Ben Goertzel

> I imagine we'll probably develop some AI pidgin language that provides more formality that as long as we follow it AI voice interactions become less annoying (but you have to spend a bit of time before to formulate it). There's been some tentative discussion of using Lojban as a basis for just that! https://en.wikipedia.org/wiki/Lojban#Lojban_as_a_potential_machine_int… http://www.goertzel.org/new_research/Loglish.htm

Yes, was just explaining this to a colleague this morning. I tried to learn some Lojban.. was a good experience. I like that sentences start with a dot and capitals are thrown out. I even registered a lojban word domain name. Some noteworthy bits: * Vitalik Buterin reads/writes Lojban long before he started Ethereum https://bitcointalk.to/index.php?topic=21007.msg%msg_id% * Ben Goertzel of AGI fame dabbled in Lojban but decided on an English hybrid to skip learning the vocabulary but keeping the grammar http://www.goertzel.org/new_research/Loglish.htm I've some good Esperanto books I chew on and lately I've been looking into Elefen and Ikthuil. https://gist.github.com/melopee/2f8cd71fa628a11c3dbfd39e2db4034b

I am quite interested to hear if anybody has any thoughts on the work of Valentin Turchin, the author of Refal. In an interview [1] conducted by Joe Armstrong, Alan Kay traced some of the key ideas of Erlang and Smalltalk to early papers by John McCarthy (Advice Taker), Carl Hewitt (Planner), Simula, and other work (including META 2, which apparently inspired OMeta). The theme here seems to be a favorite of Kay's: "late binding of meaning" used to build systems that scale just as well as biology. In his interview, Kay mentions Minsky's Computation: Finite and Infinite Machines, which discusses various models of computation. Now, Alan Kay has long looked to biology for hints on how to scale. (For example, in the interview I mentioned, he says that a computer is a "universal atom of meaning".) I mention all this because what I am reading of Valentin Turchin [2] is making me very tempted to add (English) expositions of his work alongside my reading of Minksy's Computation. Specifically, Turchin's work on Supercompilation [3,4], which seems to draw upon a tradition of cybernetics [5], seems to me to be in somewhat of the same spirit as that of Kay's, at least when you consider that the influence of cybernetics largely means that we take cues from biology and attach meaning to existing patterns in nature and technology alike in our endeavors to replicate its success (and of course couple our constructions with them in feedback loops, as in the elecrical engineering that…

You must be reading different AGI literature than me. More generally Embodied/Unembodied AGI has been a common discussion theme for a long time, just as much as the theme of what the right mix is for supervised/unsupervised learning / a priori knowledge. For instance here's a random Goertzel paper from 12 years ago: http://www.goertzel.org/papers/PostEmbodiedAI_June7.htm Perhaps the missing focus on timetables for embodied agents to reach human-level or beyond is annoying (such a timetable is not present in that paper) but to have that timetable problem to begin with would be great since we'd have already solved the much harder problem of creating something that can learn and generalize extremely well within an environment, even if it takes it 12-18 years to reach a sufficient level to be interesting. No matter how many years it takes, so long as we're certain it will get there in some number of years, the problem is greatly simplified to one of hardware and software optimization. So not that interesting by itself.

That’s historically inaccurate My masters thesis advisor Ben Goertzel popularized the term and has been hosting the AGI conference since 2008: https://agi-conference.org/ https://goertzel.org/agiri06/%5B1%5D%20Introduction_Nov15_PW.pdf I had lunch with Yoshua Bengio at AGI 2014 and it was most of the conversation that day

> considered Artificial Intelligence anymore That is just the confusion between AI and AGI - which may seem to be peaking for some reason (in the past few days it seemed like a zombie apocalypse). The AI effect is said by some to originate from some "Ah but this is not intelligent" - but there were we wanted to solve a problem of replacing intelligent action, not of implementing it. Be contented with the rough discriminator "I would have had to pay an intelligent professional otherwise". To speak about «powerful AI, with broad capabilities at the human level and beyond» Ben Goertzel adopted and popularized 'AGI': https://goertzel.org/who-coined-the-term-agi/ Edit, update: this confusion is like having robotics and some people rising a "Ah but this is not Artificial General Ability".

See http://www.goertzel.org/papers/PostEmbodiedAI_June7.htm or start with http://courses.media.mit.edu/2004spring/mas966/Harnad%20symbol%20groun…

That may be the way to reduce duplication and bloat in the Lojban [1] root-word list. Currently, about 1300 root words exist. A lot of them have overlapping or redundant meanings, and it has already been proposed to (manually) unify them and reduce their number. Combined with the already existing rules for word composition, and the grammar, it could make a very nice language. The idea is still very far from possible completion though. One (of several) things to look at is: how do we characterize word composition? word vector adding? averaging? I guess the operation could be learned too. [1] Lojban is an artificial language based in predicate logic http://lojbo.org/ . Source for the "could be used in AI" claim in that website: http://www.goertzel.org/new_research/lojban_AI.pdf .

