Oops, I mean chimpanzees not gorillas. They outperform humans in short term memory tests. https://youtu.be/ravykEih1rE
On Sun, Feb 24, 2019, 9:46 AM Stefan Reich via AGI <agi@agi.topicbox.com> wrote: > > For example, you cannot learn to remember a 20 digit permutation on a > screen and immediately recall it back no matter how much you practice, > which a something a gorilla can do because its DNA is different. > > Gorillas can do that? > > On Sun, 24 Feb 2019 at 14:46, Matt Mahoney <mattmahone...@gmail.com> > wrote: > >> Colin, I think the source of our disagreement is that we have very >> different ideas about what we mean by AGI. To you, AGI is an autonomous >> agent that learns on its own by doing science (experiments). It is >> completely general and can work in any field like a real human. To me, AGI >> means automating anything we might have to otherwise have to pay a human to >> do. >> >> You believe (I think) that AGI is not even possible in conventional >> computers. I tend to agree. First, transistors use too much power, about a >> megawatt for a human brain sized neural network. We might achieve tens of >> kilowatts using neuromorphic computing at the physical limits of >> minituration. >> >> Second, the brain is optimized for reproductive fitness, not universal >> learning, something Legg proved is not even mathematically possible. >> Instead we are born with 10^9 bits of knowledge encoded on our DNA. That is >> half of what we know as adults, and that knowledge took 3 billion years to >> program at the rate of one bit per generation. For example, you cannot >> learn to remember a 20 digit permutation on a screen and immediately recall >> it back no matter how much you practice, which a something a gorilla can do >> because its DNA is different. >> >> Third, we do not even want autonomy. Then we would have to deal with >> human limitations like emotions and the need to sleep, take vacations, and >> get paid. We work around these limitations and train humans to specialize >> in a million different fields because that is how an organization gets work >> done. >> >> I don't expect AGI to look anything like a human. We already automate 99% >> of work using specialized machines that are vastly better at their jobs >> than humans could ever be. We don't want autonomy. We want to be in >> control. We want to asymptomatically approach 100% as the cost of the >> remaining human portion rises at 3-4% per year as it has for centuries. AGI >> is not a robot revolution. AGI is more productivity with less effort using >> machines that can see and understand language, sense but not feel, know >> what we want without wanting, and recognize and predict human emotions >> without having any. >> >> On Sun, Feb 24, 2019, 1:56 AM Colin Hales <col.ha...@gmail.com> wrote: >> >>> Matt: >>> >>> "When you put millions of these specialists together you have AGI." >>> >>> No you don't!!!! Says who? (1) Where's the proof? (2) Where's the >>> principle that suggests it? You have neither of these things. Even if you >>> had both these things you'd still have to build AGI and test it assuming >>> they are false in order to do the science properly. >>> >>> And you do not get to 'define it' this way. >>> >>> This is SCIENCE. You have an artificial version of a natural general >>> intelligence when you've built one and it (yes the AGI itself, not your or >>> anyone else's blessing) AUTONOMOUSLY proves it. Like fire. Flight and a >>> million other things. >>> >>> I can think of 1000 things that such a specialist-narrow-AI-collection >>> doesn't cover (like everything that science does not know, but could find >>> out), and that a natural general intelligence can autonomously learn (find >>> out), but that 'collection of specialist narrow AI' lacks .... along with >>> an ability to _autonomously_ learn it, which is also something natural >>> general intelligence (yes us) can do. And even worse: such specialist >>> collections have ZERO intelligence, not because it doesn't know >>> something, but because it lacks the _autonomous_ bit. A real AGI can know >>> absolutely NOTHING and yet have non-zero intelligence because it includes a >>> means to autonomously find out. Like us. >>> >>> So that collection cannot be an "artificial version of a natural >>> general intelligence". >>> >>> End of story. >>> >>> Real AGI is defined by how it autonomously handles what it doesn't know >>> (its ignorance!), not by what we bestow on it. If we bestow a means for >>> learning X, that too does not make it AGI. A real but artificial version of >>> a natural general intelligence has to _autonomously_ learn how to learn >>> something it does not know, like us. To prove it you first prove it does >>> NOT know it. Then, later, after learning, when it proves it does, >>> autonomously, it gets a stab at the AGI gold medal. >>> >>> Meanwhile? Nothing wrong with what's being done. Powerful. Useful. >>> Impressive. All good. Rah rah rah, carry on. BUT: Its AUTOMATION based on >>> natural general intelligence, not AGI and it has ZERO intellect. >>> >>> [image: AGI.JPG] >>> >>> The entire AGI project is foundered on this basic fact of the science. >>> >>> And all we ever get here is the endless echo chamber of "if only we can >>> program enough computers" (= AUTOMATION) AGI will magically appear. >>> Rubbish. It was rubbish 65 years ago and we've done nothing but prove more >>> completely it is still rubbish. >>> >>> Enough. >>> >>> I know you'll never face it. Forget it. >>> >>> >>> >>> On Sun., 24 Feb. 2019, 11:08 am Matt Mahoney, <mattmahone...@gmail.com> >>> wrote: >>> >>>> OpenCog is one open source effort. But real progress in AI like Google, >>>> Siri, Alexa etc. is not just software. It's hundreds of petabytes of data >>>> from the 4 billion people on the internet and the millions of CPUs needed >>>> to process it. It's not just something you could download and run. >>>> >>>> I realize it's not AGI yet. We are still spending USD $83 trillion >>>> per year for work that machines can't do yet. There are still incompletely >>>> solved problems in vision, language, robotics, art, and modelling human >>>> behavior. That's going to take lots more data and computing power. The >>>> theoretical work is mostly done, although we still lack good models of >>>> humor and music and much of our own DNA. >>>> >>>> If you want to make progress, choose a narrow AI problem. When you put >>>> millions of these specialists together you have AGI. Don't try to do it all >>>> yourself. You can't. >>>> >>>> On Sat, Feb 23, 2019, 12:33 PM Ed Pell <edp...@optonline.net> wrote: >>>> >>>>> All, why is there no open source AGI effort? >>>>> >>>>> Ed Pell >>>>> > > -- > Stefan Reich > BotCompany.de // Java-based operating systems > *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/T69c9e23ba6b51be9-M7e8c88a665fd613737dfe39d> > ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/T69c9e23ba6b51be9-M6eeb8c2df6ee4b86c924fe78 Delivery options: https://agi.topicbox.com/groups/agi/subscription
