DeepMind: A Generalist Agent
(Former AI researcher &#x2F; founder here)<p>It always surprises me at the ease at which people jump on a) imminent AGI and b) human extinction in the face of AGI. Would love for someone to correct me &#x2F; add information here to the contrary. Generalist here just refers to a &quot;multi-faceted agent&quot; vs &quot;General&quot; like AGI.<p>For a) - I see 2 main blockers,<p>1) A way to build second&#x2F;third order reasoning systems that rely on intuitions that haven&#x27;t already been fed into the training sets. The sheer amount of inputs a human baby sees and processes and knows how to apply at the right time is an unsolved problem. We don&#x27;t have any ways to do this.<p>2) Deterministic reasoning towards outcomes. Most statistical models rely on &quot;predicting&quot; outputs, but I&#x27;ve seen very little work where the &quot;end state&quot; is coded into a model. Eg: a chatbot knowing that the right answer is &quot;ordering a part from amazon&quot; and guiding users towards it, and knowing how well its progressing to generate relevant outputs.<p>For (b) -- I doubt human extinction happens in any way that we can predict or guard against.<p>In my mind, it happens when autonomous systems optimizing reward functions to &quot;stay alive&quot; (by ordering fuel, making payments, investments etc) fail because of problems described above in (a) -- the inability to have deterministic rules baked into them to avoid global fail states in order to achieve local success states. (Eg, autonomous power plant increases output to solve for energy needs -&gt; autonomous dam messes up something structural -&gt; cascade effect into large swathes of arable land and homes destroyed).<p>Edit: These rules <i>can&#x27;t possibly all be encoded</i> by humans - they have to be learned through evaluation of the world. And we have not only no way to parse this data at a global scale, but also develop systems that can stick to a guardrail.