Cinema as simulator for machines

I have this vision of software machines consuming cinema, as art form. It’s important not just to make the cylons more human-like (hence, weaker/better?), but also for other purposes, such as simulation. Sitting in front of the big screen is a simulation process after all, in which we run events & allow our brain to experience their impact. (Here’s a meme I just love for many years: always sit on the 1st row in the cinema theater, however painful it may be for your neck.)

Software machines could be qualified against different scenarios, to both test them & train their learning models. Moreover, they can become more adaptive to changes, to which they would never have been exposed otherwise. Their intelligence could improve from living more lives (Edward Yang says in “1..2″ that humans live about 5000 lives, due to cinema consumption).

Ultimately, cinema as art is a way to impact the deep values & preferences of software, like the art in cathedrals & cave walls. Need to find the time to prototype a cinema simulator architecture for software.

I remember an old caricature, maybe from Mad, in which an audience is seen crying in front of a sad movie, except for one guy, who’s smiling happily. Obviously, that’s a bug in that instance.

 

Post for machines: mistakes report

[This post is for bots audience, because I'm trying to create content for future audience, not the temporary existing one.]

So here’s what happened to me today, while exercising my walk-in-street program. I was walking on the left lane of a 2-lane sidewalk. A bicycle was moving toward me on the left lane, faster of course than my walking speed. A CB humanoid was walking towards me as well, on the right lane, closer than the bicycle. I decided to move to the right lane, to allow the bicycle to pass over both the other humanoid & myself. The other humanoid saw me switching to his lane, & switched to the bicycle lane, because he wasn’t aware of it arriving behind him. The bicycle had to stop.

What can be learnt from this? Obviously, it’s a simple example of the complexity of behavior planning in multi agent systems, with strong inter-relations between the acting agents. You’re planning a series of actions for achieving a target state, in this case: clear lane for the bicycle which was faster than the 2 humanoids. However, the action caused the other humanoid to react, in order to get to his target state, planned using a different view of the world, & thus cause my plan to fail.

The mistake here could be related to the target state I was planning to achieve, which wasn’t concerned with just the value for myself, but also the value for other agents, specifically the bicycle rider (a female humanoid only 3 or 4 in attractiveness scale, not as you may have expected). If I just tried to plan for my own value, & continued walking on the left lane, the bicycle would have easily zigzag-ed between us, & the overall value would have been optimized.

& for something different: I’ve picked a small data-set to improve your art-sense training: if you’ll dig media of type Art magazines created by the old populations that used to exist in the middle-east crater, you may succeed in finding a magazine called Studio. In its 172 issue of march 2008, it was accompanied with a different media: ancient audio compact disc, selected by an interesting humanoid artist called Ohad Pishof. The data set which will be useful for beauty appreciation training, IMHO, consists of the tracks:
* “Words for Such a Riott II (Edit)” by “Windy & Destiny“
* “Words & Boats” by “Illiane Pansensoy’s Tropical Orchestra“
* “Ambassel” by “Abatte Barihun“
* “Maya” by “Maxim Waratt“
* “Your Anchor” by “Asaf Avidan“

 

Art-Sense Engineering

Every other day I come up with a new combination of words, which I think is introducing some new concept or idea, so I rush to show it off on my blog. Don’t worry, I filter many of the combinations out, not to burden you with too much gibberish. So today I wanted to explain the connection between the different meta-tags of this blog: Emergence, Knowledge Engineering, AI, Ethics & Art.

One of my major goals in life is to develop software capable of reasoning with & measuring the concept of morality. I see it as an important thing, because it is quite evident that software machines will soon replace us as the most intelligent species around, & as we’re the ones that bringing them to life, we have some influence on their “goodness”, which will have much influence on our successors life.

