Here it is people: test proving taumode 🍄🍄🍄 Since the publication of my latest paper I have received suggestions about testing my ideas on a real dataset. Here it is! A complete unroll of the CVE dataset from 1999 to 2025 to: ⚙️ build a fine-tuned embedder on domain-specific text 🧩 generate a taumode index for the embeddings ❔❔❔ query the index 🧮 check the quality of the results against cosine similarity The results demonstrate that we can search better than current vector databases do 👇👇👇 008_arrowspace_proof_of_concept_energy_informed_search - AI Research Engineering Link to code available in the blog post. Please consider sponsoring me on Github -> https://github.com/sponsors/Mec-iS #vectorDB #embeddings #search #ranking #matching taumode: a new way of searching vector databases was originally published in Coinmonks on Medium, where people are continuing the conversation by highlighting and responding to this storyHere it is people: test proving taumode 🍄🍄🍄 Since the publication of my latest paper I have received suggestions about testing my ideas on a real dataset. Here it is! A complete unroll of the CVE dataset from 1999 to 2025 to: ⚙️ build a fine-tuned embedder on domain-specific text 🧩 generate a taumode index for the embeddings ❔❔❔ query the index 🧮 check the quality of the results against cosine similarity The results demonstrate that we can search better than current vector databases do 👇👇👇 008_arrowspace_proof_of_concept_energy_informed_search - AI Research Engineering Link to code available in the blog post. Please consider sponsoring me on Github -> https://github.com/sponsors/Mec-iS #vectorDB #embeddings #search #ranking #matching taumode: a new way of searching vector databases was originally published in Coinmonks on Medium, where people are continuing the conversation by highlighting and responding to this story

taumode: a new way of searching vector databases

Author: Medium

Source: Medium

2025/11/02 13:48

1 min read

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Here it is people: test proving taumode 🍄🍄🍄

Since the publication of my latest paper I have received suggestions about testing my ideas on a real dataset. Here it is!

A complete unroll of the CVE dataset from 1999 to 2025 to:
⚙️ build a fine-tuned embedder on domain-specific text
🧩 generate a taumode index for the embeddings
❔❔❔ query the index
🧮 check the quality of the results against cosine similarity

The results demonstrate that we can search better than current vector databases do 👇👇👇

008_arrowspace_proof_of_concept_energy_informed_search - AI Research Engineering

Link to code available in the blog post.

Please consider sponsoring me on Github -> https://github.com/sponsors/Mec-iS

#vectorDB #embeddings #search #ranking #matching

taumode: a new way of searching vector databases was originally published in Coinmonks on Medium, where people are continuing the conversation by highlighting and responding to this story.

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