How to Use AI to Do Stuff: An Opinionated Guide

This page summarizes the projects mentioned and recommended in the original post on news.ycombinator.com

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  • datadm

    DataDM is your private data assistant. Slide into your data's DMs

  • Pretty good examples and simple explanations. I didn't realize Claude 2 was so good at working with PDFs natively. I wonder if they're doing anything special? Is this just due to larger context length they have?

    Also, biased opinion on my part: I'm especially interested in watching how these things affect data science and data literacy as a whole. Code interpreter is a game changer in my opinion, the most powerful tool that somehow isn't getting as much press I think it deserves. I released an open source code-interpreter for data (https://github.com/approximatelabs/datadm) and even though I know how to code and use Jupyter daily, I still find myself doing analysis with it instead.

    All in all, it does seem like the different models and agents are gaining "specialization" skill is actually good for the user (rather than just using a single jack of all trades super chat model). Even though GPT-4 takes the language model crown, there's still specialization that matters and improves quality for different tasks as discussed here.

    I wonder if in 2-5 years we'll all use "a single" AI chat interface for everything, or every specialization continues to "win at its own vertical" and we just have AI embedded inside of every app

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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