[P] My co-founder and I quit our engineering jobs at AWS to build “Tensor Search”. Here is why.

This page summarizes the projects mentioned and recommended in the original post on reddit.com/r/MachineLearning

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  • marqo

    Tensor search for humans.

    My co-founder and I, an AWS SDE and senior Amazon research scientist respectively, launched Marqo a little over a week ago - a "tensor search" engine https://github.com/marqo-ai/marqo

  • Scout APM

    Truly a developer’s best friend. Scout APM is great for developers who want to find and fix performance issues in their applications. With Scout, we'll take care of the bugs so you can focus on building great things 🚀.

  • proposals

    Temporal proposals (by temporalio)

    Emit events from your primary DB (postgres, etc.) to something like kafka or rabbitmq and then catch that in your search engine. There's also some end-to-end solutions like temporal (temporal.io) or cadence (https://cadenceworkflow.io/)

  • cadence

    Cadence is a distributed, scalable, durable, and highly available orchestration engine to execute asynchronous long-running business logic in a scalable and resilient way.

    Emit events from your primary DB (postgres, etc.) to something like kafka or rabbitmq and then catch that in your search engine. There's also some end-to-end solutions like temporal (temporal.io) or cadence (https://cadenceworkflow.io/)

  • towhee

    Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.

    Milvus also has incredible flexibility when it comes to choosing an indexing strategy, and we also have a library specifically meant to help vectorize a variety of data called Towhee (https://github.com/towhee-io/towhee).

  • Zigi

    The context switching struggle is real. Zigi makes context switching a thing of the past. It monitors Jira and GitHub updates, pings you when PRs need approval and lets you take fast actions - all directly from Slack!

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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