[smoussa]

I think it’s important to understand what our objective is.

Reading these comments comparing birds and aeroplanes is nonsense since they both have very different flight behaviours and objectives. Birds’ wings flap for agility to avoid predators. They have brains which is half reflex and allows them to regulate their bodies. Planes don’t have predators and don’t need cognition.

If our objective is to solve a business problem, machine learning is great for specific tasks and can achieve superhuman results in some cases. We don’t need much neuroscience here.

But if our objective is AGI, it gets interesting because it is very far from current machine learning / deep learning / reinforcement learning. It’s hard to put a definition on AGI at all. What do we want to achieve? To replicate the human brain, of course we need neuroscience. To replicate intelligence without designing the components for bodily function will need an approach which looks at brain circuitry and function but is implemented with a good level of abstraction.

I believe we know a lot more about the brain than the public thinks. Read Cell Neuron and Nature Neuroscience journals and clinical encyclopaedias to get an understanding. I don’t think we should be replicating things on the neuron level but at a more abstract level of neuronal dynamics, neuronal populations and networks with a focus on understanding the developmental biology of the first few years of human life where learning really happens.