Thanks MP, I am sending a test email to you now.
Cheers, Jeremy On Tue, Jun 12, 2018 at 4:10 PM, MP via AGI <[email protected]> wrote: > My email is mindpixel at proton male daht Kahm. > > Hopefully all but the minimally intelligent bots out there don’t pick up > on my address. > > But I’ll let you all know if I can find the source or not. It wouldn’t > take long to rewrite it, though. I’ll share the github link when I can. > > > Sent from ProtonMail Mobile > > > On Tue, Jun 12, 2018 at 5:52 PM, Jeremy Owen Turner via AGI < > [email protected]> wrote: > > Hello everyone, > > I have been passively reading the correspondence between all of the > authors. I do not have anything to add to this group at this point and I am > not taking any sides. I am just taking in all of your ideas into > consideration for now. I personally think that some kind of hybrid > approach between all of these cognitive engineering paradigms will > eventually unlock AGI capabilities. > > Apologies to posting this email to the whole group. My intention was to > contact MP directly but I did not see a direct email for MP. > > MP, I would like to read more about MINT (papers, proposals, > documentation, code etc.)...Have there been any toy or real implementations > of a MINT-agent yet - virtual or otherwise? Is this something like MC-AIXI > but even more diluted in its intellectual capabilities and reach? > > Many thanks, > Jeremy > > On Sat, Jun 9, 2018 at 10:56 AM, MP via AGI <[email protected]> wrote: > >> 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.html are 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-Mb45fd >> 1f76d6ed4014a05cc4f 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/T943a4c6b8d2be614-M95e27e631956118babd94900> > ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/T943a4c6b8d2be614-M9ec236ec8b43a9aa87c7affa Delivery options: https://agi.topicbox.com/groups
