The impact is going to be the very same way like you have on your iPhone, all the faces being grouped together. It's this new generation of how computers are able to interact with the information that are fed. Every single application as these embedding models are sourced will be able to go in and leverage up. And that's just like the big companies who have had all the access of the hardware to be able to trade neural networks that can generate powerful embeddings.
In this episode, we discuss the impact of AI with Andriy Mulyar, co-founder of AtlasAI and creator of GPT4All. We explore how running local private language models can provide competitive benefits over using public models like ChatGPT without confidential data. Additionally, we delve into the importance of embeddings in AI and their potential impact on understanding data semantically. Finally, Andriy shares his thoughts on crypto/AI overlap, specifically focusing on data provenance as a key area for collaboration.
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Disclosures: This podcast is strictly informational and educational and is not investment advice or a solicitation to buy or sell any tokens or securities or to make any financial decisions. Do not trade or invest in any project, tokens, or securities based upon this podcast episode. The host and members at Delphi Ventures may personally own tokens or art that are mentioned on the podcast. Our current show features paid sponsorships which may be featured at the start, middle, and/or the end of the episode. These sponsorships are for informational purposes only and are not a solicitation to use any product, service or token. Delphi’s transparency page can be viewed here.