Scott Condron @_ScottCondron
Helping build AI/ML dev tools at @weights_biases. I post about machine learning, data visualisation, software tools. scottcondron.com Dublin, Ireland Joined April 2018-
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Scott Condron retweeted
Ok, some big news that I've been sitting on for a minute: @OpenPipeAI is getting acquired by @CoreWeave!
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Scott Condron retweeted
🧵 We acquired OpenPipe! OpenPipe's ART framework makes it easy to beat foundation models with smaller open models on real problems, using reinforcement learning.
Is there a library that creates a completion-compatible API for a given python function?
Scott Condron retweeted
🚨 We’ve just published a recipe to train a frontier-level deep research agent using RL. With just 30 hours on an H200, any developer can now beat Sonnet-4 on DeepResearch Bench using open-source tools. (Thread 🧵)
Scott Condron retweeted
fine tuning hasn’t taken off (yet) because (1) you need to have a good idea of what you want to improve, and (2) you need a way to label data at scale. most builders don’t know enough about (1), mostly because they have little proper monitoring. until recently, (2) meant time…
fine tuning hasn’t taken off (yet) because (1) you need to have a good idea of what you want to improve, and (2) you need a way to label data at scale. most builders don’t know enough about (1), mostly because they have little proper monitoring. until recently, (2) meant time…
Scott Condron retweeted
W&B Inference is now on @OpenRouterAI! You can use @AIatMeta's Llama 3.3 70B Instruct today, with more models rolling out in the coming weeks.
Scott Condron retweeted
Been playing quite a bit with optimizers, this one about Muon on diffusion. Here is sweep of Adam LR, very clean, great candidate for mUP (middle is eval/loss on params and right is eval/loss on EMA params, common in diffusion).
Scott Condron retweeted
I enjoyed reading this LLM-powered data application paper from UCSF: "When the Domain Expert Has No Time and the LLM Developer Has No Clinical Expertise." It gets at the heart of many of my favorite things: accelerating productivity with data analysis, evals in cross-functional…
Scott Condron retweeted
GEPA has landed in DSPy 3.0!! 🛠️🧰 I am SUPER EXCITED to publish a new video sharing my experience using GEPA to optimize a Listwise Reranker! 🚀 The main takeaway I hope to share is how to monitor your GEPA optimization run to know if you are on the right track, or need to…
Scott Condron retweeted
So this is what dataset with zero-flaws looks like
niche tip: If you're looking to view histograms / distributions of data per step in wandb, you can log using `wandb.Histogram(loss_array)` and you get a plot where you can hover over each step and see the distribution change during training
Scott Condron retweeted
BIG LAUNCH: @deepseek_ai's V3.1 is now live on W&B Inference! One model, two modes: toggle between high-speed 'Non-Think' & deep 'Think'. Priced at just $0.55/$1.65 per 1M tokens, it’s a game-changer for building intelligent agents. Want $50 in free credits? Details below.
Scott Condron retweeted
With just a few lines of code, Feng’s (@fengyao1909) suggested fix—applying importance sampling on the behavior policy—resolved the training instability in my case (oat). I believe the result can generalize to other RL frameworks as well. Great work, Feng!
logging a bunch of different media types to Weave to test how they render, something pretty cool about seeing them all in a table together
Scott Condron retweeted
"My biggest problem with evals? I have no idea where to start" Stop feeling overwhelmed with all the tools, models, etc. Take a deep breath. Start simple, iterate quickly.
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