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In both this demonstration and the demonstration by Google of image generation by neural networks (http://www.popsci.com/these-are-what-google-artificial-intell
by Aqueous 11y ago
In both this demonstration and the demonstration by Google of image generation by neural networks (http://www.popsci.com/these-are-what-google-artificial-intelligences-dreams-look http://www.popsci.com/these-are-what-google-artificial-intel...) you can see hints of organic, naturalistic behavior emerging from artificial networks. Is there any doubt that such networks can simulate even more complex aspects of our cognition? Isn't the writing on the wall (no joke intended) with regard to the Strong AI hypothesis? Or at least a stronger weak hypothesis.
- why-el 11y agoAre we sure what is being simulated here is cognitive? It seems to me merely mechanical. Not to deride the achievement of course.
- iaw 11y agoI think we may be reaching a point where the line between mechanical and cognitive get blurred slightly. While I feel that this falls into the mechanical end of the spectrum because I understand how the model was created, RNN's demonstrate some very fascinating emergent behaviors that will become more complex as computational power increases. I wouldn't say that this is cognitive but it definitely learns to perform a skill in a similar fashion to intelligent beings which is remarkable. Extrapolating that behavior to self-awareness isn't likely however (of course this could lead to a philosophical debate)
- Aqueous 11y agoWouldn't this be an example of motor cognition (https://en.wikipedia.org/wiki/Motor_cognition https://en.wikipedia.org/wiki/Motor_cognition)? Isn't this essentially what motor cognition does when we write?
- ericjang 11y agoMechanical vs. Cognitive are good adjectives! Maybe cognition is more mechanical than not.
- Aqueous 11y agoCouldn't this be seen as a kind of motor cognition (https://en.wikipedia.org/wiki/Motor_cognition https://en.wikipedia.org/wiki/Motor_cognition)? Isn't this essentially what motor cognition does when we write? Perhaps this is more low-level than that, but it seems to me this neural network embodies the 'muscle memory' we develop when we practice handwriting.
- justonepost 11y agoAre we sure cognition isn't merely mechanical? Neural networks are pretty basic and yet they provide compelling products.
- romaniv 11y agoCognition is not "merely mechanical" by definition. If it was mechanical, there would be no special word to distinguish it from other reactions of the natural world.
- baddox 11y agoThat's certainly not true. The term "cognitive" could refer to a proper subset of the set of "mechanical" things. Terms for subsets are still useful.
- romaniv 11y agoSo I guess you're fine with calling books "merely paper" because they are a "subset" of paper-based products? And you're fine with calling people "merely animals" because they're a "subset" of animals? Human language is not based on set theory. There is a huge difference in connotations here.
- eidyia 11y agoHe said "Terms for subsets are still useful.", so I would guess no he is not fine
- baddox 11y agoContext is important, and the word "merely" can be interpreted in multiple ways. In the first case in this thread, I understood "merely mechanical" to mean "only mechanical," i.e containing nothing that is not mechanical. Using that definition, then humans are merely animals, because they're not something that's not an animal. Books are a bad example, because they do have things other than paper (like ink, glue, maybe a plastic or leather cover). You seem to be using "merely" to mean "nothing more specific than," which is a very different meaning that would not be appropriate when talking about things which are subsets of other things.
- ericjang 11y agoThe "organic" behavior you see is replaying the natural statistics of actual handwriting trajectories. I suspect that generative models that "compress & replay" human data in order to mimic humans will lead to more complex AI systems, but capturing the statistics of "internal" processes like cognition and consciousness are still far away (and may require advancements in cognitive neuroscience first).
- heygrady 11y agohttp://www.technologyreview.com/view/518006/how-a-fly-brain-detects-motion/ http://www.technologyreview.com/view/518006/how-a-fly-brain-... I'm not an expert but... Fly brains and human brains already have have neural networks for common tasks, like sensing motion, baked into our genetics. Evolution has already trained these networks to an extent. Training a computer-simulated neural network seems to yield similar results to what nature has done. My personal uninformed opinion is that we'll start to see how much human experience and expression is driven by our brain wiring. That we'll discover how similar we all are to each other based our wiring. And that we'll find that approximating advanced cognition will be the result of putting that wiring into a computer model -- and having a computer powerful enough to run it.
