Discussion intelligence

Where the AI market is talking

A source-linked Hacker News monitor for the tracked company graph. These are attributable public discussions—not sentiment, endorsements, or unverified company facts.

Attributed mentions

2105

Across all collected Hacker News results

Companies represented

12

Exact-name monitor matches only

Collection source

Hacker News

Latest new record seen

Source-backed records

Latest market discussions

HN v1 · Reddit and X require approved API adapters

Showing 21012105 of 2105 matching discussions

Weaviate
comment

Ask HN: Who wants to be hired? (April 2026)

Location: Remote (Rochester, NY) Willing to relocate: No Technologies: Python, LangChain/LangGraph, RAG, Weaviate, FastAPI, React, PostgreSQL, Docker, Anthropic/OpenAI/Gemini APIs, MCP, multi-agent systems Résumé/CV: github.com/forkei Resume available on request, please send me an email. Email: olivier.couthaud@gmail.com CS/AI accelerated MS student at RIT. I build production multi-agent systems and RAG pipelines. Shipped: - Enterprise RAG pipeline (Weaviate + Oracle DB) for a finance client - VOS: open-source multi-agent virtual OS with MCP (github.com/Forkei/VOS-public) - rookery.network: live social platform with GNN paper recommendations - VibeOS: CLI-native agentic OS, faster than MCP tools (in progress) 5/5 on Wyzant, 6+ client projects. …

Weaviate
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Weaviate Podcast on Substack

https://weaviatepodcast.substack.com/?r=82hn51&utm_campaign=...

Weaviate
story
10 comments

Multi-Vector Search with Amélie Chatelain and Antoine Chaffin

Hey everyone! I am SUPER EXCITED to publish a new episode of the Weaviate Podcast with Amélie Chatelain and Antoine Chaffin on Multi-Vector Search! Amélie, Antoine, and the LightOn team are on fire! They are making breakthrough after breakthrough in Search with Multi-Vector, Late Interaction retrieval models. This podcast covers all sorts of topics, starting with the motivation of Multi-Vector Search to its particular successes in code with ColGrep, as well as reasoning-intensive and multimodal retrieval. We also covered the cost of MaxSim and Multi-Vector Storage and how MUVERA and PLAID can help. If that wasn't enough, the podcast concludes with their new work on ColBERT-Zero and PyLate! A lot of big takeaways from this one, I hope you find it useful! YouTube: https://www.yout…

Methodology: HN Search returns recent public items matching a monitored company name. AIIStack stores a short normalized excerpt and the original link, deduplicates by company/provider/item ID, and creates an activity signal only after a threshold of newly observed records. Review the original discussion before making a decision.