Web3 infrastructures need to grow The current generation of blockchain runtimes has not been designed to run large foundation models, even for inference use cases. To address that challenge, new blockchain runtimes optimized for larger and more complex compute workloads are definitely needed. Off-chain inference computation is a nice middle ground, but one that doesn't fully address the centralization concerns with generative AI. Foundation models need to become smaller

5/8 4/19/24, 5:53 PM Last year, Microsoft coined the term "small language models" based on its work on a foundation model called Phi and the iconic paper "Textbooks is All You Need". The small Phi was only 3B parameters and was pre-trained on a series of computer science textbooks, and it was able to outperform 70B models in math and computer science tasks. The work on Phi signaled that smaller and more specialized models are one of the most important steps towards the adoption of generative AI. In the same way that Web3 infrastructures need to scale to adopt foundation models, the SLM trend can make models more practical to run on Web3 infrastructure. It is unlikely we will see a Web3 infrastructure running a trillion parameter model in the near future, but 2B3B is definitely possible. STORY CONTINUES BELOW Recommended for you:

Kraken Is Buying TradeStation Crypto, Expanding Cryptocurrency Exchange's U.S. Reach e Mango Markets Exploiter Avi Eisenberg Found Guilty of Fraud and Manipulation Crypto for Advisors: Bitcoins Supply Reduction Difficult but possible path to decentralized AI The idea of decentralized generative AI is conceptually trivial but practically very difficult. AI naturally evolves as an increasingly centralized technology, and any decentralization efforts are an uphill battle. The mainstream adoption of open source generative AI models is essential for the viability of decentralized AI infrastructures. Similarly, the current state of generative AI suggests that most of the initial use cases of decentralized AI will focus on inference rather than pretraining or fine-tuning. Finally, to make decentralized AI practical, Web3 infrastructures need to scale on several orders of magnitude, while foundation models need to become smaller and more adaptable to decentralized environments.

The Enablers of Decentralized Al 6/8 4/19/24, 5:53 PM The Enablers of Decentralized Al That combination of factors represents the best path towards decentralized generative AI. That path will be extremely difficult but, at least for now, certainly possible. Edited by Benjamin Schiller. Newsletter > Every Weekday The Node Sign up for The Node, our daily newsletter bringing you the biggest crypto news and ideas.