watching the world turn.

Another post from the draft pile that I finally polished into something that isn’t a series of half formed sentences… enjoy

The human body as a closed system is not sustainable, as any closed system eventually achieves an equilibrium lacking order. Entropy would increase as the second law of thermodynamics asserts itself. Flux of energy/matter is required to maintain and build order. This is a central part of Ludwig von Bertalanffy’s paper on “general systems theory” and his theory of open systems:

“the conventional formulation of physics are, in principle, inapplicable to the living organism being open system having steady state. We may well suspect that many characteristics of living systems which are paradoxical in view of the laws of physics are a consequence of this fact.”

I think though, that a similar law applies to intelligent systems. Without stimulus the mind is not alive and eventually a lack of synaptic firing would lead to the neuronal weighting between neurons to deteriorate. This would result in a reversal to the initial states that most artificial neural networks start in (they are usually initiated with random weights)… but perhaps this reversal of weights on neurons that no longer fire isn’t a bad thing. It may lead to them being re-purposed…

As one ages, it can become more difficult to pick up new information as existing synaptic channels get reinforced and so the neuronal tributaries of our brains because less used, or require more active effort to use than taking the ready associations that come easily to our consciousness. While these tributaries may get reset to random weightings due to dis-use, this may allowed them to later get stimulated and used to store new associations.

The NY Times earlier this year posted “How to train the aging brain”:

“There’s a place for information,” Dr. Taylor says. “We need to know stuff. But we need to move beyond that and challenge our perception of the world. If you always hang around with those you agree with and read things that agree with what you already know, you’re not going to wrestle with your established brain connections.”

Such stretching is exactly what scientists say best keeps a brain in tune: get out of the comfort zone to push and nourish your brain. Do anything from learning a foreign language to taking a different route to work.

These new scenarios make the brain utilise alternative neuronal branches:

“As adults we have these well-trodden paths in our synapses,” Dr. Taylor says. “We have to crack the cognitive egg and scramble it up. And if you learn something this way, when you think of it again you’ll have an overlay of complexity you didn’t have before — and help your brain keep developing as well.”

Not only that, but if you are encouraging more interesting events in your life, especially those that push and challenge you and your preconceptions, then your perception of time expands. While in the moment it may seem like time flies, retrospectively it will seem like the past took longer. The brain collapses intervals of time where nothing much happens.

So if you don’t push your brain to learn new things, you’re cutting it off from having anything new to work with. It will also be easier to efficiently and compactly store your experiences based on what you already know. This shrinks your temporal impression of memory and, retrospectively, it will seem as though the last 5 or 10 years were but a blink. If you keep using the same arguments, and facing the same challenges, then you will become optimised and specialised at that task, but this will come at the cost of generality and breadth of understanding.

Earlier this week I met with a linguistics PhD student from Victoria University named Myq, we discussed a variety of topics. I shared my experience with OpenCog and suggested he check out RelEx. He discussed his work around disproving a study which investigated the number of words required in a piece of text to retain the core meaning. Basically, a lot of the words in text/speech, although useful for stringing ideas together, are not vital to the message being carried.

This got me thinking…

Since I’m working on NetEmpathy, which is currently focussed on analysing the sentiment of tweets, the meaning within tweets (when it exists) is very high. There’s little space for superfluous flowery text when you only have 140 characters.

Myq mentioned how academic papers are a lot like this now. The meaning is highly compressed, particularly in scientific papers. You’ve got to summarise past research, state your method so that it’s reproducible, analyse the results, etc. All in a half a dozen pages. This wasn’t always the case though. In the past academic papers would be long works which meandered their way to the point. Part of this might have to do with the amount of preexisting knowledge present in society, i.e. earlier on there was less global scientific knowledge available, so to adequately cover the background of a subject wasn’t a major difficulty and they could spend more time philosophising. That’s a topic for another post though…

What I was interested is how densely information is packed. Is this increasing?

My immediate thoughts were: text compression! and measure the entropy!.

