That sounds interesting, please look it up if you can. On Wed, 12 Sep 2018 at 15:26, Nanograte Knowledge Technologies via AGI < [email protected]> wrote:
> Jim > > Bootstrapping a computational platform with domain knowledge (seeding with > insights), was already done a few years ago by the ex head of AI research > in France. I need to find his blogs again, but apparently he had amazing > results with regards re-solving classical mathematical problems. > > Our question is; would that constitute AGI? > > I appreciate your comment on how such an approach would not be considered > radical at all. However, the claim you make immediately thereafter; that > the approach would help to think of the problem in a different way, is > refutable. > > The thinking in terms of relationships suffer the same fate. Not radical, > and not thinking in a new or different way. > > As such, we need to think as radically as we could possibly do. We need to > find a few radical approaches and see if they could be focused on a few > avenues of pragmatic research. May the best approach win. > > For example, instead of relationships, thinking free-will (random) > associations. This is not a semantic ploy, but a radical departure in terms > of AGI architecture. > > Furthermore, instead of thinking of seeding, rather allowing the > computational platform to Find, Frame, Make and Share. This would denote > another radical departure in current thinking (I did come across a similar > approach recently). > > Rob > > ------------------------------ > *From:* Jim Bromer via AGI <[email protected]> > *Sent:* Wednesday, 12 September 2018 2:25 PM > *To:* [email protected] > *Subject:* [agi] Growing Knowledge > > The idea that an AGI program has to be able to 'grow' knowledge is not > conceptually radical but the use of the idea that a program might be > seeded with certain kinds of insights does make me think about the > problem in a slightly different way. By developing a program to work > along principles that are meant to incorporate some way to build on > the basis of insights that are provided as the program explores > different kinds of subjects I think I might be able to see this theory > in the terms of a transition from programming discrete instructions > that correspond to a particular sequence of computer operations into > programming with instructions that have a potential to grow > relationships between the knowledge data. The kinds of relationships > do not need to be absolutely pre-determined because the use of basic > relationships and references to specific ideas can implicitly develop > into more sophisticated relationships that would only need to be > recognized. For example, an abstraction of generalization seems pretty > fundamental to Old AI. However, I believe that just by using more > basic relationships which can refer to other specific ideas and to > groups of ideas, the relationships that will effectively refer to a > kind of abstraction may develop naturally - in primitive forms. It > would be necessary to 'teach' the AGI program to recognize and > appreciate these abstractions so that it could then use abstraction > more explicitly. > Jim Bromer > *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/T032c6a46f393dbd9-M44ff28f8a47bd56696724c2f> -- Stefan Reich BotCompany.de // Java-based operating systems ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/T032c6a46f393dbd9-Mb40e6e3e04e04b8a3b8069b9 Delivery options: https://agi.topicbox.com/groups/agi/subscription
