Thank you very much for this elaborated answer, Ben. It helps me to understand the situation better. Now I am digging into the code to understand how things are done. This will take some time. But than I hope to be able to contibute something usefull.
--Andi Am Samstag, 30. Juli 2016 17:09:04 UTC+2 schrieb Ben Goertzel: > > From what I can tell, Google's tech leaders are smart, inventive and > good-hearted people who are not, however, deep thinkers about AGI ... > they are too busy for that... > > Demis and Shane are brilliant, inventive, deep-thinking people who are > however apparently convinced that loose brain emulation (Demis) or > some mix of loose brain emulation and algorithmic information based > approaches (Shane) are the best approach to AGI ... so they are simply > not that intellectually interested in approaches like OpenCog, even > though they're aware of it... > > I would like to have more funds so we could hire more senior > developers and proceed faster. However, I would not like this *as > badly* as I prefer the project to remain free and open source, as I > feel FOSS AGI will be the best course for the good of the humanity and > will increase the odds of a positive Singularity. So being fully > sucked into a big company or gov't agency or typical VC-funded AI > startup situation is not so compelling to me at this point... indeed > opportunities for this have been presented ... > > The odds seem reasonable that with the current favorable climate > toward AGI, OpenCog will be able to secure greater funding during the > next year, so it can grow faster in various directions without > "selling out" .... > > Once we get the project past a certain critical threshold in terms of > funky downloadable demos AND clear documentation and simpler usabilty > by developers, then I think the thing can really take off quickly, and > become as I've said "the Linux of AGI" (just for a start). Getting > to this threshold is proving slow and laborious given the complexity > of the design. But from the inside, the progress is clear. A > moderate-sized burst of funding would get us there, but we can also > very likely get there without that, just not quite as fast... > > -- Ben > > > > > > On Sat, Jul 30, 2016 at 5:08 AM, Andi <[email protected] <javascript:>> > wrote: > > Ben, my congratulations for reaching this point! > > > > I am watching the AI scene since more than 40 years - as far as I can > see, > > the opencog stystem is the richest and by far most probable to build an > AGI. > > > > Why Google does not chain you and your team to a desk at their > > headquarters????????????? > > They need to spend about 500.000.000 USD on new projects every week. Why > > they do not put one week on you and your team???? > > AGI is essential for them. Opecog is the only complete approach to reach > it. > > Is there nobody at Google who watch closely opencog -and- understand > what it > > is doing????? > > > > Respect! > > Andi > > > > > > > > > > > > Am Freitag, 29. Juli 2016 03:32:11 UTC+2 schrieb Ben Goertzel: > >> > >> (proposed R&D project for fall 2016 - 2017) > >> > >> We are now pretty close (a month away, perhaps?) to having an initial, > >> reasonably reliable version of an OpenCog-controlled Hanson robot > >> head, carrying out basic verbal and nonverbal interactions. This > >> will be able to serve as a platform for Hanson Robotics product > >> development, and also for ongoing OpenCog R&D aimed at increasing > >> levels of embodied intelligence. > >> > >> This email makes a suggestion regarding the thrust of the R&D side of > >> the ongoing work, to be done once the initial version is ready. This > >> R&D could start around the beginning of September, and is expected to > >> take 9-12 months… > >> > >> > >> GENERAL IDEA: > >> Initial experiment on using OpenCog for learning language from > >> experience, using the Hanson robot heads and associated tools > >> > >> In other words, the idea is to use simple conversational English > >> regarding small groups of people observed by a robot head, as a > >> context in which to experiment with our already-written-down ideas > >> about experience-based language learning. > >> > >> BASIC PERCEPTION: > >> > >> I think we can do some interesting language-learning work without > >> dramatic extensions of our current perception framework. Extending > >> the perception framework is valuable but can be done in parallel with > >> using the current framework to drive language learning work. > >> > >> What I think we need to drive language learning work initially, is > >> that the robot can tell, at each point in time: > >> > >> — where people’s faces are (and assign a persistent label to each > person’s > >> face) > >> > >> — which people are talking > >> > >> — whether an utterance is happy or unhappy (and maybe some additional > >> sentiment) > >> > >> — if person A’s face is pointed at person B’s face (so that if A is > >> talking, A is likely talking to B) [not yet implemented, but can be > >> done soon] > >> > >> — the volume of a person’s voice > >> > >> — via speech-to-text, what people are saying > >> > >> — where a person’s hand is pointing [not yet implemented, but can be > done > >> soon] > >> > >> — when a person is moving, leaving or arriving [not yet implemented, > >> but can be done soon] > >> > >> — when a person sits down or stands up [not yet implemented, but can > >> be done soon] > >> > >> — gender recognition (woman/man), maybe age recognition > >> > >> EXAMPLES OF LANGUAGE ABOUT THESE BASIC PERCEPTIONS > >> > >> While simple this set of initial basic perceptions lets a wide variety > >> of linguistic constructs get uttered, e.g. > >> > >> Bob is looking at Ben > >> > >> Bob is telling Jane some bad news > >> > >> Bob looked at Jane before walking away > >> > >> Bob said he was tired and then sat down > >> > >> People more often talk to the people they are next to > >> > >> Men are generally taller than women > >> > >> Jane is a woman > >> > >> Do you think women tend to talk more quietly than men? > >> > >> Do you think women are quieter than men? > >> > >> etc. etc. > >> > >> It seems clear that this limited domain nevertheless supports a large > >> amount of linguistic and