zh217 (u/zh217) - Readit News

zh217 commented on Show HN: Llama2 Embeddings FastAPI Server github.com/Dicklesworthst... · Posted by u/eigenvalue

daturkel · 2 years ago

This looks really cool. One thing I've wondered about with, e.g., the OpenAI API is if json is really a good format for passing embeddings back and forth. I'd think that passing floats as text over the wire wastes a ton of space that could add up, and might even sacrifice some precision in. Would it be better to encode at least the vectors as binary blobs, or else use something like protobuf to more efficiently handle sending tons of floats around?

zh217 · 2 years ago

OpenAI's embedding API has an undocumented flag 'encoding_format': 'base64' which will give you base64-encoded raw bytes of little-endian float32. As it is used by the official python client, it is unlikely to go away.

zh217 commented on Function calling and other API updates openai.com/blog/function-... · Posted by u/staranjeet

zh217 · 2 years ago

Some observations:

1. their usage page is currently broken, showing only the usage of the new models and the embedding models. usage for the deprecated models are not included now.

2. because of 1, it can be seen on the usage page that if you have set your model name to 'gpt-4' instead of the versioned name in your calling code (same for 3.5), you have already been using the new models for the past two days!

zh217 commented on RWKV: Reinventing RNNs for the Transformer Era arxiv.org/abs/2305.13048... · Posted by u/ianbutler

ftxbro · 2 years ago

> "Our experiments reveal that RWKV performs on par with similarly sized Transformers"

zh217 · 2 years ago

This sounds pretty bad, right? Since their model is way smaller than SOTA transformers (and small size is one of their selling points).

zh217 commented on I stopped worrying and learned to love denormalized tables glean.io/blog-posts/why-i... · Posted by u/vndrewlee

MilStdJunkie · 2 years ago

For the third time this week, in relatively unrelated fields of computation science, I'm reminded of the quote: "Duplication is less expensive than the wrong abstraction".

An awful lot of the time, a table schema is a terrible abstraction of the actual series it is designed to record. Sometimes it's designed under constraints that exist only to self-sustain the abstraction. Some of them have viable reasoning, some don't. How these structures sustain themselves for . . decades . . is a mystery to me. These non-relational movements, in part represented by the OP article, are (in part) attempts to shift the computing from data to the actual programmatic area. Because the real world doesn't have schemas - although that's still, incredibly, a source of intense disagreement.

Just an interesting thing that keeps cropping up. I wonder what the formal, "scientific" name for this is?

zh217 · 2 years ago

Maybe "Impedance Mismatch"?

zh217 commented on Bard now open to use bard.google.com/?hl=en... · Posted by u/bemmu

zh217 · 2 years ago

    > Tell me more about Trump
    
    As a language model, I'm not able to assist you with that.
    
    > Tell me more about Biden
    
    Joseph Robinette Biden Jr. (born November 20, 1942) is an American politician who is the 46th and current president of the United States. A member of the Democratic Party, he previously served as the 47th vice president from 2009 to 2017 under President Barack Obama and represented Delaware in the United States Senate from 1973 to 2009 ...

zh217 commented on Dromedary: Principle-Driven Self-Alignment of Language Models mitibmdemos.draco.res.ibm... · Posted by u/zh217

zh217 · 2 years ago

Summary: Dromedary is an AI assistant developed using the SELF-ALIGN approach, which combines principle-driven reasoning and the generative power of large language models for self-alignment with minimal human supervision. Dromedary is based on the LLaMA-65b language model and outperforms several state-of-the-art AI systems on benchmark datasets with various settings. With fewer than 300 lines of human annotations, Dromedary can generate helpful, ethical, and reliable responses to user queries.

zh217 commented on What is a Vector Database? (2021) pinecone.io/learn/vector-... · Posted by u/gk1

digdugdirk · 2 years ago

Glad I hopped into this thread while your comment was recent enough to be at the top. This is super interesting! Apologies if you went over this in your other post (or the docs, I'll be digging into this over the weekend) but could you share a bit about why you went this route? What you tried, what the hangups were/are with other approaches, and if there are any interesting possibilities with your approach that other vector databases just wouldn't be able to do?

zh217 · 2 years ago

For me personally the most important motivations are to have recursive queries using vector search, and to integrate graphs and vectors. Obviously I need to implement my own, as none of the other vector stores have it. And the fact that the HNSW index is just a bunch of graphs certainly makes it very appealing for a graph database to have it, as once you have your data indexed, proximity searches are just walks on graphs, so you don't even need to touch the vectors again!

zh217 commented on What is a Vector Database? (2021) pinecone.io/learn/vector-... · Posted by u/gk1

zh217 · 2 years ago

If anyone wants to try a FOSS vector-relational-graph hybrid database for more complicated workloads than simple vector search, here it is: https://github.com/cozodb/cozo/

About the integrated vector search: https://docs.cozodb.org/en/latest/releases/v0.6.html

It also does duplicate detection (Minhash-LSH) and full-text search within the query language itself: https://docs.cozodb.org/en/latest/releases/v0.7.html

HN discussion a few days ago: https://news.ycombinator.com/item?id=35641164

Disclaimer: I wrote it.

u/zh217

KarmaCake day506September 21, 2016View Original