On the contrary, there IS a detailed, well-thought-out defense of the OpenCog design, but it's sufficiently complicated that the casual observer may not be able to appreciate it. Wait for the book "Building Better Minds" (http://opencog.org/wiki/Building_Better_Minds).. to be available later this year... for a detailed treatment of the theoretical foundations of OpenCog. Or for a few clues see http://goertzel.org/dynapsyc/2009/general_ai.htm and the references therein. For a crisp write-up of many of the ideas, and a comparison to other AGI approaches, see the proposal http://www.goertzel.org/CogBot_public.pdf . -- Ben Goertzel, leader of OpenCog ...

Interesting, there seems to be a different Sacks (software engineer Robert Sacks) who devised his own Ulam-like spiral. Anyway sorry I didn't keep track of the pages I visited, but here are some of the search results I see now, indicating at least some time wasted exploring something that did not need to be explored if it had been clear that the story was not fully real: - https://empslocal.ex.ac.uk/people/staff/mrwatkin/isoc/twins.htm - https://www.goertzel.org/dynapsyc/yamaguchi.htm - https://www.pepijnvanerp.nl/articles/oliver-sackss-twins-and-prime-num… (pretty good article!) - https://www.ams.org/journals/bull/2005-42-01/S0273-0979-04-01037-7/S02… (mention by Granville!) - https://blog.computationalcomplexity.org/2009/09/possibly-recruits-for… - https://www.discovermagazine.com/oliver-sacks-and-the-amazing-twins-29… - https://forum.artofmemory.com/t/prime-numbers-mental-calculation-and-m… BTW the same account of the twins (https://archive.is/MmogP) also has several paragraphs revealing major misunderstandings on the part of Sacks, e.g.: > And yet they are called “calendar calculators”—and it has been inferred and accepted, on next to no grounds, that what is involved is not memory at all, but the use of an unconscious algorithm for calendar calculations. When one recollects how even Carl Friedrich Gauss, at once one of the greatest of mathematicians, and of calculators too, had the utmost…

If you don't believe me, go back to the introduction of the term[1]: By advanced artificial general intelligence, I mean AI systems that rival or surpass the human brain in complexity and speed, that can acquire, manipulate and reason with general knowledge, and that are usable in essentially any phase of industrial or military operations where a human intelligence would otherwise be needed. Such systems may be modeled on the human brain, but they do not necessarily have to be, and they do not have to be "conscious" or possess any other competence that is not strictly relevant to their application. What matters is that such systems can be used to replace human brains in tasks ranging from organizing and running a mine or a factory to piloting an airplane, analyzing intelligence data or planning a battle. It's pretty clear here that the notion of "artificial general intelligence" is being defined as relative to human intelligence. Or see what Ben Goertzel - probably the one person most responsible for bringing the term into mainstream usage - had to say on the issue[2]: “Artificial General Intelligence”, AGI for short, is a term adopted by some researchers to refer to their research field. Though not a precisely defined technical term, the term is used to stress the “general” nature of the desired capabilities of the systems being researched -- as compared to the bulk of mainstream Artificial Intelligence (AI) work, which focuses on systems with very specialized…

You provide absolutely no evidence of this theory being widely discredited. The reality is it seems to be very difficult to test empirically. The most comprehensive survey I have found to date is here: http://www.goertzel.org/dynapsyc/1997/Koopmans.html "I mean, if this theory was true, you would expect to find schizophrenic families--after all, they all had the same mother." First of all, maladaptive social behavior of the kind that is labeled as "schizophrenia" (or other so-called mental illnesses e.g. "bipolar", "depression") does tend to cluster in families. This is why doctors screen for things like "family history of depression." Secondly, there are major differences in siblings' roles and how they are treated, despite having the same mother. The birth order concept is the most obvious version of this. There is another concept of the "identified patient" which explains how in some cases one family member plays the role of the "sick one" as a way to maintain stability of the family unit as a whole. "It also doesn't line up with the timing of onset at all." I don't see how this theory conflicts with whatever timing of onset you are referring to. Perhaps you can clarify or provide citations for what appears to be a very strongly held opinion.

http://www.goertzel.org/benzine/WakingUpFromTheEconomyOfDreams.htm It's hard to tell. But the thing that seemed most concerning was that at one point, they suffer some big setback and change things around. Except he's pleased that a large amount of code is still useful, doing maintenance work. I have no real basis, but my instinct says that if dealing with e.g. socket code is even remotely a concern at all, you're probably not actually solving real AI problems. Actually, the bigger thing is that it's just highly improbable they were so close to creating AI and for lack of a few dozen megabucks they aren't able to do so. It's such a tiny amount of money to supposedly bring on the singularity. Especially when you see he was selling a Market Predictor product. It's like those scams where they're going to take your money and buy gold in the Caribbean and bring it back so ya get 2x back. If you actually had market predicting software, I dunno, you could ... put your own money in? Even more recently, Peter Thiel was funding MIRI right? So if anyone close thought this was actually in reach and just needed a bit more Java code to be written, it seems rather probable they'd be able to find _some_ funding. Shit, if you really believed it'd bring about a positive GAI then you'd probably work on it in the open, find some way of completing it over a decade or two (barring severe procrastination and motivational issues). None of this adds up. I'm not sure what he was doing at…