best run using GPT-4o, o1, o3-mini …
How a Key-Value (KV) cache reduces Transformer inference time by trading memory for computation
The field of artificial intelligence is evolving rapidly, with increasing efforts to develop more capable and efficient language models. However, scaling these models comes with challenges, particularly regarding computational resources and the complexity of training. The…
The unusual timing of the Qwen 2.5-Max's release points to the pressure DeepSeek's meteoric rise in the past three weeks has placed on overseas rivals and domestic competition.
A recipe for reasoning LLMs
AI has entered an era of the rise of competitive and groundbreaking large language models and multimodal models. The development has two sides, one with open source and the other being propriety models. DeepSeek-R1, an open-source AI model developed by DeepSeek-AI, a Chinese…
Johann Rehberger snagged a copy of the [ChatGPT Operator](https://simonwillison.net/2025/Jan/23/introducing-operator/) system prompt. As usual, the system prompt doubles as better written documentation than any of the official sources. It asks users …
Developers have tricks to stop artificial intelligence from making things up, but large language models are still struggling to tell the truth, the whole truth and nothing but the truth.
This article covers 12 influential AI research papers of 2024, ranging from mixture-of-experts models to new LLM scaling laws for precision..
New release of my [LLM](https://llm.datasette.io/) CLI tool and Python library. A bunch of accumulated fixes and features since the start of December, most notably: - Support for OpenAI's [o1 model](https://platform.openai.com/docs/models#o1) …
The company built a cheaper, competitive chatbot with fewer high-end computer chips than U.S. behemoths like Google and OpenAI, showing the limits of chip export control.
DeepSeek are the Chinese AI lab who dropped the best currently available open weights LLM on Christmas day, DeepSeek v3. That model was trained in part using their unreleased R1 …
The rapid advancement and widespread adoption of generative AI systems across various domains have increased the critical importance of AI red teaming for evaluating technology safety and security. While AI red teaming aims to evaluate end-to-end systems by simulating real-world…
New paper from Microsoft describing their top eight lessons learned red teaming (deliberately seeking security vulnerabilities in) 100 different generative AI models and products over the past few years. …
This is a standalone notebook implementing the popular byte pair encoding (BPE) tokenization algorithm, which is used in models like GPT-2 to GPT-4, Llama 3,...
Let’s start the year on an exciting note
We picked 50 paper/models/blogs across 10 fields in AI Eng: LLMs, Benchmarks, Prompting, RAG, Agents, CodeGen, Vision, Voice, Diffusion, Finetuning. If you're starting from scratch, start here.
Note: gist: https://gist.github.com/bjpcjp/117ecf144c062c3c933f2690e7ece5c2
Intelligent agents are considered by many to be the ultimate goal of AI. The classic book by Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach (Prentice Hall, 1995), defines the field of AI research as “the study and design of rational agents.”
Note: I have expanded the previous summaries of each section and paragraph from Chip Huyen's article "Agents," published on January 7, 2025, by including links to the resources cited within the article. **Agent Overview** 1. The term "agent" has been used in various engineering contexts, including software agents, intelligent agents, user agents, conversational agents, and reinforcement learning…
A comprehensive list of some of the most impactful generative papers from last year
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Two powerful workflows that unlock everything else. Intro: Golden Age of AI Tools and AI agent frameworks begins in 2025.
A long reading list of evals papers with recommendations and comments by the evals team.
A lot has happened in the world of Large Language Models over the course of 2024. Here’s a review of things we figured out about the field in the past …
Using knowledge graphs and AI to retrieve, filter, and summarize medical journal articles
Note: requires weaviate account 25 per month lowest tier
A detailed analysis of ChatGPT search and Google's performance across 62 queries, with scoring metrics and practical examples.
Each response was meticulously fact-checked and evaluated for alignment with potential user intents.
two-thirds of which were informational
Plus building Python tools with a one-shot prompt using uv run and Claude Projects
A curated list of interesting LLM-related research papers from 2024, shared for those looking for something to read over the holidays.
Compute costs scale with the square of the input size. That’s not great.
This is probably why Google charges twice as much, per token, for Gemini 1.5 Pro once the context gets longer than 128,000 tokens. Generating token number 128,001 requires comparisons with all 128,000 previous tokens, making it significantly more expensive than producing the first or 10th or 100th…
In a series of papers, Princeton computer scientist Tri Dao and several collaborators have developed FlashAttention, which calculates attention in a way that minimizes the number of these slow memory operations.
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step - rasbt/LLMs-from-scratch