I am of a similar opinion. There was a real revolution in ~2011-2013 with deep learning. These have achieved much better results in image/speech tasks. These gains have leveled off, and we're seeing some limitations.
At current trajectory, we're not headed towards a general intelligence. Progress has been made, but there are big gaps. Smart home devices are a great case in point. They are somewhat flexible in the voice commands they accept. Specific phrasing and pronunciation are not necessarily required. Their responses and speech, however, are all pre-programmed and templated by humans.
Edit: There is potential for more breakthroughs in the future, but I am not seeing them on the horizon at the moment.
AFAIK, these are all implementations of deep learning or similar, not a fundamentally new architecture. We'll continue to see these as DL matures, but it doesn't address the shortcomings of the technique.
At current trajectory, we're not headed towards a general intelligence. Progress has been made, but there are big gaps. Smart home devices are a great case in point. They are somewhat flexible in the voice commands they accept. Specific phrasing and pronunciation are not necessarily required. Their responses and speech, however, are all pre-programmed and templated by humans.
Edit: There is potential for more breakthroughs in the future, but I am not seeing them on the horizon at the moment.