There are two parts to this. First one is about parsing the speech, and we&#x27;re getting pretty good at that. The second part is actually understanding the context of the speech and that&#x27;s obviously harder problem.<p>We&#x27;re just starting to explore machine learning in any meaningful sense. I think the progress we&#x27;ve seen already bodes tremendously well for AI assistants.<p>&gt;The primary bottleneck for intelligent agents is not voice recognition, it&#x27;s semantic insight.<p>I absolutely agree. We won&#x27;t see general purpose assistants in the near future, but that doesn&#x27;t mean we won&#x27;t see specialized assistants. Something like the desktop is a fairly constrained environment.<p>A lot of what you&#x27;d need to do is already being done by systems like Google search. You can type in a random term and it will often do an excellent job of finding exactly what you wanted.<p>Here&#x27;s an example of just how good this tech is now. I forgot a name of a tv show one time and I typed in &quot;movie with a clock and the key&quot; into Google. Sure enough it found the show as the first result.<p>While we don&#x27;t know how to make a general purpose AI right now, but there is a ton of work happening in that domain. I would be very surprised if we don&#x27;t see a lot of progress there in the next few decades.<p>The AI doesn&#x27;t have to be self improving, our brains aren&#x27;t and we can do all the things that a digital assistant would need to do.