renee-jia

renee-jia / latent-feed

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Automated AI news aggregation that feeds directly into your Obsidian vault. Stay current on the latest LLM research, trending repos, and breakthroughs — curated daily

14
3
100% credibility
Found Mar 23, 2026 at 14 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

Latent Feed is a tool that collects recent AI/ML news from sources like ArXiv, blogs, GitHub Trending, Hacker News, Papers with Code, and Reddit, filters and categorizes items by user interests, optionally generates summaries, and outputs daily digests to Obsidian notes or email.

How It Works

1
📰 Discover Latent Feed

You find this handy tool that gathers the latest AI news from papers, blogs, and online discussions into one easy morning read.

2
📥 Bring it home to your computer

You download it and get it set up with a quick install so it's ready to use.

3
📓 Tell it where your notes live

You show it the folder for your personal note-taking app, like Obsidian, so it can add the news right there.

4
Pick your favorite extras
🤖
Add smart summaries

Turn on quick AI recaps to make skimming even faster.

📧
Set up email delivery

Add your email so the digest lands in your inbox too.

✅
Keep it simple

Skip extras and just get the basic organized list.

5
✨ Run it for the first time

Hit go and watch as it pulls together today's top stories, sorts them by topic, and drops a beautiful summary into your notes.

6
⏰ Set it to run every morning

Schedule it to automatically fetch and deliver fresh news at your wake-up time.

☕ Wake up to your perfect briefing

Every day, open your notes or email to a tidy, relevant roundup of what's new in AI—saving you hours of searching.

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AI-Generated Review

What is latent-feed?

Latent-feed is a Python tool that automates a daily news feed on LLM research, pulling from ArXiv papers, GitHub trending repos, Hacker News, Reddit, Papers with Code, and blogs like OpenAI and Anthropic. It filters for relevance, categorizes into topics like agents or interpretability, adds optional AI summaries via Claude or Ollama, and injects clean Markdown into your Obsidian vault or emails it as a newsletter. No more manual tab-hopping—set your vault path in config.yaml, run `python main.py`, and cron it for mornings.

Why is it gaining traction?

It stands out with seamless Obsidian integration, dropping categorized digests into daily notes, plus email output for teams. GitHub Actions support enables automated deployment without local runs, and the `--dry-run` flag lets you preview instantly. Developers love the automated newsletter creation that's better than expected, skipping noisy sources for signal-only feeds.

Who should use this?

ML engineers tracking frontier models and repos, researchers scanning ArXiv without overload, or Obsidian power-users building knowledge graphs from daily AI breakthroughs. Ideal for solo devs or small teams using automated GitHub pipelines to stay sharp on reasoning, safety, and systems papers.

Verdict

Worth forking for personal use if you're in AI—solid docs and quick setup make it production-ready despite 14 stars and 1.0% credibility score signaling early maturity. Add tests for reliability before team rollout.

(178 words)

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