communicative complexity. > >> > >> SECOND STAGE OF PERCEPTIONS > >> > >> A second stage of perceptual sophistication, beyond the basic > >> perceptions, would be to have recognition of a closed class of > >> objects, events and properties, e.g.: > >> > >> Objects: > >> — Feet, hands, hair, arms, legs (we should be able to get a lot of > >> this from the skeleton tracker) > >> — Beard > >> — Glasses > >> — Head > >> — Bottle (e.g. water bottle), cup (e.g. coffee cup) > >> — Phone > >> — Tablet > >> > >> Properties: > >> — Colors: a list of color values can be recognized, I guess > >> — Tall, short, fat, thin, bald — for people > >> — Big, small — for person > >> — Big, small — for bottle or phone or tablet > >> > >> Events: > >> — Handshake (between people) > >> — Kick (person A kicks person B) > >> — Punch > >> — Pat on the head > >> — Jump up and down > >> — Fall down > >> — Get up > >> — Drop (object) > >> — Pick up (object) > >> — Give (A gives object X to B) > >> — Put down (object) on table or floor > >> > >> > >> CORPUS PREPARATION > >> > >> While the crux of the proposed project is learning via real-time > >> interaction between the robot and humans, in the early stages it will > >> also be useful to experiment with “batch learning” from recorded > >> videos of human interactions, video-d from the robot’s point of view. > >> > >> As one part of supporting this effort, I’d suggest that we > >> > >> 1) create a corpus of videos of 1-5 people interacting in front of the > >> robot, from the robot’s cameras > >> > >> 2) create a corpus of sentences describing the people, objects and > >> events in the videos, associating each sentence with a particular > >> time-interval in one of the videos > >> > >> 3) translate the sentences to Lojban and add them to our parallel > >> Lojban corpus, so we can be sure we have good logical mappings of all > >> the sentences in the corpus > >> > >> Obviously, including the Stage Two perceptions along with the Basic > >> Perceptions, allows a much wider range of descriptions, e.g. … > >> > >> A tall man with a hat is next to a short woman with long brown hair > >> > >> The tall man is holding a briefcase in his left hand > >> > >> The girl who just walked in in a midget with only one leg > >> > >> Fred is bald > >> > >> Vytas fell down, then Ruiting picked him up > >> > >> Jim is pointing at her hat. > >> > >> Jim pointing at her hat and smiling made her blush. > >> > >> However, for initial work, I would say it’s best if at least 50% of > >> the descriptive sentences involve only Basic Perceptions … so we can > >> get language learning experimentation rolling right away, without > >> waiting for extended perception… > >> > >> LANGUAGE LEARNING > >> > >> What I then suggest is that we > >> > >> 1) Use the ideas from Linas & Ben’s “unsupervised language learning” > >> paper to learn a small “link grammar dictionary” from the corpus > >> mentioned above. Critically, the features associated with each word > >> should include features from non-linguistic PERCEPTION, not just > >> features from language. (The algorithms in the paper support this, > >> even though non-linguistic features are only very briefly mentioned in > >> the paper.) …. There are various ways to use PLN inference chaining > >> and Shujing’s information-theoretic Pattern Miner (both within > >> OpenCog) in the implementation of these ideas… > >> > >> 2) Once (1) is done, we then have a parallel corpus of quintuples of > the > >> form > >> > >> [audiovisual scene, English sentence, parse of sentence via link > >> grammar with learned dictionary, Lojban sentence, PLN-Atomese > >> interpretation of Lojban sentence] > >> > >> We can take the pairs > >> > >> [parse of sentence via link grammar with learned dictionary, > >> PLN-Atomese interpretation of Lojban sentence] > >> > >> from this corpus and use them as the input to a pattern mining process > >> (maybe a suitably restricted version of the OpenCog Pattern Miner, > >> maybe a specialized implementation), which will mine ImplicationLinks > >> serving the function of current RelEx2Logic rules. > >> > >> The above can be done for sentences about Basic Perceptions only, and > >> also for sentences about Second Stage Perceptions. > >> > >> NEXT STEPS FOR LANGUAGE LEARNING > >> > >> The link grammar dictionary learned as described above will have > >> limited scope. However, it can potentially be used as the SEED for a > >> larger link grammar dictionary to be learned from unsupervised > >> analysis of a larger text corpus, for which nonlinguistic correlates > >> of the linguistic constructs are not available. This will be a next > >> step of experimentation. > >> > >> NEXT STEPS FOR INTEGRATION > >> > >> Obviously, what can be done with simple perceptions can be done with > >> more complex perceptions as well … the assumption of simple > >> perceptions is because that’s what we have working or almost-working > >> right now… but Hanson Robotics will put significant effort into making > >> better visual perception for their robots, and as this becomes a > >> reality we will be able to use it within the above process.. > >> > >> > >> > >> -- > >> Ben Goertzel, PhD > >> http://goertzel.org > >> > >> Super-benevolent super-intelligence is the thought the Global Brain is > >> currently struggling to form... > > > > -- > > You received this message because you are subscribed to the Google > Groups > > "opencog" group. > > To unsubscribe from this group and stop receiving emails from it, send > an > > email to [email protected] <javascript:>. > > To post to this group, send email to [email protected] > <javascript:>. > > Visit this group at https://groups.google.com/group/opencog. > > To view this discussion on the web visit > > > https://groups.google.com/d/msgid/opencog/d614d10d-f629-427f-97d0-ceeeedc00180%40googlegroups.com. > > > > For more options, visit https://groups.google.com/d/optout. > > > > -- > Ben Goertzel, PhD > http://goertzel.org > > Super-benevolent super-intelligence is the thought the Global Brain is > currently struggling to form... > -- You received this message because you are subscribed to the Google Groups "opencog" group. 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