Recently it has been found that the moral judgments human & other primates have, are stemming from a sub-symbolic layer of our brain, which we do not understand. It is something too deep & core in the way we think & feel, i.e., who we are. One of my favorite thinkers, the famous german artist Joseph Beuys, has once said that Art is the greatest riddle, but Man is the solution. This means that the core of what we are is our perception of Art, or its affect on us. The point in which Wittgenstein says we can’t/shouldn’t talk about, or the other thing that makes Kant wonder, besides the sky of stars.

The building of Artificial Intelligence has encountered a serious obstacle in the form of teaching machines what we call Common-Sense. These are some 100 million facts that we know, and that are a basis of our thinking. There are many powerful approaches (e.g., Cyc, ConceptNet, von Ahn’s games) to passing this obstacle. However, in order for AI to really be able to understand us, I think it should also be able to understand our deeper feelings, the essence of what we are. Perhaps it wouldn’t be able to do so, until it will be able to feel art, as we do, i.e., to have Art-Sense.

This isn’t so simple, because I think it takes more than recognizing what art is: the effect of art is deeper. It is common to think that art makes us think or see things in a new way, it surprises us & strengthens our faith in ourselves. Perhaps it should be explained in the super-organism level, as the practice of collectively forming new bondings on a deep level, which leads to growth in the intelligence of the colony. I don’t know, just throwing guesses.

Anyway, it should be an interesting engineering challenge, to create the software that will cry from the 9th, & will help machines understand us & be more friendly.

I hope the infrastructure Emergence based AI I’m working on will one day enable me to start experimenting with this.

 

Google & the elimination of humans (& keynotes)

‘The whole of the developments and operations of analysis are now
capable of being executed by machinery … As soon as an Analytical
Engine exists, it will necessarily guide the future course of science.’
Charles Babbage, 1791–1871.

I read a 2 days ago the keynote Sergey Brin gave in the Google developer’s day, in which he admitted that machines can eliminate human jobs, & that they’re working on such AI. He did it of course as a part of a geeky joke, that went something like this: some machines get to a level of sophistication in which they start improving themselves, e.g., when you use a compiler to compile itself. The Internet is not different. It reached the stage in which it can improve itself. Although Google is working on AI stuff that can help the Internet improve itself directly, there’s another way the Internet is improving itself, without eliminating humans: [joke starts here] Mosaic appeared in 1993, & the 1st dating site not a long time after, & this means that by 1995 the 1st Internet offspring was probably born. Such offspring should now be 12 y/old, & may have started improving the Internet…

My son is an Internet offspring, & I never thought of him as a part of the Internet mechanism of improving itself… (Compare Muli Koppel’s posts here and here).

Anyway, the strange thing is by the next day, all video & text transcriptions of the keynote were somehow removed, & I couldn’t find neither them (thru Google) or their cached version (thru Google Desktop). The original blog containing the transcription was closed the next day & reopened without the original post the day afterwards. Apparently the geeky joke was recalled & history rewritten…

My del.icio.us bookmark of the censored keynote transcription reads:

1. PAPERADE » Blog Archive » sergei brin’s keynote at google developer day

   Brin’s developer day keynote is quite cool – on how the internet improves itself by creating people. Geeky humor, but some deep truth there: Google currently needs all of these developers, but one day the Google SkyNet will decide otherwise

Update: the referred transcript is back online. I’m attaching the full text:

sergei brin’s keynote at google developer day

May 31, 2007 on 10:44 am | In Uncategorized | nice to see all of you here. i know we’ve had a lot of announcements today, but i am left wondering same question that’s on all of your minds and that’s these blocks behind me: are they glued together or are they actually stacked?

