The following AI research report from Messari highlights the fact that decentralized AI compute platforms that focus on simply the number of GPU nodes in the networks is an unsustainable approach (supply-first). Growing and building AI applications that are use case-driven catered for the AI user (demand-first) is the ideal way to develop a decentralized AI compute network.

Original Source (Excerpt Included Below):
https://messari.io/report/are-gpu-compute-networks-supply-or-demand-constrained

This precisely aligns with the structure and design of Phoenixā€™s AI Application Ecosystem and SkyNet AI elastic compute infrastructure, which focuses on value-delivery through various vertical AI applications to grow the network. From Phoenixā€™s native apps such as AlphaNet (trading), PhoenixLLM (knowledge), or GenAI (content), to ecosystem app partners such as Horizon Protocol (AI DEX) and W3Goo (AI Search), delivering readily accessible use-case value for end users is the core tenet of our platform.

š—§š—µš—² š—£š—µš—¼š—²š—»š—¶š˜… š—§š—暝—¶š—³š—²š—°š˜š—®, our approach for AI value-creation, consists of 3 pillars: AI Alpha (market insights, trading), AI Insights (predictive analytics, enterprise apps, AI search), and AI Productivity (LLM, AIGC, automation).