Basically, information theory dictates that text that contains less information can be represented in fewer bytes. This is why it’s possible to create lossless compression. You assign frequent symbols to be represented by smaller ones. For example, because ‘the’ is one of the most common English words, you might replace it with ’1′ (and crudely, you could replace ’1′ with ‘the’ so that you could still use ’1′ normally). This way, you’ve reduced the size of that symbol by two thirds without loss of information. Obviously this wouldn’t improve your compression factor and a spreadsheet full of numbers though.

A guy called Douglas Biber has apparently already investigated this information content historically, but from a more linguistic and manual investigation.

What I’d like to do one day is examine the compression factors of early scientific journals, recent journals, tweets, txt messages, wikipedia, etc. and see just how the theoretical information content has changed, if at all.

Another project for when I’m independently wealthy.

Note this post is not to condone racism or sexism, merely as an explanation of how it might come about from embodied experience and probabilistic reasoning, as well as how we might protect against it.

Things like racism or sexism, or over-generalising on a class of people is one of the more socially inappropriate things you can do. However, depending on how your logic system works, it’s not an entirely unreasonable method of thinking (the word “unreasonable” chosen purposefully) – and for any other subject, where the things being reasoned about are not humans, we wouldn’t particularly care. In fact, certain subjects like religion and spirituality are held to less strict standards of reasoning… there’s actually more defense in being racist/sexist then being a practitioner of certain religions. Perhaps this is why these occasionally go hand in hand[1].

So what do I actually mean by this? I’m going to use two methods of reasoning, deduction and induction, and then explain them in terms of uncertain truth. Nothing in this world is ultimately absolute[2] and so it behooves us to include probabilistic uncertainty in to any conclusion or relationship within our logic set.

Continue reading →

A draft post/idea from the archives that I thought it was about time that I release. Funnily, this was entirely before I started working on NetEmpathy – maybe it’s not as disconnected as I thought from AGI after all!

It is my belief that empathy is a a prerequisite to consciousness.

I recently read Hofstadter’s I am a strange loop, whose central themes are around recursive representations of self leading to our perception of consciousness. For some, the idea that our consciousness is somewhat of an illusion might be hard to swallow – but then, quite likely, so are all the other qualia. They seem real to us, because our mind makes it real. To me, it’s not a huge hurdle to believe. I find the idea that our minds are infinitely representing themselves via self-reflection kind of beautiful in simplicity. You can get some very strange things happening when things start self-reflecting.

For example, Gödel’s incompleteness theorem originally broke Principia Mathematica and can do the same for any sufficiently expressive formal system when you force that formal system to reason about itself. One day I’ll commit to explaining this in a post, but people write entire books about the idea to make Godel’s theorem and it’s consequences easy to understand!

And as an example of self-reflection and recursion being beautiful, I merely have to point to fractals which exhibit self-similarity at arbitrary levels of recursion. Or perhaps the recursive and repeating hallucinations induced by psychedelics give us some clue about the recursive structures within the brain.

Hofstadter also later in the book delves into slightly murky mystical waters, which I find quite entertaining and not without merit. He says that, due to us modelling of the behaviour of others, we also start representing their consciousness too. The eventual conclusion, which is explained in much greater and philosophical detail in his book, is that our “consciousness” isn’t just the sum of what’s in our head but is a holistic total of ourselves and everyone’s representation of us in their heads.

I don’t think the Turing test will really be complete until a machine can model humans as individual and make insightful comments on their motivations. Ok, so that wouldn’t formally be the Turing test any more, but I think that as a judgement of conscious intelligence, the artificial agent needs to at least be able to reflect the motivations of others and understand the representation of itself within others. Lots of recursive representations!