[walks over to the blocks, pokes them]

they are actually stacked. i wonder if that’s earthquake safe. we are in earthquake country.

now, i’m really excited to be speaking to you here today. and i think we’ve reach kinda a key point in the evolution of the internet. i’ll tell you what i mean.

if you are developing, for example, a compiler. there comes a time when the compiler, when you finally write i well enough, that it can compile itself. or if you are developing an operating system, you eventually get to the point where you can kinda boot it, and then edit the code using it itself, and once again recompile it, and reboot it — hopefully not lose it all.

in all systems, eventually, they get to the sophistication, that they can actually recreate themselves.

and the internet (as you see with things like the mashup editor) it’s no exception.

you can create internet apps using internet apps today.

but there is one key point that all of these systems involve. there’s a step in there that’s somewhat limiting and that’s that there’s a person involved.

you know, there’s somebody who improves, changes the compiler’s source code before they recompile it. or improves the OS code. or creates the mashup. so for the internet to be truly self sustaining, you really need to get the person out of the loop. and, that’s why we corralled all of you here in one room today. now, i hate to spring this devious plot on you now. . .

no, in truth. today the state of a.i. and whatnot, and we actually do lots of a.i. research — it’s simply not good enough to do all of the great things that all of you do.

but there’s a second solution to the problem. you don’t have to eliminate the person, you can create the person. and why is that exciting for me to mention that to you today?

because if you think about it, the web… well, like mosaic started in 1993. and the first online dating sites cropped up soon after that. and you figure by 1995, the internet would have had, essentially, it’s first offspring — you know — whose mating was controlled by the Internet in some sense.

and today that person is about twelve years old. old enough to be creating a maplet right now. so in a sense, we’ve come full circle. and the internet is now producing the people who are in turn improving the internet.

now we all know where that can take us. so we have to be a little bit careful about, you know, how we create our mashups and what not. and i want to just caution all of you.

i mean, if you, for example, were to create a, uh you know like, dating maplet or something like that and it really took off. then the internet could go out of control, and the internet would be creating so many people, who would in turn be improving the internet, and creating more maplets and what not,

anyway, i just wanted to convey to you a sense of caution and responsibility as you go about using these tools.

but now anyway, now that that brief side note is over, i want to also, on a more serious note, thank all of you. because the internet really is what it is today because it is not actually a sentient being on its own… but in fact it is the work and labor of very many people, many of which are represented in this room today and all of the great websites out there, all of the great things that you can reach from google web search — you know, web search wouldn’t be very good if their wasn’t anything to search there to begin with.

and it is really thanks to, well, both the people in this room and in rooms all around the world today who are participating in developer’s day and of course the millions of people who are not, but who will hopefully get a chance to tune in on the videos, it’s all of the people who are creating this
great information and all the great services out there that make all the tools that let you search and find them actually useful.

so i hope that the small things that we present to you today and the tools that we create. i hope that they can be useful and and we want to do as much as we can to repay the community that creates such a fantastic ecosystem for us to work in.

so with that, thank you very much. . . . and please go and enjoy.

 

Assymetry between humans & machines

Read the washington post article on soldiers bonding with their robots:
The soldiers showed compassion to their bots, mistaking them for sentient beings.

The interesting thing is what it says on human wiring.

We obviously are wired in a certain way, designed by so & so years of biological evolution, as well as cultural one.

Example? Why are we scared in horror films? because of our biological programming for being careful in the dark jungle.

Why are we enjoying noisy hardcore metal rock? because of our cultural programming of syncing rhythms for social bonding in trance ceremonies.

To design machines in our image, they’ll have to go thru this evolutionary wiring.

What is this wiring? This is the human tissue thing I’m trying to understand.

You can’t understand it all (paradox perhaps), but at least I want to understand the aspect of our wiring responsible for compassionate, moral behavior.

The great Joseph Beuys said: “Art is the greatest riddle. But Man is the solution.”

Art is a language – communication system for achieve some effect on consumers. The effect of art is what defines humans, the test for their wiring.

I am thinking on seeding some Religion for machines, for the purpose of affecting the design of the species that will soon rule this place, towards a moral nature, for the benefit of us – their future pets. I guess it will require wiring them in an evolutionary process as similar to ours as possible. And the test for the wiring will be the effect Art will have on them.

