Peter: I want to see how it can solve a Rubik’s cube before considering it anything more than a more complicated Siri.
How can it do this? Sent from ProtonMail Mobile On Sat, Jun 9, 2018 at 2:30 PM, <[email protected]> wrote: > I’ve been actively working on AGI & AGI-ish commercial systems for more than > 20 years – with a team of 10+ for more than 11 years (combined). > > First paper/ book-chapter: > http://www.kurzweilai.net/essentials-of-general-intelligence-the-direct-path-to-agi > > First R&D company (wayback machine): http://www.optimal.org/a2i2/index.html > > My first (AGI-ish) commercial company: https://www.smartaction.ai/ > > Current AGI development company: https://agiinnovations.com/ > > Current new commercial launch: https://aigo.ai/ > > Whitepaper: https://aigo.ai/vendor/aigotoken.whitepaper.pdf (has *some* > technical details) > > 3 functional demos: https://agiinnovations.com/our-work-demos > > Get you free low Aigo serial# 😊 > https://my.aigo.ai/#cg29690f51be5cb098hfae20h91ae27 > > BTW, I host FB group with >1000 members > https://www.facebook.com/groups/RealAGI/ > > From: MP via AGI <[email protected]> > Sent: Saturday, June 9, 2018 10:57 AM > To: AGI <[email protected]> > Subject: Re: [agi] Anyone interested in sharing your projects / data models > > My model is a genetic algorithm system based on AIXI. It’s a really lame > solution to AGI, being naive and brute force, but it’s something small and > simple any computer can run. > > I call it MINT - for minimal intelligence. > > I really should dig up the old java source... it’s a neat little system. > > Sent from ProtonMail Mobile > > On Sat, Jun 9, 2018 at 11:55 AM, Matt Mahoney via AGI <[email protected]> > wrote: > >> Like everyone else on this list, I do not have a working AGI. It is easy to >> underestimate the enormity of the problem. The most obvious application of >> AGI is to automate human labor. Globally this is a USD $75 trillion per year >> problem. A working solution would have a ROI of world GDP divided by market >> interest rates, about $1 quadrillion. When investors won't even put in $1 >> million into your project, they are effectively setting odds of a billion to >> one against your success. When you count the number of false promises and >> failures to solve AI since the 1950's, that's not unreasonable. It's not >> that I haven't tried. Ten years ago I proposed an AGI composed of billions >> of narrow AI specialists and a distributed index to route your requests to >> the right agents. Building this would require a global effort over decades >> and an economic infrastructure that rewards providing useful services in a >> hostile and competitive distributed computing environment. Agents would >> compete for attention and reputation in a world where information has >> negative value. The distributed index provides a message posting service, >> where all messages are public, signed and dated and cannot be edited or >> deleted once posted, and are routed to anyone who might care. You can find >> the proposal at http://mattmahoney.net/agi2.html Such a project is far >> beyond what one person or even a large company could accomplishment. A human >> brain sized neural network with 10^14 synapses and 10 ms clock would require >> 10 petaflops and about 1 petabyte of RAM. Such computers exist but require >> over 1 megawatt of electricity, compared to about 20 watts for the human >> brain. You would need 7 billion of these computers to replace 7 billion >> workers, requiring 7000 terawatts of power. Global energy production is >> currently 15 TW. This kind of power reduction is not going to be achieved by >> further shrinking transistors, which are already close to the limits of >> physics. It will require computing by moving atoms and molecules rather than >> electrons, something that biology has already figured out but is still a >> long way off for us. Perhaps there are more efficient solutions to AGI. >> Sure, for some problems, like arithmetic. But deep neural networks are still >> the best we have for vision and probably language. The problem is that >> intelligence (measured by reward or prediction accuracy) over a wide range >> of problems increases logarithmically with CPU time and memory because the >> problems themselves have a power law distribution over difficulty. This >> clearly shows as the economy grows linearly while computing power grows >> exponentially. It shows in my own work in data compression as a measure of >> natural language prediction accuracy. The two graphs in >> http://mattmahoney.net/dc/text.htmlare 10 years old but the relationship >> hasn't changed. Ambitious, decades long AGI projects like OpenCog and NARS >> are knowledge representation frameworks with empty knowledge bases and >> inadequate hardware to solve any useful problems even if they were >> populated. Why? Because software is easy and human knowledge collection is >> hard. The design complexity of the human body cannot exceed the compressed >> information content of our DNA, which I estimated to be 300 million lines of >> code. (These numbers from my 2013 paper "The Cost of AI" published in 2017 >> as a chapter in "Philosophy of Mind: Contemporary Perspective" (Curado, >> Gouveia eds). http://mattmahoney.net/costofai.pdf ). This is doable for $30 >> billion, a tiny, insignificant fraction of the total cost. Knowledge >> collection is much harder. Human long term memory capacity is 10^9 bits, of >> which 1% is unique to you and can only be extracted by speech or typing at 7 >> bits per second costing $5 per hour at global average wage rates. This is >> only practical (and still costing hundreds of trillions to collect 10^17 >> bits) by giving up privacy and publishing your personal data. Otherwise you >> are stuck with endless surveys and repeating the same data over and over. >> How many times today did you have to type in just basic info like your name >> or email? Hoping to stimulate some intelligent discussion. -- -- Matt >> Mahoney, [email protected] ------------------------------------------ >> Artificial General Intelligence List: AGI Permalink: >> https://agi.topicbox.com/groups/agi/T731509cdd81e3f5f-Mb45fd1f76d6ed4014a05cc4f >> Delivery options: https://agi.topicbox.com/groups > > [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) > [Permalink](https://agi.topicbox.com/groups/agi/T731509cdd81e3f5f-M0cc21aba8cecdf5f023b0d16) ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/T731509cdd81e3f5f-Me34c95d461515e8ffaf3fa0d Delivery options: https://agi.topicbox.com/groups