- romaniv 11y agoMy personal uninformed opinion is that we'll start to see how much human experience and expression is driven by our brain wiring. In other words, we will start thinking about people as if they are mere things. Complex things, but things nevertheless.
- heygrady 11y agoAnd, at the very least, thinking about the human mind as an object will lead to greater advances in artificial intelligence. IMO. My mind will change when my brain does. https://en.wikipedia.org/wiki/Neuroplasticity https://en.wikipedia.org/wiki/Neuroplasticity
- eli_gottlieb 11y ago
- cristianpascu 11y agoMachine learning is reproducing the result of a process but not the process. It's easy to be confused about it, and many are. Just like when we call "thoughts" to be patterns of some sort, so then any sort of pattern is a thought. The logical error in this should punch you and any sentient being right in the stomach and leave you breathless for a few good seconds.
- tmalsburg2 11y agoMany chat bots display very human-like behaviour. Does that imply that the underlying technology will solve strong AI? Of course not. Such extrapolations are almost guaranteed to be incorrect. There have been some very eye opening articles recently about the limitations of deep neural networks which I highly recommend. AI is still an incredibly difficult problem and that is not going to change anytime soon. Deep neural networks are a decent step forward but we shouldn't get carried away.
- eli_gottlieb 11y ago> There have been some very eye opening articles recently about the limitations of deep neural networks which I highly recommend. I'm not exactly a deep-learning fan, but could you post the links?
- gambler 11y agohttp://www.evolvingai.org/fooling http://www.evolvingai.org/fooling
- eli_gottlieb 11y agoThank you. It's quite interesting, actually, how the easy-to-compute discriminative models can be fooled so easily, while they hypothesize that generative models (which are much more general, and closer to our best models of human cognition), despite being much slower, ultimately provide better performance at the boundaries of the classification region. I'd go on to venture that our minds probably use discriminative models for "intuitive" judgements, while reasoning that can explain the variance in percepts uses generative models, thus obtaining better performance where necessary despite using more energy. Or possibly, the generative models can be used to train the intuitive discriminative ones, slowly allowing the less intensive part of the mind's processing to adjust its class boundaries to suit what's really known.
- tmalsburg2 11y agoAlso http://rocknrollnerd.github.io/ml/2015/05/27/leopard-sofa.html http://rocknrollnerd.github.io/ml/2015/05/27/leopard-sofa.ht...
- fossuser 11y agoI'm starting to think that consciousness emerges out of a neural net that has the appropriate training tests, scoring functions and has the right sensors to take in feedback. For an easy example look at human babies - they're not conscious (maybe self-aware is a better word?), but we can see this development happen over time. Maybe sleeping has some role in recalculating the weights for the neural net? Eventually something like a feeling of self emerges as the evolved mechanism for working with social feedback. Maybe this is the general way intelligence works. It does seem to make sense when looking at how it develops in animals.
- gambler 11y agoThis is infinitely more impressive than Google's image generation. There are zillion ways to generate weird-looking images. However, this paper claims to: 1. Have trained a networks to generate handwriting. Handwriting can be objectively judged, unlike those images. The interactive demo does look pretty darn cool. 2. Made it so the network can be "primed" by small samples of new handwriting. This is the most impressive part, because it is something that actually qualifies as semi-generic AI. You train it on one thing and then it does another thing. Actually, the second part is bit too impressive, compared to everything I've seen from NNs before. I've read the paper, but I don't understand how this priming works. How big is the primer? Is it just the sample shown on the website? Are there any constraints? Can I simply supply a sample of my writing with a textual "translation" for this network to pick up some aspects of my writing style?
- sangnoir 11y ago> This is infinitely more impressive than Google's image generation. There are zillion ways to generate weird-looking images Google wasn't training their NNs to 'generate weird-looking images'. The NNs were for image-classification (which is pretty impressive), the weird images were just a visualisation/artefact of the training process.
- gambler 11y agoThey developed and tuned a fairly elaborate process designed specifically for generating those images out of classification NNs. The difference between the two demos is that the impressiveness of those images is mostly subjective, while handwriting replication has pretty well-established criteria to judge it by. Also, it sounds like priming is fast and does not require tons of samples.