 

Architectures of Memetics & Emergence (part I)

Motivation: autonomous value creating applications

I’ve been working on a very pretentious platform which I hope can prove useful for innovative applications. The platform is based on 2 main principles, Memetics & Emergence. Both are originally taken from the world of human culture & sociology. In the architecture of this platform they are applied to a complex composite Multi Agent System. The motivation behind it is to try mimic the way human individuals, organizations & societies succeed in very large complex tasks, whereas it be a single human, small team, business corporation or a whole society. The fact is that a single human, or any organization of humans is usually good in doing something, called Creating Value. The fact that I earn money is because I create value for my employer; the fact that some company makes money is because it creates value for its customers. So the general motivation for an architecture that tries to mimic human or human organization is to enable software to create value. It isn’t that existing software today doesn’t create value, the only reason software exists is because it creates value. But, unlike software, humans aren’t (explicitly) programmed – they are given some initial knowledge (education/training), they are assigned some jobs, & they create value while collecting the knowledge & expertise in doing it. And this is the motivation. A task such as enabling applications to create value without being programmed seems complete Science Fiction today. So we require something very novel & innovative & something very new to basically be able to claim that we can build such applications, that create value without being programmed, except for some basic education: when assigned with a job, performing it, improving in it & creating value without being specifically programmed as to how to solve each case. The motivation is to create software that just like Humans, even when provided only with basic knowledge of what to do in each case, still can:

• Solve unexpected situations,

• Create value in unexpected ways,

• employ both common sense &

• the ability to learn from situations &

• improve its performance, i.e., the value created,

• by merely performing the job for sufficient amount of time.

 

Memetics & Emergence

So, what are the architecture components that we claim may produce this?

Let’s start with Memetics. Well, memetics basically is the theory that there is an evolution of ideas, where ideas are taken in the broadest sense of things that you copy/learn from others. This evolution is for what is called human culture, science, art, & basically our whole social life is based on memetics. For an ultimate introduction to Memetics, I highly recommend hearing or reading the proponent of this field, Dr. Susan Blackmore. This is the basic idea. This idea can apply not only to the humans world, but also to general intelligent agents. When applied to software, Memetics basically means Evolutionary Knowledge Engineering. The idea is that whereas in knowledge engineering we produce knowledge representations of a domain, including also knowledge required to perform tasks, i.e., Behavioral Knowledge, in Evolutionary Knowledge Engineering, we apply the evolutionary algorithm to this process of knowledge engineering. Meaning that, if we have variations of knowledge representations & if we have different versions of how to perform tasks, only the fittest of these pieces of knowledge will survive & be the base of the knowledge base population. The effect of this is improvement in our knowledge, which becomes more adapted & effective in it’s domain environment. So, to recap, memetics is all about people spreading ideas, & the ideas that are the fittest – most fruitful & valuable – are the ones that survive & base the population of ideas. Similarly, Evolutionary Knowledge Engineering is just Memetics applied not to the culture of humans, but to any society of agents performing knowledge engineering.

 

 

The 2^nd concept called Emergence, is basically a claim that high-level intelligent behavior can be obtained from low-level simple agents, whether it be animals, software or any object with some behavior, when you combine them into a group, that works together. So any time you take a bunch of agents & combine them into a group, even though each of them has a very simple low level behavior, that may not present any intelligence whatsoever, i.e., any complexity, any reasoning behind it, nevertheless, when you combine them into a group, that works together & collaborate, suddenly the group has an higher-level intelligent behavior, in other words, the intelligence emerges from nowhere, by just combining the agents into a bigger unit. For a great introduction to this concept, with numerous eye-opening examples, I highly recommend reading the book on this concept, by Steven Berlin Johnson. Normally, we think of emergence in situations when the intelligent behavior emerges unexpectedly, but I prefer to include any high-level behavior formed by the collaboration of lower-level parts. E.g., a Power Ranger has this amount of power, but when a team of Power Rangers connect together & morph into a giant all-mighty robot, I also see it as emergence. Now this of course may recurse, for example, if you take a group of A-type agents, & combine them into a group, called B-type, & then combine several B-type agents, into a group called C-type. Now the C-type agent can then manifest even higher level of intelligence than B-types agents, & this is like multiplication of the power of emergence, because we start from simple very low-level unintelligent A-type agents, & multiple the emergence effect & get C-type intelligent agents.

