Terry Rodriguez
terry-remyx
AI & ML interests
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Recent Activity
reacted to salma-remyx's post with ❤️ 2 days ago
Agents are helping me scale the search for my next great idea.
Outrider is a GitHub Action for recommending methods and drafting PRs for your target repo.
VQASynth is an open-source multimodal dataset synthesis pipeline, reflecting the design detailed in SpatialVLM: https://spatial-vlm.github.io/
Outrider helped me discover a pipeline simplification using the recent work: InstructSAM
Check out their repo: https://github.com/DCDmllm/InstructSAM
Now I can focus on the remaining challenges, like porting the new architecture with .gguf conversion
https://github.com/smellslikeml/sam3cpp/blob/feat/instructsam-decoder/docker/Dockerfile
reacted to salma-remyx's post with 🔥 4 days ago
Nobody can be the originator of every great idea. And the rate of innovation in AI is difficult to track in detail.
But the next great idea for your codebase may have been described in open-science publications like arXiv.
Who among us can keep up with reading, smoke testing, adapting every viral method in the feed? (not me)
And what about the long-tail of results that you won't discover for another 6 months? That's what we built Outrider for!
Now I get alerts when candidate methods look like a good fit for the engineering challenges I'm addressing in my application.
I don't waste time running down dead end leads. Instead, I choose to invest my attention into ones which have earned it with evidence.
Try it yourself: https://studio.remyx.ai
Read the docs: https://docs.remyx.ai reacted to salma-remyx's post with 👀 5 days ago
Your coding agent is waiting on you to decide what to try next.
It doesn't originate that decision on its own.
What's usually missing is a way to generate that decision systematically, grounded in something more than the random paper that came across someone's feed that week.
Outrider starts from research with code and data behind it to scope a change applying the core method in your own codebase. A feature branch gets gated on your own evaluation methods before it reaches you in review.
The result is tied to what actually happened in your system, not to a model's read on its own output.
Here's what a code recommendation system looks like end to end.Organizations