The development of consciousness within AI via empathy is what, in my opinion, will allow us to create friendly AI. Formal proofs won’t work due to computational irreducibility of complex systems. In an admittedly strained analogy this is similar to trying to formally prove where a toy sailboat will end up after dropping it in a river upstream. Trying to prove that it won’t get caught in an eddy before it reaches the ocean of friendliness (or perhaps if you’re pessimistic and you view the eddy as the small space of possibilities for friendly AI). Sure computers and silicon act deterministically (for the most part), but any useful intelligence will interact with an uncertain universe. It will also have to model humans out of necessity as humans are one of the primary agents on the Earth that will need to interact with… perhaps not if it becomes all-powerful but certainly initially. By modelling humans, it’s effectively empathising with our motivations and causing parts of our consciousness to be represented inside it[1].

Given that machine could increase it’s computationally capacity exponentially via Moore’s law (not to mention via potentially large investment and subsequently rapid datacenter expansion) it could eventually model many more individuals than any one human does. So if the AI had a large number of simulated human minds, which would, if accurately modelled, probably bawk at killing the original, then any actions the AI performed would likely benefit the largest number of individuals.

Or perhaps the AI would become neurotic trying to satisfy the desires and wants of conflicting opinions.

In some ways this is similar to Eliezer’s Collected Extrapolated Volition (as I remember it at least… It was a long time ago that I read it. I should do so again to see how/if it fits with what I’ve said here).

[1] People might claim that this won’t be an issue because digital minds designed from scratch will be able to box up individual representations to prevent a bleed through of beliefs. Unfortunately, I don’t think this is a tractable design for AI, even if it was desirable. AI is about efficiency of computation and representation, so these concepts and beliefs will blend. Besides, conceptual blending is quite likely a strong source of new ideas and hypotheses in the human brain.

The 2nd International Conference on Advanced Intelligence 2010 has just released it’s call for papers, which you can download here: ICAI2010 Call For Papers.

How is “Advanced Intelligence” different from general AI? The release says:

Typical features of Advanced Intelligence include: (1) Close interaction and coordination between Natural Intelligence and Artificial Intelligence, (2) Ideas and applications that push the frontiers of both Artificial Intelligence and Natural Intelligence, (3) Large-scale Distributed Intelligence and Web Intelligence

FWIW, I’m not sure I agree with the name, since “advanced” is a relative term, and the field of AGI (artificial general intelligence) is already fragmented enough without adding additional labels. Having said that, I’ve been invited to be an assistant co-chair, so I cordially invite you to submit interesting papers since then they’ll be a greater chance of me getting interesting papers to review

The log format for Amazon S3 is slightly annoying. Not overwhelmingly so, but the date field has the field separator (a space) in the middle of it and it isn’t encapsulated by quote characters. Here’s some code to split the fields up, assuming you’ve downloaded the log file already (it’s easy enough to list all logs and retrieve them with boto):

Recently I found out about SizeUp in OSX and found it really useful. Basically it gives you hot keys for window positions, such that you can maximise them vertically and attach them to the left or right of the screen. Great for placing terminal windows and browsers. This is similar to the behaviour in Windows 7 (don’t know what they call it or care, they are just copying this stuff from existing window managers and getting all the credit). You can also send a window to a corner, or maximise horizontally and attach to top/bottom.

I knew it must be possible in linux somehow. For one thing, there’s wmctrl, a command line program for scripting window positions and I found some scripts made by others in the Ubuntu forums that act similar to the way I wanted.

However, it turns out there is something already available if you’re using Compiz as your display manager.

To change to using Compiz and get the required config tool, run:

And then open the menu System → Preferences → Appearance. Go to the Visual Effects tab and choose “Extra”.

Then fire up the CompizConfig Settings Manager that’s also under System → Preferences. When the dialog loads, go to the filter and type “grid”. This is the module of Compiz that gives you almost the same behaviour as SizeUp (you can get the rest of the behaviour using other modules in the “Window Management” category.

