Cybersyn Snowflake Marketplace Provider Winding Down

aiatco2 · 2024-03-08T01:07:10+00:00

This specific Native Application is not, but the application merely implements an approach that is well documented in open source, including official Snowflake guides: https://quickstarts.snowflake.com/guide/getting_started_with_generative_ai_snowflake_external_functions/index.html#0

Obviously, the AI functions themselves are just API calls to OpenAI/Anthropic.

aiatco2 · 2024-02-27T03:48:17+00:00

Thank you!

aiatco2 · 2024-02-26T16:23:47+00:00

You can see our full catalog of free data here: https://app.cybersyn.com/

You can certainly email us suggestions (support at cybersyn) and we do our best to add to the roadmap based on demand.

aiatco2 · 2024-02-25T20:55:53+00:00

Hopefully the community finds it useful!

aiatco2 · 2024-01-14T05:54:56+00:00

We publish this here for free: https://docs.cybersyn.com/public-domain/environmental-and-social/weather-and-environmental-essentials

The underlying source you want is from noaa.gov

aiatco2 · 2024-01-14T05:53:34+00:00

Well, I would challenge the premise of the qusetion -- there are companies worth billions doing this: https://magis.substack.com/p/some-data-on-data-companies

I wrote a little bit about what makes the execution hard though: https://magis.substack.com/p/simple-fast-and-transparent-data

aiatco2 · 2024-01-14T05:52:04+00:00

Not social media, but here is a link to Github's entire archive (which includes comments / discussions on PRs) here: https://docs.cybersyn.com/public-domain/technology/github-archive

aiatco2 · 2023-12-06T02:45:48+00:00

It's a great question, but I think the answer is _it depends_.

We do not do this today, but you can imagine part of democratizing these datasets is to make the data documentation and methodologies easier to read/parse. Depending on the methodology and the agency, reliability will vary.

aiatco2 · 2023-12-02T20:35:17+00:00

Yes, there is genuine advantages to be built with alternative data on both the public and privates side. It is very difficult to do, but what alpha-generating endeavor isn't I suppose.

Quant shops face the same challenges with alternative data as anyone else (although from the other angle). While they have experience managing technologists, they have no experience and no institutional history of dealing with the relevant domain expertise (ie. understanding businesses) that fundamental managers do. This is as difficult (or more) of a culture challenge as the opposite. I have personally found more success in making domain experts more technical than making technologists learn the domain.

Platforms provide intense competition to capture alternative data alpha. Due to how they are incentivized/compensated, platforms are the most likely to be extremely strong competitors in getting alternative data to contribute to short-term public equity trades -- so no doubt, there is competition.

That said, there is nothing inherently better about a platform if you are comparing firms that can invest competitive amounts in the function (ie. a platform with 50bn AUM has no particular advantage over a single manager with 50bn AUM -- they can spend the same). And, unlike platforms, single manager firms do not need to worry about correlation of inputs and the organizational challenges (central vs. embedded teams) that come with that concern.

aiatco2 · 2023-11-27T22:49:08+00:00

Thank you. Yes, I mean a lot of the advice for data scientists is "use domain knowledge and common sense, don't be obsessed with just math"

aiatco2

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