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    Snowflake Engineering Blog

    medium.com/snowflake · Company blog · on HN since 2021

    The Snowflake Engineering Blog is the company's Medium publication on its data platform, AI models, text-to-SQL, Bazel builds and infrastructure.

    Visit blogHN submissions
    DatabasesAI & Machine LearningDevOps & Cloud
    What HN says

    Commenters link it to clarify Snowflake's text-to-SQL results with Mistral and Arctic's mixture-of-experts work, and one skeptically calls a claim no better than GPT-4.

    Stats for nerds
    17HN people shared it
    18linked in comments
    27story points
    Apr 2024last shared
    2023people per year2024

    Top posts on HN

    1. 1
      CrystalCosts: A cost monitoring AI agent for Snowflake
      1 person · 5 points · first shared 2024 · Discussion on HN
    2. 2
      MyDay – From iOS to Native Snowflake App
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      Snowflake Engineering: Blue-Green Upgrades of Istio Control Plane
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    4. 4
      Building Our Gen AI Sales Knowledge Assistant on Snowflake
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    5. 5
      Snowflake Supports Trailing Comma for the Select Clause
      1 person · 2 points · first shared 2024 · Discussion on HN
    6. 6
      Snowflake’s migration to Envoy for traffic management
      1 person · 2 points · first shared 2023 · Discussion on HN
    7. 7
      Snowflake Arctic Cookbook Series: Mixture of Experts (Moe)
      3 people · 1 points · first shared 2024 · Discussion on HN
    8. 8
      Addressing Bazel OOMs
      2 people · 1 points · first shared 2023 · Discussion on HN
    9. 9
      Apache Iceberg enables ACID compliance for data lakes
      1 person · 1 points · first shared 2023 · Discussion on HN
    10. 10
      Snowflake: Building a Data Cloud
      1 person · 1 points · first shared 2024 · Discussion on HN

    What HN people wrote when they linked it

    • jeffra45Apr 2024

      By truly open, we mean our releases use an OSI-recognized license (Apache-2) and we go beyond just model weights. Here are the things that we are open-sourcing:

      i) Open-Sourced Model Weights

      ii) Open-Sourced Fine-Tuning Pipeline. This is essentially the training code if you want to adapt this model to your use cases. This along with an associated cookbook will be released soon, so keep an eye on our repo for updates: https://github.com/Snowflake-Labs/snowflake-arctic/

      iii) Open-Sourced Data Information: We trained on publicly available datasets, and we will share information on what these datasets are, how we processed and filtered them, composition of our datasets etc. They will be published as part of the cookbook series here: https://www.snowflake.com/en/data-cloud/arctic/cookbook/, shortly.

      iv) Open-Sourced Research: We will share all of our findings from our architecture studies, performance analysis etc. Again these will be published as part of the cookbook series. You can already see a few blogs covering MoE Architecture and Training Systems here: https://medium.com/snowflake/snowflake-arctic-cookbook-series-exploring-mixture-of-experts-moe-c7d6b8f14d16, https://medium.com/snowflake/snowflake-arctic-cookbook-series-building-an-efficient-training-system-for-arctic-6658b9bdfcae

      v) Pre-Training System information: We actually used the already open-sourced libraries DeepSpeed and Megatron-DeepSpeed for training optimizations and the model implementation for training…

    • jmmvJul 2023

      Thanks!

      The Bazel posts stopped for a while after I left Google, but I'm now back at a different place where I'm working with Bazel once again. So you can expect the posts on this topic to gradually come back :) (For some context, here is one: https://medium.com/snowflake/addressing-bazel-ooms-38023b736fa2)

      Let's see if my plans to return to Europe in the next few years play out...

      Edit: Oh, and the few posts that look like Twitter threads (they are tagged like that) are hand-crafted and were an experiment. I first wrote the threads as blog posts, ensuring each paragraph fit in a tweet, and then copy/pasted them into Twitter. I wrote them as a blog post because I wanted to have the "unrolled" version in the canonical source for future reference, without relying on those unroll apps.

    • mritchie712Apr 2024

      smoke? it's the same as gpt4

      https://medium.com/snowflake/1-1-3-how-snowflake-and-mistral-push-the-boundary-in-text2sql-169bfa391331#:~:text=When%20we%20combine%20the%20Snowflake%20fine%2Dtuned%20model%20with%20Mistral%20Large%20in%20a%20chained%20setup%2C%20we%20are%20able%20to%20improve%20execution%20accuracy%20by%206%20percentage%20points%20from%20~40%25%20to%20%3E46%25%20in%20our%20internal%20evaluation%20dataset%20%E2%80%94%20outperforming%20GPT%2D4%3A

    • adrien-treuilleApr 2024

      Actually, Snowflake doesn’t use Arctic for SQL codegen internally. They use a different model chained with mistral-large… and they do smoke the competition. https://medium.com/snowflake/1-1-3-how-snowflake-and-mistral-push-the-boundary-in-text2sql-169bfa391331

    • fhoffaJul 2023

      FWIW, I now analyze the Stack Overflow dumps on Snowflake

      https://medium.com/snowflake/how-to-load-the-stack-overflow-xml-dumps-into-snowflake-631c90fff57

    • rajhansApr 2024

      We have published some insights here. https://medium.com/snowflake/snowflake-arctic-cookbook-series-exploring-mixture-of-experts-moe-c7d6b8f14d16

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