• OpenCog is getting get a bit of comment on twitter, which might in part be due to it being linked on Hacker News.
• I’ve started up at Jai Thai Kickboxing, which is just around the corner from where I live so I hope to get 4-5 sessions in a week. After my first session my shins and feet are somewhat bruised, this could indicate that my technique leaves something to be desired. Equally likely however is that my shins just need to harden up!
• I read in the paper that Avatar is the faster movie to reach a billion dollars at the box office. It was very pretty, but it was also only a passable story. I hope that Avatar’s success will show the movie industry that they need to adapt by making cinema an immersive experience so that they are providing people a reason to go to the cinema instead of watching movies at home.
• My life experience keeps expanding and it makes me feel alive. I stand by my assertion that the meaning of life is experience.

Recently I’ve been contemplating a number of potential directions for creating a start-up based on application of OpenCog to a problem or field.

One evening, I had an interesting discussion in bed with my partner that was related to licensing such technology. OpenCog is open source, which is my personal preference for the development of AGI, even if the jury on whether it’s beneficial or needless reckless is still out. As open source software, it means that if we sold expert systems based on OpenCog to end-users, we’d have to also provide the source. Even though we can license it under different terms from SIAI, this isn’t entirely needed since my current viewpoint is that the real value will be in data within the system.

As an analogy, the biological design for the brain isn’t what makes us unique or what encompasses our knowledge and experience of the world. The pattern that’s formed during our childhood and education is what is really valuable, otherwise we’d make no distinction between twins and not particularly care if one twin passed away.

So, the digital mind’s pattern would be the important part that we’d license or sell. However dealing with a dynamic system makes that interesting, since the pattern that was sold/licensed would inevitably change. Learning software could well have the valuable part (the “identity” if you will) morph and change beyond the original deployment. In fact, the software could learn new things which makes the individual deployment “smarter” than the original or any other deployment.

In that case, who owns those improvements? Should we get
the rights, since it was our software that altered itself, or does it belong to the license-holder since the AI learnt the improvement in their environment?

I’m sure with sufficiently rigorous legal-work one could protect towards one view over another, but I’m more interested in what seems right.

It’s Christmas time, and I enjoy getting gifts for people even though I’m not religious. I’ve also been enjoying getting rid of lots of stuff I don’t use/need. This not only makes me feel like I’m clearing out mental space (I have Tyler Durden’s words echoing in my head “The things you own, end up owning you”) but also makes me feel good that other people are getting something that they want/need. Especially since I’m either giving the stuff away or selling it cheaply on TradeMe.

I googled “It’s better to give than receive.” since that’s the quote that’s automatically been ingrained into my psyche. Turns out it’s from the Bible, Acts 20:35 (King James Version):

“I have showed you all things, how that so labouring ye ought to support the weak, and to remember the words of the Lord Jesus, how he said: ‘It is more blessed to give than to receive.’”

(I guess “more blessed” translates to “better” these days.)

Never mind that giving psychologically makes us happier than spending money on ourselves. It also physiologically affects us, by releasing, not only the good old reward molecule Dopamine, but also the love neurotransmitter Oxytocin (unfortunately the mention of oxytocin isn’t in the abstract, but it’s discussed here).

There is another aspect of gift giving I want to mention, which I haven’t got any references for, but is based on my intuition on the mechanics of intelligence. When we give someone a gift, we usually have a reason for it, and when we choose a gift for them we tend to think “Will the person like this?”. The act of that means we have to emulate, model, and predict what they want and by activation it re-enforces their pattern within our mind. Does this inadvertently get us thinking of other aspects of their personality and of what other people might like too? I’ve discussed how part of love is the strong bonding of patterns, one’s self in another mind, their mind emulated in the self. This twinning makes us feel connected to the other person. To me, it makes sense that going through this process while selecting gifts for other people will inevitably make one feel more connected in general. And as mentioned above, the neurotransmitter associated with love is also released during giving.

Maybe this is why the gifting economy of Kiwiburn (and the American equivalent) is such a central part of the festivals and contributes to them being such enjoyable experiences.

“We make a living by what we get, but we make a life by what we give.”
– Winston Churchill