Maxime Rivest 🧙♂️🦙🐧 @MaximeRivest
Easy LLM context for all! ✨pip install attachments Inspired by: ggplot2, DSPy, claudette, dplyr, OpenWebUI! Follow for: API design, AI, and Data 🐍CC📜🛠 maker maximerivest.github.io/attachments/ Ottawa 🇨🇦 Joined January 2018-
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We raised $250M to accelerate building AI's unified compute layer! 🔥 We’re now powering trillions of tokens, making AI workloads 4x faster 🚀 and 2.5x cheaper ⬇️ for our customers, and welcomed 10K’s of new developers 👩🏼💻. We're excited for the future!
For the dspy aficionado, here are a few somewhat hidden utils I wish I had learned to use earlier. In this particular case, I wanted my Qwen model to stop overthinking.
I despise having to type out the name of a keyword argument when the method or function only take 1 or 2.
Qwen has overtake Anthropic in my list of top 4 AI models/lab. I am happy to see a top lab publish so many open models, hope they never stop!
We beat Nvidia’s cuBLAS kernels on B200s in 170 LOC. Using zero CUDA. Just pure Mojo. Here’s exactly how we went from 1% to 106% of Nvidia benchmark perf from scratch (with code) 👇🧵
Every time, I think, ah, oh no, dspy does not support that... but then thanks to the fact that it's open-source and I can investigate the code, I can just change the right thing at the right place and boom! With only that code below you can make it so that any DSPy optimizers…
That's what I want!
In DSPy, we often talk about prompts being brittle and needing to be model-specific. But what happens if we optimize for cross-model performance?
Qwen3-Omni is new sota any-to-any model🔥 everything you have to know ⤵️ > a 30B MoE model with 3B active params, comes in three variants: instruct, thinking and captioner 🤩 thinking is for reasoning and captioner is for robust speech generation 🗣️ > it understands everything…
X released some info about its algorithms recently, and I see lots of people referring to it. I’ve never really cared much about the algorithm, neither on YouTube nor here. I posted 10+ videos in a month and then stopped for 5 years. One of those videos got 750,000 views, even…
I love how extensible dspy is. I feel zero lock-in, and I really like that. I wanted to use dspy with a self-hosted, in-process local LLM on a Mac. In about a day of work, I was able to wrap mlx-lm and use it as a model backend for dspy. Beautiful stuff!
My biggest pet peeve in dspy is when the optimizers go crazy, running nonstop through lots of failures and errors. Let’s fix that. It’s very scary and jarring for users. It’s also quite opaque.

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