Should be updated to read "Generalist (across the data we've given it)" Given the grapes example, can it learn what a new fruit is? I doubt it. Still impressive (and they achieved the goals set out in the paper), but in the context of AGI, the 'learning' component still has a ways to go. I think they should shift focus on how they can improve the debugging situation when it comes to ML models before they can start building practical/money-generating use-cases out of this. They also seem to be really focused on "do-thing" AIs in their recent papers, as opposed to "about-thing" - reasoning. I want to see more focus on goal-settings, dynamic desires, and learning how to satisfy those desires using built up knowledge. Would also like it if they can start including more practical metrics, such as "our AI took only 3 tries to figure out drinking unsalted water quenched its thirst, which it just discovered. That would be really spectacular, and I think they're close.
On Tue, May 17, 2022 at 7:14 PM <[email protected]> wrote: > Here's another one, seems different: > https://www.deepmind.com/publications/a-generalist-agent > *Artificial General Intelligence List <https://agi.topicbox.com/latest>* > / AGI / see discussions <https://agi.topicbox.com/groups/agi> + > participants <https://agi.topicbox.com/groups/agi/members> + > delivery options <https://agi.topicbox.com/groups/agi/subscription> > Permalink > <https://agi.topicbox.com/groups/agi/T153394f89409ceb1-M877644ad961f5b50e508462d> > ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/T153394f89409ceb1-Mee35e4b6ea84a493a8d66202 Delivery options: https://agi.topicbox.com/groups/agi/subscription
