Nicolay Gerold

With a Two Tower Model, you generate embedding vectors for the user and for all the content you need to retrieve/rank. An embedding vector is just a compact representation that captures the attributes and relationships of an item in a machine-learning-friendly vector.

Once you have these embedding vectors, you can look at the similarity between a... See more

Navigating the terrain of vector databases in 2023 reveals a diverse array of options each catering to different needs. The comparison table paints a clear picture, but here's a succinct summary to aid your decision:

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• ClickHouse: It's a high performance columnar database that's great for real time queries. It enables querying and storing large amounts of data on commodity hardware. Some of my customers have millions of page views and I don't have an unlimited budget, so it's been very handy.


• PostgreSQL: My favorite database. Sane defaults, battle-tested, and well

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All the recommendation systems you see at Twitter, Facebook, TikTok, YouTube, etc. have a similar high-level architecture.

They have a layered architecture that looks something like the following

1. Retrieval - Narrow down the candidates of what to show a user to thousands of potential items


2. First Stage Ranking - Apply a low-level ranking system to

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HelixNet is a Deep Learning architecture consisting of 3 x Mistral-7B LLMs. It has an actor, a critic, and a regenerator. The actor LLM produces an initial response to a given system-context and a question. The critic then takes in as input, a tuple of (system-context, question, response) and provides a critique based on the provided answer to the... See more

koboldcpp

🤗 Transformers

Huggingface is an open source platform and community for deep learning models for language, vision, audio and multimodal. They develop and maintain the transformers library, which simplifies the process of downloading and training state of the art deep learning models.

This is the best library if you have a background in... See more

Build & Deployments

Our build process starts by pushing changes to a repository on GitHub. When code is pushed to a repository through a pull request, it triggers a job to build the changes made to the branch and deploy them in isolation. This worklow happens interactively within the pull request, where the author has visibility of all steps.

Some... See more

Prioritize work to minimize opportunity cost. This prevents you from only pursuing incremental futures. In each quarter how much time to allocate incremental ~ 60%, to big new initiatives ~30%, to guidance & infrastructure ~10%.