Deep image prior 'learns' on just one image • Hacker News Board

Re: Deep image prior 'learns' on just one image

#191

Post by ben_w » Fri, Dec 01, 2017, 6:11 PM UTC

mjburgess wrote: post #135

ben_w wrote: post #132

Earlier quoted context omitted.

> Line up all the things in the universe that are intelligent. They are all conscious. The words “intelligent” and “conscious” are not sufficiently well defined to make that claim. By “intelligence”, do you mean: 1) “the ability to learn or understand or deal with new or trying situations”? Even current AI can do that. 2) “the ability to apply knowledge to manipulate one’s environment”? That’s another rabbit hole its…

> Even current AI can do that. No it can't. A machine's output is not deterministic from its input and can be sensitive to conditions not anticipated at-programming-time. That isn't understanding. A spinning top may spin on many surfaces not anticipated by the designer and acquire all sorts of interesting behaviors by doing so. "The opposite of consciousness" is not a meaningful criterion of interest. I'm not even su…

> "The opposite of consciousness" is not a meaningful criterion of interest. I'm not even sure it's a meaningful term.

Then let me rephrase: The state that you are in when you are not asleep nor anesthetised nor in a coma. (I’m assuming you wrote consciousness rather than unconsciousness as an autocomplete typo not as a misreading, I’m having to edit a lot of comments for that reason today).

(Also, strange example with fire and rocks, given there is one axis on which fire does rise for the opposite cause of rocks falling: buoyancy)

> Many of these tests you're outlining arent relevant to the question "does this robot have what we are interested in"

I listed them because it was not clear what you are interested in when you say “intelligence”. You have improved one step by saying “understanding”, but that has nine meanings lf its own, half of which point back to “intelligence” without adding anything useful to my mental model of what you might be trying to describe.

Now, with regards to your dogs-vs.-spinning-tops comparison. I totally accept that spinning tops are not intelligent. I do not understand how you decided to fit spinning tops against definition 1. I believe dogs are intelligent. I cannot prove dogs are intelligent by definitions 2, 3, or 4, only by definition 1 — can you? Can you demonstrate that a dog has any of “thoughts, concepts, ideas, imagination”? Again, I believe they do, but I cannot prove any of those things and I am aware of both the risk of anthropomorphism and of dehumanising (ironic word in this context, but it fits) their minds.

Finally, why do you believe that neuro-biomechanical processes are fundamentally capable of things that silicon cannot do? What makes it special?

Re: Deep image prior 'learns' on just one image

#192

Post by machiaweliczny » Fri, Dec 01, 2017, 6:16 PM UTC

mjburgess wrote: post #151

asfdsfggtfd wrote: post #148

Earlier quoted context omitted.

Where do you think human consciousness comes from?

I think all consciousness (a feature of most animals) is a specific kind of neuro-bio-chemical process. To put it another way, to improve your focus I can give you Modafinil. To stabilize your mood lithium. To give you hallucinations, lsd. To distort your visual perception, ketamine. To make you more empathetic, trusting and less hostile: mdma. To speed up your thinking, cocaine. To make you aggressive, too much coca…

If it's purely physical process then it can be simulated. If it is process then it has some state. You can save state.

> The internet may one day hold very detailed descriptions of people's brains. These will sit like textbooks and tombs though, and not care/wish for/consider/want/desire/understanding anything.

Same would be if you saved state of biological world without running(simulating) it.

Re: Deep image prior 'learns' on just one image

#193

Post by ben_w » Fri, Dec 01, 2017, 6:35 PM UTC

mjburgess wrote: post #175

ConfucianNardin wrote: post #173

Earlier quoted context omitted.

No, the issue is with the very premise, then. It is not clear that consciousness necessarily only emerges from a neurochemical process. What was basically said was "We do not know for certain that it is this neurochemical process that accounts for consciousness. Isn't it reasonable to suppose that we might encounter things that actually are conscious, but whose consciousness is not accounted for by the same property…

Scientific claims are not necessities. I'm not saying I can prove consciousness is a biological process only that its overwhelming reasonable to suppose so. Emergence is a result of causal interactions between parts of a system being different than the internal causal interaction within one part. It doesnt mean "complexity" and it really has nothing to do with a machine. The oscillating electric field acquires no new…

> Of all the known things in the universe which think, to remove their nerves is to destroy their capacity to think. I cannot see any reason to suppose thinking is not merely their activity.

You appear to be using circular reasoning. You assert that only biological-neuron entities are intelligent, use this assertion to create the set of intelligent entities, and then say that this is valid because to remove the neurons in those entities also removes their intelligence.

