'Building a new blockchain comes with numerous challenges, but the rapid evolution of L2 runtimes ...makes the possibility of a generative AI blockchain much more achievable than in previous years.' Opinion jrdothoughts intotheblock
Generative artificial intelligence has quickly become one of the hottest and arguably the most transformational technology trends of the last few decades. The impact of generative AI is evident in all areas of the technology stack, ranging from infrastructure to applications.
Until a few months ago, the gap between API-based and open-source foundation models was significant. Models such as OpenAI's GPT-4, Anthropic's Claude in the language space, DALL-E, and Midjourney in the computer vision space, seemed significantly advanced compared to open-source alternatives. However, a change started to occur late last year with the surprising open-source release of Stable Diffusion, which provided a viable alternative to API-based text-to-image models.
In the first scenario, we are likely to witness tools like exchanges, explorers, or wallets incorporating conversational capabilities powered by large language models. Additionally, a new generation of DApps will be built with generative models as their cornerstone. In this scenario, Web3 primarily acts as a consumer of generative AI capabilities, with models running on traditional Web2 cloud infrastructures.
The answer lies in the architectural mismatch between the requirements to run foundation models and blockchain runtimes. A typical pre-trained foundation model consists of millions of neurons spread across tens of thousands of interconnected layers, executing on clusters of GPUs or specialized deep learning hardware topologies. No smart contract in the history of Web3 even comes close to that level of complexity. Thus, it is logical to conclude that a new type of architecture is needed.
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