In my opinion that is a very good answer not only from philosophical point of view but rather from a mathematical vantage point. Well i think cognitive scientist understand how far we are from a human like machines. However Tech communities sticked to the term intelligence because it is just fancy and because it sounds very nice when you want to promote your research or your product. Like what in the world makes a human driving a car Intelligent whereas a machine is indeed considered such as. There are a lot of fundamentals difference between human brain and machinery "Intelligence". At the end machine learning and AI is constrained and tethered whithin the realem of mathematical framework and you can't bypass it. Which it turns out that we don't even understand the mathematics of these models. For instance we don't know what class of function neural network can approximate, (well we know that we can approximate any continuous function in theory and this is a very broad statement theorem), what kind of regularities the function should have, how these models are exploting the symmetries of the problems, what are the principles or strategies the model is pursuing to solve the task, lets say we had a deep understanding of these topics can we than solve the problem without learning etc.. so i guess our lack for the mathematical understanding of these models is the real obstacle. Understanding intelligence and cognition is important if you want to do human like machine but nowdays i don't think we have such, we rather have a human task imitating machines.