Decentralizing AI: Cheaper, Better Inference with Open-Source Models and Subquery?

Our first in-person interview! In this episode, we sat down with
James, COO of Subquery, to dive into their latest project
expansion — decentralized AI inference. We discussed the
significance of offering alternatives to centralized cloud
providers for running AI models and explored how Subquery is
cutting through the hype in the AI and crypto space.


James shared insights into how their decentralized network allows
developers to host AI models in a more open, affordable, and
high-performance way, highlighting the potential for Web3 to
disrupt the AI landscape. 


They are launching an update aimed at enhancing the hosting and
inference capabilities of Artificial Intelligence (AI) models,
with a particular focus on large language models (LLMs). This
upgrade uses a community-driven approach to bring about a more
accessible, cost-effective, and flexible AI ecosystem.


How do you feel about Decentralized AI?


Please share this if you learned something! What should
we discuss next? Comment! 


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Timestamps:


00:00 - Teaser


02:22 - What is Subquery?


04:33 - Why Decentralize RPCs


08:30 - How It Works


13:00 - Decentralized AI Inference


16:03 - AI Models & GPUs


17:50 - Intelligent Apps


20:10 - Crypto & AI HYPE


23:25 - Progress On Open Source AI


28:17 - Subquery Roadmap


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Links / Additional Material:


Subquery Website: https://subquery.network/home


Subquery on X: https://x.com/subquerynetwork


James on X: https://x.com/JamesABayly


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