Ainolabs’ search for Holy Grail is to build sufficiently advanced system to can replace an experienced professional. That Holy Grail is challenging for several reasons, but mostly because the way to do that would be to collect an immense amount of multi-channel data about professional environment and then to process that into a single, all-encompassing model.
The difficulty stems not only from the volume of data, but also the nature of it. A professional acts in a multi-sensory environment – 5 human senses, touch, sight, hearing, smell and taste. In working environment sight and hearing are dominant. In addition to these a professional working in an organization needs to be attuned to the social environment – who said what, when. These combined explain why it might take an infant 20+ years to become proficient in e.g. Business Strategy Consulting.
Considering a simpler task: Could a Barista Robot be built out of components?
A Barista Robot would need to interface with customers. A good over the counter customer service representative notices clients as they come in, keeps track of their order so that they’ll all be served in time, notices their demeanor and addresses each customer in an appropriately courteous and polite manner.
A Barista Robot needs also to brew coffee and possibly recommend suitable combinations.
There are great chatbot-style customer service machines. There are also robot arms that can brew coffee. The question is – how to combine the two so that the system Robot Barista would fluently serve incoming clients?
A modular architecture was proposed in The Medium in 2023 – see https://medium.com/@amir.ghm/breaking-the-llms-16k-token-limit-introducing-the-modular-ai-systems-architecture-5a23b37139ac
That might do the trick if it was somehow possible to define the interfaces between parts somehow similar as to APIs are defined as swagger files or Docker components’ dependencies are listed in the manifest.
That however is really puzzling, in biological terms equivalent to surgically attach great barista hands to a well-spoken customer service representative. Besides unethical, that wouldn’t work since a barista’s hand needs to be connected with a barista’s nervous system.
In digital terms – how would one connect a great customer service agent LLM with a great Coffee Making Barista model to a Barista robot arm?
I don’t know, I wish someone did.
Modular AI systems 