That's a longstanding debate, but yes, a common view is that there's more of an algorithm/formalization bottleneck than a hardware-speed bottleneck. There are some things we in principle know how to do in AI, but just can't practically do fast enough--- those will be fixed by speed increases. But there are a lot of things where we don't even know how, in principle, to write down an algorithm to approach the problem satisfactorily. Hence the notion of "AI-completeness" rather than "NP-completeness" as a colloquial expression for what makes an AI problem hard.