#255 Zhamak's Corner 28 - Generative AI and Data Mesh: The Start of a Long Road

Takeaways:This is just scratching the surface of generative AI and data mesh - we will have much deeper discussions in future episodes.Zhamak believes generative AI has a ton of positive real world potential, especially in data mesh. Scott is more skeptical. But if things like GenAI are only able to be leveraged by a few large companies trying to collect as much information - especially sensitive information - as possible, there are some big potential societal issues that might come from that. We need to democratize the ability to leverage these types of tools.ChatGPT set off a frenzy. It can be easy to want to move incredibly fast towards implementing generative AI. But companies don't have the vast amount of data where they can throw moderate - or worse - quality data and get something useful out. Garbage in, garbage out is a real concern.Because they have less data than essentially the sum of the internet like OpenAI used for ChatGPT, companies need to focus on providing quality data into an LLM (large language model) in order for it to actually provide good results. Again, otherwise it is garbage in, garbage out.Sponsored by NextData, Zhamak's company that is helping ease data product creation.For more great content from Zhamak, check out her book on data mesh, a book she collaborated on, her LinkedIn, and her Twitter. Sign up for Data Mesh Understanding's free roundtable and introduction programs here: https://landing.datameshunderstanding.com/Please Rate and Review us on your podcast app of choice!If you want to be a guest or give feedback (suggestions for topics, comments, etc.), please see hereData Mesh Radio episode list and links to all available episode transcripts here.Provided as a free resource by Data Mesh Understanding / Scott Hirleman. Get in touch with Scott on LinkedIn if you want to chat data mesh.If you want to learn more and/or join the Data Mesh Learning Community, see here: https://datameshlearning.com/community/All music used this episode was found on PixaBay and was created by (including slight edits by Scott Hirleman): Lesfm, MondayHopes, SergeQuadrado, ItsWatR, Lexin_Music,...

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Interviews with data mesh practitioners, deep dives/how-tos, anti-patterns, panels, chats (not debates) with skeptics, "mesh musings", and so much more. Host Scott Hirleman (founder of the Data Mesh Learning Community) shares his learnings - and those of the broader data community - from over a year of deep diving into data mesh. Each episode contains a BLUF - bottom line, up front - so you can quickly absorb a few key takeaways and also decide if an episode will be useful to you - nothing worse than listening for 20+ minutes before figuring out if a podcast episode is going to be interesting and/or incremental ;) Hoping to provide quality transcripts in the future - if you want to help, please reach out! Data Mesh Radio is also looking for guests to share their experience with data mesh! Even if that experience is 'I am confused, let's chat about' some specific topic. Yes, that could be you! You can check out our guest and feedback FAQ, including how to submit your name to be a guest and how to submit feedback - including anonymously if you want - here: https://docs.google.com/document/d/1dDdb1mEhmcYqx3xYAvPuM1FZMuGiCszyY9x8X250KuQ/edit?usp=sharing Data Mesh Radio is committed to diversity and inclusion. This includes in our guests and guest hosts. If you are part of a minoritized group, please see this as an open invitation to being a guest, so please hit the link above. If you are looking for additional useful information on data mesh, we recommend the community resources from Data Mesh Learning. All are vendor independent. https://datameshlearning.com/community/ You should also follow Zhamak Dehghani (founder of the data mesh concept); she posts a lot of great things on LinkedIn and has a wonderful data mesh book through O'Reilly. Plus, she's just a nice person: https://www.linkedin.com/in/zhamak-dehghani/detail/recent-activity/shares/ Data Mesh Radio is provided as a free community resource by DataStax. If you need a database that is easy to scale - read: serverless - but also easy to develop for - many APIs including gRPC, REST, JSON, GraphQL, etc. all of which are OSS under the Stargate project - check out DataStax's AstraDB service :) Built on Apache Cassandra, AstraDB is very performant and oh yeah, is also multi-region/multi-cloud so you can focus on scaling your company, not your database. There's a free forever tier for poking around/home projects and you can also use code DAAP500 for a $500 free credit (apply under payment options): https://www.datastax.com/products/datastax-astra?utm_source=DataMeshRadio