It becomes easier to take the progress seriously and understand it when you drop the "intelligence"-style labels which misleads people into thinking something is there that isn't.
Machine "learning" isn't ideal either, but is at least a bit more limited in the scope of what it conveys.
Once you leave the hype baggage behind, it's more easy to see the significant progress that these tools - in concert with increased power and data resources - have made in many different areas over the last few years, some of them listed elsewhere in the answers to your question.
Machine "learning" isn't ideal either, but is at least a bit more limited in the scope of what it conveys.
Once you leave the hype baggage behind, it's more easy to see the significant progress that these tools - in concert with increased power and data resources - have made in many different areas over the last few years, some of them listed elsewhere in the answers to your question.