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Concept Artists Say Generative AI References Only Make Their Jobs Harder

https://thisweekinvideogames.com/feature/concept-artists-in-games-say-generative-ai-references-on...
1•KittenInABox•53s ago•0 comments

Show HN: PaySentry – Open-source control plane for AI agent payments

https://github.com/mkmkkkkk/paysentry
1•mkyang•2m ago•0 comments

Show HN: Moli P2P – An ephemeral, serverless image gallery (Rust and WebRTC)

https://moli-green.is/
1•ShinyaKoyano•12m ago•0 comments

The Crumbling Workflow Moat: Aggregation Theory's Final Chapter

https://twitter.com/nicbstme/status/2019149771706102022
1•SubiculumCode•16m ago•0 comments

Pax Historia – User and AI powered gaming platform

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2•Osiris30•17m ago•0 comments

Show HN: I built a RAG engine to search Singaporean laws

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1•ambitious_potat•23m ago•0 comments

Scams, Fraud, and Fake Apps: How to Protect Your Money in a Mobile-First Economy

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Porting Doom to My WebAssembly VM

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Cognitive Style and Visual Attention in Multimodal Museum Exhibitions

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Full-Blown Cross-Assembler in a Bash Script

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1•grajmanu•30m ago•0 comments

Logic Puzzles: Why the Liar Is the Helpful One

https://blog.szczepan.org/blog/knights-and-knaves/
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Optical Combs Help Radio Telescopes Work Together

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2•toomuchtodo•47m ago•1 comments

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The Tao of Programming

http://www.canonical.org/~kragen/tao-of-programming.html
1•alexjplant•54m ago•0 comments

Forcing Rust: How Big Tech Lobbied the Government into a Language Mandate

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3•akagusu•54m ago•0 comments

PanelBench: We evaluated Cursor's Visual Editor on 89 test cases. 43 fail

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https://github.com/oozoofrog/mcp-baepsae
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Make Trust Irrelevant: A Gamer's Take on Agentic AI Safety

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Hello world does not compile

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Protocol Validation with Affine MPST in Rust

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Female Asian Elephant Calf Born at the Smithsonian National Zoo

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Automatic Programming Returns

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1•benrules2•1h ago•1 comments
Open in hackernews

Show HN: OctaneDB – Fast, Open-Source Vector Database for Python

https://github.com/RijinRaju/octanedb
33•rijin_r•5mo ago
OctaneDB is an open-source vector database for Python that focuses on ultra-fast similarity search for high-dimensional data—perfect for AI/ML, semantic search, and large-scale document or embedding retrieval.

What does it do?

Store, index, and search millions of embeddings (text, images, etc.) with sub-millisecond query time.

Supports in-memory and efficient HDF5 persistent storage.

Integrates seamlessly with sentence-transformers for automatic text embedding.

Key Features:

10x faster than Pinecone or ChromaDB for vector search and batch insertions.

Advanced indexing: HNSW (approximate nearest neighbor), FlatIndex

Batch search, advanced metadata filtering, GPU acceleration

Comments

ozgrakkurt•5mo ago
Please stop with these LLM generated readme files. It burns the eyes.

Just take 10 minutes to write something that explains the project.

As soon as I see this README I assume the code is generated(worthless) as well

ImPrajyoth•5mo ago
Someone wise once said

- Don't judge a book by it's cover

mfitzp•5mo ago
Someone even wiser once said:

- Don’t give your book a shit cover because it will put people off.

Bishonen88•5mo ago
Looking at the repo, everything seems too clean and pristine. There's only 5 commits. Not that it matters, but was the whole thing vibe coded? If so, I wonder if mentioning this in the Readme would be helpful to potential users.
rijin_r•5mo ago
Thanks for pointing it out! The README is a first draft—I’ll update it ASAP to better explain what OctaneDB does and cover any AI-generated components.
JSR_FDED•5mo ago
This looks very good, easy to understand. Do you have a sense for how much RAM it uses (not for storing the vectors themselves - those I’ll keep in a file), but when doing a search? I have one use case where it could run on a VPS provided its memory use doesn’t balloon too much.
icemanx•5mo ago
Definitely vibe code, and I agree with the others - please mention it in the README if you want people to use AI generated code. You are not the mind behind it

Update: Looking through your code, I already found within 5 minute flaws, since it is obvious that you have not written it (looking at your past work, I doubt you even understand what it does), I will not even point the issues out.

hmcamp•5mo ago
Hey, I’m curious. How can you tell that it was vibe coded?
brandonasuncion•5mo ago
Claims of being "10x faster performance than existing solutions" using a HNSW written entirely in Python is enough to raise alarm bells, vibecoded or not.
rf15•5mo ago
Looking at your code, I don't think you understand any of the regular DB requirements, let alone how to implement a vector database that is actually fast. Because, let me tell you: this isn't it.

Please get more experience and use AI less. It's not a good look, and if it's vibe coded it's not your code anyway, it's just you asking somebody else to do it (at best). You don't want to be an expert in asking others to do your work.

Best of luck on your turn around.

dikei•5mo ago
Big claims with not a single benchmark to back them up
redskyluan•5mo ago
Curious—why the shift from a Milvus-compatible API to a Chroma-compatible one? And of course, something in Python… because that’s obviously the fastest way to conquer the world.