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Everything AION read, in seven sections. Pick one, a topic or a time window.
VideoStop Renting Intelligence: The Train-to-Deploy Loop for Specialized AI — Fireworks AI
Jetashree Ravi, who leads part of the applied machine learning team at Fireworks AI, explains how teams move from closed models to open ones without losing quality.
I trained a 414k-parameter transformer to fly a boids flock, then tested whether the rules a probe can read are the ones it uses [P]
I wrote a small boid simulator (12 birds), recorded it flying, and trained a transformer to predict each bird's next move without it knowing about any boid rules.
Converting dense models into Mixture-of-Experts
For the past few weeks I've been trying out converting existing dense models to sparse Mixture-of-Experts models, with no pretraining from scratch.
Qwen Image 2.1 Turbo - extend 'magic' 8 steps sigmas further
So, I've decided to try Qwen Image 2.1 Turbo with the following 'magic' sigmas, taken directly from their Diffusers implementation:
VideoHill-Climbing Skills: Improve Agents Without Changing the Model — Shubhankar Srivastava, Browserbase
Shubhankar Srivastava uses that uneven progress to show how browser agents can learn a task without changing model weights.
VideoParameter Golf with AutoResearch — Vayum Arora, Zhengyao Jiang, Dixing Xu & Dhruv Srikanth, Weco AI
Zhengyao Jiang introduces autoresearch as repeated proposals and evaluations, and Dixing Xu explains the team's Aiden system and its contributions to OpenAI's Parameter Golf challenge.