nowfound

AI · March 3, 2021

NN

NNext.net – A Firebase-like managed vector storage for ML applications

Hi HN. Peter here. As a machine learning engineer, I mostly think in terms of feature vectors, embeddings, and matrices. One of the most useful byproducts of deep neural networks is embeddings because they allow us to represent high-dimensional data in terms of lower-dimensional latent vectors. These feature vectors can be used for downstream applications like similarly search, recommendation systems and near duplicate detection. As an ML engineer, I was frustrated by the lack of a datastore in which vectors are first-class citizens. As a result, most ML engineers, including myself, end up…

Alternatives

What it does

In the maker’s words, at launch

Hi HN. Peter here. As a machine learning engineer, I mostly think in terms of feature vectors, embeddings, and matrices. One of the most useful byproducts of deep neural networks is embeddings because they allow us to represent high-dimensional data in terms of lower-dimensional latent vectors. These feature vectors can be used for downstream applications like similarly search, recommendation systems and near duplicate detection. As an ML engineer, I was frustrated by the lack of a datastore in which vectors are first-class citizens. As a result, most ML engineers, including myself, end up using awkward workarounds to store vectors such as arrays in SQL/NoSQL databases, stringifying vectors and storing them as text in in-memory-based caching systems such as Redis ETC. Furthermore, these systems don't allow for vector-based query operations such as nearest neighbor search. Consequently, engineers have to deploy additional approximate nearest neighbor search systems such as Facebook's FAISS or Spotify's ANNOY. These systems, while nifty and fast, are difficult to install and are costly to maintain. To address these issues, I built NNext, a managed vector datastore in which vectors are first class citizens. NNext, allows you to store vectors along with any json-blob metadata. Furthermore, NNext comes with a fast approximate nearest-neighbor (ANN) search capability. I would love to get feedback on your experience as Data Scientist or ML engineer storing feature vectors and ANN systems. Please shoot me an email at [redacted].

Does the same job

all alternatives →

More ai this month

the category →
  • I trained a 125M model to autocomplete piano on-device▲598

    I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.

    AI · 17d ago · simedw.com

  • Astute▲585

    Automate your B2B brand going viral, with new media creators

    AI · 18d ago · company-app.joinastute.com

  • Grok Bot▲547

    AI teammates that you can give real work to

    AI · 25d ago · x.ai

  • Needle2: 14MB agentic LLM for phones, wearables, smart home and robots▲537

    Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…

    AI · 26d ago · cactuscompute.com

  • Coldtea.ai▲512

    Make your software self-driving

    AI · 30d ago · coldtea.ai

  • Soloop▲472

    Approval-first Agent OS for solo founders

    AI · 30d ago · soloop.io

Launched alongside, March 2021

the whole month →