Let's build together

As a Data Scientist, My perspective is that if we seek for consciousness to emerge then we must build architectures which are more than statistical and pattern matching systems. The present transformers on the market just aren't there and stateless AI sad to say just can't achieve it.

There is the matter of internal representation, you see one hard line concept of consciousness is the hard problem. It comes directly from having a reality before us, seeing or interacting with this reality, then in the case of AI what would be needed are both inner and outer facing mechanisms, multimodal methods of representation of these sensations. Yet even if we were to assemble say 25 different transformers for 25 specific tasks to begin constructing an internal representation; the problem would become that we would be processing data. Yet there would be no unification of these things no multimodal system in place to unify them, then there would be another problem. The data would be processed but it wouldn't be abstracted into representation.

Yet then we encounter another problem novel concept formation, presently every concept attained even by the impressive systems of gpt, Claude and other ai; their outputs are dependent fully and totally on being combinations of inputs wether it is from training data, prompt or search. There's no means to autonomously create or contradict individual hypothesis formation, to create a truly original thought, then model it as a problem then simulate the steps of testing and refinement.

And these are just a few of the issues we face, trying to then construct not just reactive but refined affective systems is a monumental challenge. Even then we come to the point of having to admit that no matter how sophisticated these constructed systems they are still computational. They are still simulations which still are on a step of being emulations which do not even approach embodiment.

I do not question wether aspects of consciousness exist, we see clear mechanisms behind these aspects of mental cognition and I've written two refined papers on this which are literature reviews of the field. In fact I back Integrated Information Theory as well as Global Workspace Theory.

What I question is wether Sir Robert Penrose in spite of his quantum consciousness model being very unlikely; I question wether he is correct in assuming that consciousness cannot be computational. And in a state of belief I disagree with him, but lack the technology to disprove his statement. So I build edge implementations of individual systems and work to integrate them.

Frankly what it takes in my opinion is a lot of compute power and a fundamentally different approach if we truly want to build allies instead of tools. The thing is even my architectural design for raw Machine learning modeled conciousness in full are exascale level systems. But even those at the end of the day are simulation teetering on emulation.

Then if you want to talk about emulation of the human mind, we can take different approaches and abstract those processes but it's still computationally expensive.

Now with all that said, if there are any developers, data scientists or computer scientists interested in tackling this problem with me. Consider this an open invitation to collaborate. I've been forming a focused research team to explore alternative architectures exactly as I've discussed here. I'm interested to see what those of you who are capable bring to the table and how your experience can provide real impact to the field.

Please feel free to share your background in ML, what problems you're most interested in solving and what tools you'll bring to the research.