The DALL-E-2 models are very interesting and provide a different path to computer creativity and understanding. But I believe all of these "deep learning" approaches will ultimately fail in that they will not lead to AGI. Why? Essentially without a body that interact with a world through its 5 senses these models will not be able to develop commonsense and thus develop intelligence, as intelligence requires understanding of the world. Melanie Mitchell, Sante Fe Institute scientist, gives the following example to illustrate this: ‘‘Consider what it means to understand ‘The sports car passed the mail truck because it was going slower.’ You need to know what sports cars and mail trucks are, that cars can ‘pass’ one another and, at an even more basic level, that vehicles are objects that exist and interact in the world, driven by humans with their own agendas.’’ Now true believers, on the other hand, argue that given enough data, a purely statistical approach (i.e., large language models) can develop a common-sense understanding of the world. As you state, AGI is always just 10 years away. Gary Marcus, professor emeritus of NYU, has argued for ‘‘a coordinated, multidisciplinary, multinational effort’’ modeled after the European high-energy physics lab CERN, which has successfully developed billion-dollar science projects like the Large Hadron Collider. ‘‘Without such coordinated global action," Marcus "thinks that A.I. may be destined to remain narrow, disjoint and superficial; with it, A.I. might finally fulfill its promise."
Broad agreement here. Embodiment is (probably) a crucial component of true, in-the-world common sense and context-sensitive intelligence. It's been long ignored by the mainstrea AI current, though here and there I see people trying to bring it into the fold - Marcus, for one, indeed. One thing I'm breaking my head over at the moment is the extent to which this embodiment can be emulated in virtual agents exploring virtual environments, which brigns me back to the games idea. More soon, I'm sure ;).
The DALL-E-2 models are very interesting and provide a different path to computer creativity and understanding. But I believe all of these "deep learning" approaches will ultimately fail in that they will not lead to AGI. Why? Essentially without a body that interact with a world through its 5 senses these models will not be able to develop commonsense and thus develop intelligence, as intelligence requires understanding of the world. Melanie Mitchell, Sante Fe Institute scientist, gives the following example to illustrate this: ‘‘Consider what it means to understand ‘The sports car passed the mail truck because it was going slower.’ You need to know what sports cars and mail trucks are, that cars can ‘pass’ one another and, at an even more basic level, that vehicles are objects that exist and interact in the world, driven by humans with their own agendas.’’ Now true believers, on the other hand, argue that given enough data, a purely statistical approach (i.e., large language models) can develop a common-sense understanding of the world. As you state, AGI is always just 10 years away. Gary Marcus, professor emeritus of NYU, has argued for ‘‘a coordinated, multidisciplinary, multinational effort’’ modeled after the European high-energy physics lab CERN, which has successfully developed billion-dollar science projects like the Large Hadron Collider. ‘‘Without such coordinated global action," Marcus "thinks that A.I. may be destined to remain narrow, disjoint and superficial; with it, A.I. might finally fulfill its promise."
Thanks for the great comment, Larry!
Broad agreement here. Embodiment is (probably) a crucial component of true, in-the-world common sense and context-sensitive intelligence. It's been long ignored by the mainstrea AI current, though here and there I see people trying to bring it into the fold - Marcus, for one, indeed. One thing I'm breaking my head over at the moment is the extent to which this embodiment can be emulated in virtual agents exploring virtual environments, which brigns me back to the games idea. More soon, I'm sure ;).