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nomadic-ml
nomadic
HISTORICAL RECORD2024–2024
nomadic-ml / nomadic · Not publicly available

nomadic

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REPOSITORY AT A GLANCE

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This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 12:54:37 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by week2 dated mentions

Observed mentions: 2024-09-05 18:14:46 UTC to 2024-11-08 20:17:11 UTC. Weeks start Monday, UTC.

012024-09-02 00:00:00 UTC to 2024-09-09 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsSep 22024-09-09 00:00:00 UTC to 2024-09-16 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-09-16 00:00:00 UTC to 2024-09-23 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-09-23 00:00:00 UTC to 2024-09-30 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-09-30 00:00:00 UTC to 2024-10-07 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsSep 302024-10-07 00:00:00 UTC to 2024-10-14 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-10-14 00:00:00 UTC to 2024-10-21 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-10-21 00:00:00 UTC to 2024-10-28 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-10-28 00:00:00 UTC to 2024-11-04 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-11-04 00:00:00 UTC to 2024-11-11 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsNov 4

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Sep 22024-09-02 00:00:00 UTC2024-09-09 00:00:00 UTC110
Sep 92024-09-09 00:00:00 UTC2024-09-16 00:00:00 UTC000
Sep 162024-09-16 00:00:00 UTC2024-09-23 00:00:00 UTC000
Sep 232024-09-23 00:00:00 UTC2024-09-30 00:00:00 UTC000
Sep 302024-09-30 00:00:00 UTC2024-10-07 00:00:00 UTC000
Oct 72024-10-07 00:00:00 UTC2024-10-14 00:00:00 UTC000
Oct 142024-10-14 00:00:00 UTC2024-10-21 00:00:00 UTC000
Oct 212024-10-21 00:00:00 UTC2024-10-28 00:00:00 UTC000
Oct 282024-10-28 00:00:00 UTC2024-11-04 00:00:00 UTC000
Nov 42024-11-04 00:00:00 UTC2024-11-11 00:00:00 UTC110

What Hacker News says

2 sources
varunkrishnan17·Nov 8, 2024Submission

Show HN: RL Agent that can auto-optimize your LLM prompts

Hey everyone! Along with my team, I've developed a reinforcement learning system that automatically optimizes LLM prompts, complete with a visualization feature to track both prompt structure and learning progress over time. Take a look here: https://nomadic-ml.github.io/nomadic/cookbooks/Nomadic_Promp... Check out our website too:https://www.nomadicml.com/ In terms of how this visualization works: The RL Prompt Optimizer employs a reinforcement learning framework to iteratively improve prompts used for language model evaluations. At each episode, the agent selects an action to modify the current prompt based on the state representation, which encodes features of the prompt. The agent receives rewards based on a multi-metric evaluation of the model's responses, encouraging the development of prompts that elicit high-quality answers. And s
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ee our github repo! https://github.com/nomadic-ml/nomadic
14 points · Open discussion
mustafabal·Sep 5, 2024Submission

Show HN: Nomadic – Minimize RAG Hallucinations with 1 Hyperparameter Experiment

Hey HN! Mustafa, Lizzie, and Varun here from NomadicML (https://nomadicml.com). We’re excited to show you Nomadic (https://github.com/nomadic-ml/nomadic): a platform focused on parameter search to continuously optimize AI systems. Here’s a simple demo notebook where you get the best-performing, statistically significant configurations for your RAG — and improve hallucination metrics by 4X in just 5 minutes — with a single Nomadic experiment: https://tinyurl.com/4xmaryyw Our lightweight library is now live on PyPI (`pip install nomadic`). Try one of the README examples :) Input your model, define an evaluation metric, specify the dataset, and choose which parameters to test. Nomadic emerged from our frustration with existing HPO (hyperparameter optimization) solutions. We heard over and over that for the sake of deploying fast, folks resor
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t to setting HPs through a single, expensive grid search or better yet, intuition-based “vibes”. From fine-tuning to inference, small tweaks to HPs can have a huge impact on performance. We wanted a tool to make that “drunken wander” systematic, quick, and interpretable. So we started building Nomadic - our goal is to create the best parameter search platform out there for your ML systems to keep your hyperparameters, prompts, and all aspects of your AI system production-grade. We started aggregating top parameter search techniques from popular tools and research (Bayesian Optimizations, cost-frugal flavors). Among us: Built Lyft’s driver earnings platform, automated Snowflake’s just-in-time compute resource allocation, became a finalist for the INFORMS Wagner Prize (top prize in industrial optimization), and developed a fintech fraud screening system for half a million consumers. You might say we love optimization. If you’re building AI agents / applications across LLM safety, fintech, support, or especially compound AI systems (multiple components > monolithic models), and want to deeply understand your ML system’s best levers to boost performance as it scales - get in touch. Nomadic is being actively developed. Up next: Supporting text-to-SQL pipelines (TAG) and a Workspace UI (preview it at https://demo.nomadicml.com). We’re eager to hear honest feedback, likes, dislikes, feature requests, you name it. If you’re also a optimization junkie, we’d love for you to join our community here https://discord.gg/PF869aGM
95 points · Open discussion

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