For the last four months we have been experimenting a lot with LLM models in an attempt to simplify the creation of reasoning chains without using an auxiliary programming language. The idea comes from the control unit in classical processors. We see LLM as a more complex ALU, but the models lack a unit that can perform more complex sequences of prompts, including loops. In psychoanalysis there is a concept of the central executive system, which is somewhat similar to the control unit in CPUs.
> The central executive is responsible for controlled processing in working memory, including but not limited to, directing attention, maintaining task goals, decision making, and memory retrieval.
The low cost of the Raspberry Pi has disrupted many facets of general computing, but that also extends to cluster computing. Using a series of Raspberry Pi Model B boards is possible, but with the new range of Raspberry Pi Compute Modules, we can build clusters that offer the same or greater computational power while consuming less space. The Turing Pi 1 [1] from Turing Machines used seven Compute Module 3+, but with the announcement of the Raspberry Pi Compute Module 4, the company has announced [2] Turing Pi 2, which will support up to four Compute Module 4 boards.
That's one of the point too. We have industrial customers who deploy apps in the places with a limited access to the internet, so increased reliability something important to them. Another thing is that they can host apps with different purposes on different nodes in containers. Besides that all the infrastructure could be managed with a tool like Kubernetes and organically work with existing cloud infrastructure. And the last but not least in a cluster like that you can combine general purpose modules with accelerated compute modules.