The cycle keeps repeating. A new advancement in computing power, networking, or algorithms means there's a new batch of low-hanging fruit for AI to pick, so we pick it. Investors say "What about the high-hanging fruit?" and we say "No problem. We just need a slightly longer ladder."
Two years later everybody finally realizes the high-hanging fruit is on the moon.
There's a recent NLP model that was trained on a trillion words. It would take us 10,000 years to read or listen (no breaks, no sleep) to that many words. Problems like attention, and the relation between memory and sequential thinking haven't been cleared up at all. Even semantics, i.e. basic understanding of a utterance or a scene, is in its infancy.
Large neural nets can help with interesting problems, but it's not going to mimic our style of thinking any time soon.
No algorithm running on digital hardware can emulate the biological process of animal intelligence.