Jeff Bezos on AI (1998) [video]
The common sentiment around AI in the 90s and early 2000s was that it didn&#x27;t work; it had its hype, it had its heyday, but it seemed like a dead-end for the most part. The Perceptron was merely a linear function approximator. And the Multi-layer Perceptron was a little more capable, but the many orders of magnitude it would have to scale up in order to be convincing just wasn&#x27;t feasible back then (it finally was in the 2010s).<p>Simple statistical models that aren&#x27;t &quot;AI&quot; so much as just generic ML were and are quite useful: like recommendation and newsfeed engines (&quot;the Algorithm&quot; as we call it so often today). Love &#x27;em or hate &#x27;em, they can be quite good at predicting interest&#x2F;engagement.<p>The resurgence in deep learning in the 2010s has shown us new magic tricks, but they&#x27;re still just that: parlor tricks. At least they&#x27;re more convincing tricks than what we had 40 years ago!<p>That&#x27;s what ultimately depresses me about AI. It&#x27;s still just a parlor trick. We haven&#x27;t actually taught computers to think, to reason, to be innovative. Deep learning is definitely having its day, but I suppose this too will pass unless we can unlock certain ways to make AI reliable and responsible. Or... to just start understanding it in general.