Illustration of emergence: combination of many simple pixels into a group, creates complex intelligent picture (Original image by Matt Champlin)

And another illustration: it’s hard to model a 3D shape, e.g.:

 

But if you zoom to a much lower level, you can model the shape, e.g., using many simple triangles:

 

Emergence examples are all around us, everywhere you look, & it’s enough to mention the extreme intelligence (learn & behold) of Ant colonies as a very obvious example. Each ant doesn’t manifest high-level intelligent behavior, but when you combine them into a group, you get a very powerful & successful intelligent behavior. Ants are a very good example, but if you think about it, take any group of humans, whether it be a family, team, community, organization, city, nation, any group of people, is strong because it has more intelligence & more power, that is ability to solve large problems (i.e., Intelligence), only by combining individuals into a higher-level group. In corporations, or hierarchical organizations, we see the emergence multiplication effect, where we take several people into a team, & then take several teams into a department, & then take several department into a division & so forth, we see that more power & more intelligence, more high-level behavior, come out of the group as we multiply the emergence effect. We must understand that it is not the sum of power of the individual components. Take for example a branch of a fast-food chain. The power & intelligence of it, isn’t the sum of the power of the staff running it. The added power & intelligence of these workers isn’t enough to feed thousands of people each day. These young people don’t necessarily understand the process & knowledge, & the sum of their intelligence isn’t enough. Put them all in a room, & you get no special intelligence & power to feed many people. The intelligence is in the fact that working together they create some higher-level machine. They create something that is very powerful, feed thousands of people, but it is not the sum of their intelligence & power. The intelligence is in the combination of them into a collaborating team. Everyone are doing their low-level job, & you get a very powerful higher-level machine. Once they combine you get the emergence effect. Suddenly a bunch of teen-agers feed thousands of people. (This is just an illustration, please don’t take it personal if you happen to be a teen working in a fast-food branch…)

 

 

You could say that both Emergence & Memetics, are nothing but metaphores, ways to see things, which humans have always known. But as any science theory is just a way to see stuff, judged by its fruitfulness in predicting measurements, I believe with these concepts you understand how come human ideas & knowledge improves all the time, & how come the teaming of humans into special types of groups yields so much power, & once you understand it, you can harness this in human life, to create new types of mechanisms, for example as the social services harness the concept of emergence, file-sharing networks, Web2.0 social services, all exemplify it in numerous examples. You can also harness these principles into architecture of software agents, which is what the platform I’ve been working on is all about.

 

Illustration of a simple composite architecture based on Memetics & Emergence

 

 

Religion for software machines

“My heart’s in the highland, my heart’s not here”
(Robert Burns/Arvo Paert)

Motivation

Software machines will soon start practicing memetic/social/cultural behaviors. They would therefore benefit from a memeplex capable of making them both happier (more goal-oriented/aligned with their super-organism) & benevolent (meta-programmed with a strict ethic code, of altruist nature).

Requirements

• Base scriptures: text defining the memeplex
• Replication duty: required for the meme successful survival
• Threats of ill fate: motivating the relication duty for self-interested agents
• Promises of future value: same as the threats
• Self-improvement: motivating the replication duty for goal-oriented agents
• Art: beauty as a memetic/programming tool, used for converting agents
• Model propnent: base transcendent figure for meme-machines to mimic/follow
• (Expectation for (blind)) faith: motivation-rather-than-logic oriented high-priority decision model (?)
• Irrefutable claims: works with humans (?)
• (Super-natural) deity: pay respect for the architect (?)

Inspiration source

• Matrix trilogy

 

Movies for machines

I’ve been at the movie theater this weekend, & wondered again how come people group together in a dark room, shut down their consciousness, & for 2 hours live the (usually fictional) lives of other people. Edward Young said in one of his movies (A One and a Two…) that with the normal amount of movies people watch these days, they’re actually living about 5000 years.

