With chat gpt as a model, I definitely think weโ€™ll have really solid AI assistants in a decade. Siri and Alexa but with greatly expanded use cases. But these are essentially just language models: understanding some inputs, searching for info, and then giving it back in an understandable format.

But I donโ€™t see what you described for farming, for example. Thatโ€™s essentially an engineering/optimization problem. Same for logistics. Capturing the right data is the hard part. Once you have those, weโ€™re already able to find the optimal solution

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I canโ€™t go too into detail on how it works since itโ€™s part of my work but itโ€™s essentially self optimizing and regulating itself, shared data is a big part of it. I agree that capturing it is the hard part but distribution and implementation of it with the use of Ai is what I was talking about, no need for humans to find the optimal solution, thatโ€™s the computers task.

Very cool. You got a link to any papers or blog posts where I can read more about that application?

Need systems that can do logical reasoning and planning with gaurauntees, otherwise you wonโ€™t really be able to count on the assistant to take care of things you actually care about.

Thereโ€™s work in inductive logic programming (ML on symbolic data) and neuro symbolic approaches that are very interesting. I think weโ€™ll see new classes of systems in the next 5 years or so that combine much of the reliable decision making work thatโ€™s been going on since the beginning of AI with NN learning progress from the last decade