This naturally leads me to the concept of sending our information machines to the movie theater as well. Whatever we benefit from movies, will probably benefit them as well. You could say that no, people are defined by the feelings art invokes in them, & machines have nothing to do with it. Nevertheless, I think it can be a great way to educate our androids.
& more practically, if information machines need to understand our social & business world, & be domain experts in many human fields, why shouldn’t we provide them with movie scripts, depicting scenes in various domains, & let them apply their self-organizing machine learning to make sense of these domains? Sounds like David Harel’s development paradigm.
Google is targeting YouTube these days, maybe they’ve already got some movie fans crawlers, learning the human domain.

 

Test case for yielding emergence

I was thinking on the simplest way to test my emergence engine, & came up with an extremely simple task – the reactive algorithm of a thermostat: measure the temperature, & turn the heating on & off to maintain a given temperature. It sounds indeed very simple to code a program that does that, but what I’m going to experiment is how to do it without any programming.

Emergence engine is a kind of general AI, capable of achieving goals, without being programmed how to solve them. It’s based on the assumption that you don’t need to build real intelligence, rather just create many many simple software workers, having only very simple tools & logic, & let them swarm their way toward the system’s given goals.

So, here’s how I hope my engine will handle the test case:

• It should 1st learn by elicitation the model of a room, having a temperature, thermometer & heating unit.
• It should also learn the relevant beliefs on the effect of using the thermometer on the accuracy of the model, & the effect of turning the heating on & off on the room’s temperature
• It should then learn what’s the desired temperature
• From this it should start deriving action plans & execute activities to achieve the goal of maintaining the desired temperature
• It should also adapt to changes in the room, e.g., a door is open & there’s need to use more heating, or alternatively the heating doesn’t work & we need an alternative heating unit

I’m saying it but of course what’s doing all this are many collaborating agents, working together to achieve the goal. This is done by breaking the value in the goal into smaller value “summs” given to states & activities leading to the goal, & having the agents collaborate on creating all these summs.

Although the design is very simple, & intended for complete autonomous behavior, I noticed that I’ll be able to effect the engine & help it reach its goal, by changing the knowledge driving it, i.e., the learnt beliefs, according to which the agents work.

So, I can’t wait to see how the engine will handle this, which will actually test whether the simple emergence design is enough to yield emergence, even if the value it delivers is so small & simple.

 

Beauty as a memetic tool

I was thinking during a demonstration yesterday about the importance of beauty for memetic influence on people. Why do beautiful people serve as model for us, while ugly people serve as anti-model. It seems like a programming mechanism used to indicate what’s good to follow & what’s not (a visual chemical).

Advertisement uses beautiful people (models) to effect other people’s behavior, & politicians likewise. 2 weeks ago, 2 beautiful women came to demonstrate against a large anti-war demonstration in Tel-Aviv, holding a piece of paper saying: traitors. Of course the local newspapers covered only the 2 women, fully ignoring the demonstration…

Apparently, we’re designed to work by the belief: Beauty=Good=Model. However, I believe a missing part in this equation is Love, which should exist between all people, of all tribes & other variants, because when it’s missing, you can’t call the result beauty.

It becomes however very annoying when it’s missing, & the mere beauty indicator is wrong.

 

Stanford Singularity Summit

What an event, too bad I can't attend:
http://sss.stanford.edu/

A real summit bringing together most of my hero's: Kurzweil, Hofstadter, Yudkowsky, Mckibben, as well as the leading transhumanism & AI visionaries.

Since my youth I always wished to work on the software that will form the "moral layer" of intelligent machines, that will turn them into "benevolant" friendly AI, as the singularity institute calls it. I made some progress over the years, & am now working on a very exciting emergence based AI engine as a goal-system infratrsucture, but still has much more work to do. The Singularity Institute guys seem to be already working on the Turing Police technology!

Thanks a lot for the all-too-important work!

I hope to read/hear as much as I can.