Indeed, it does — but then I get to assert that only silicon-logic-gate entities are intelligent, because their ability to process sensory inputs and translate this into signal outputs goes away when you remove their doped silicon wafers. It doesn’t help.

Re: Deep image prior 'learns' on just one image

#194

Post by machiaweliczny » Fri, Dec 01, 2017, 6:39 PM UTC

ConfucianNardin wrote: post #143

mjburgess wrote: post #135

Earlier quoted context omitted.

> Even current AI can do that. No it can't. A machine's output is not deterministic from its input and can be sensitive to conditions not anticipated at-programming-time. That isn't understanding. A spinning top may spin on many surfaces not anticipated by the designer and acquire all sorts of interesting behaviors by doing so. "The opposite of consciousness" is not a meaningful criterion of interest. I'm not even su…

> Even current ("real") intelligence can do that. No it can't. A biological creature's output is not deterministic from its input and can be sensitive to conditions not anticipated at-programming-time. That isn't understanding. A spinning top may spin on many surfaces not anticipated by the designer and acquire all sorts of interesting behaviors by doing so. [...] Many of these tests you're outlining aren't relevant…

> The dog experiences illusions of thoughts, concepts, ideas, imagination (and many other things besides) that are about its environment. Those have been caused by the nature of its environment. The spinning top topples towards its final point as-if it understood, just like the dog.

I think it's the same case with humans. We wouldn't differ from monkeys without ability to store information and imagination/abstraction(I think animals might posses those as well). Biologically-wise we are striving for same goals just in different environment(influenced/created) by us and more means(posibble acions).

Re: Deep image prior 'learns' on just one image

#195

Post by jonmc12 » Fri, Dec 01, 2017, 6:46 PM UTC

cs702 wrote: post #21

Wow: "In this work, we show that, contrary to expectations, a great deal of image statistics are captured by the structure of a convolutional image generator rather than by any learned capability. This is particularly true for the statistics required to solve various image restoration problems, where the image prior is required to integrate information lost in the degradation processes. To show this, we apply untrain…

> PS. This makes me wonder whether and to what degree the structure of the brain's connectome might be a necessary prior for AGI.

I've seen an analogy in hardware that is potentially interesting to explore.

There is a technique in A/D converters (ADC) where input signal noise can be reduced by RMS averaging the sequence of digital outputs. This increases the effective resolution of the ADC, while lowering the effective sampling frequency of the input signal.

In the case that the input noise of a precision ADC is very low, the digital averaging has no effect on effective resolution. Surprisingly, in this case you can actually inject a "hand-crafted" noise source into the input, and still realize the resolution improvements from digital averaging. The key is to find the right amount of noise to randomize the quantization noise.

In the case of the ADC, the structure of the quantizing hardware is known, as is the characteristics of quantization noise. This allows for a guassian noise to be injected with the input source (might be analogous to a "prior"). From there, one can balance the input injection noise with the output digital averaging to get an optimal increase in output resolution.

This technique is explained well in this paper: http://www.analog.com/en/analog-dialogue/articles/adc-input-...

Re: Deep image prior 'learns' on just one image

#196

Post by machiaweliczny » Fri, Dec 01, 2017, 6:47 PM UTC

mjburgess wrote: post #155

ConfucianNardin wrote: post #143

Earlier quoted context omitted.

> Even current ("real") intelligence can do that. No it can't. A biological creature's output is not deterministic from its input and can be sensitive to conditions not anticipated at-programming-time. That isn't understanding. A spinning top may spin on many surfaces not anticipated by the designer and acquire all sorts of interesting behaviors by doing so. [...] Many of these tests you're outlining aren't relevant…

What you've done here is expose an epistemological problem but not the ontological one under consideration. My ontological premises are: consciousness exists and it is a neurochemical process. From this follows: machines which are not instances of this process are not conscious. Now you have basically said: but we do not know for certain that it is this neurobiochemical process that accounts for consciousness. Isnt i…

> The distinction between a chisel and cocaine is hopefully clear enough: they act on their target objects in extremely different ways.

No. Both change target state. And when "running"(spinning, living) will act differently.

Re: Deep image prior 'learns' on just one image

#197

Post by machiaweliczny » Fri, Dec 01, 2017, 7:18 PM UTC

Isn't it simply hardcore overfitting of network?

I haven't read the paper yet but it seems to me that it shows you can use overfitting for output interpolation with great results.

Same should be possibile for example for interpolation of video images instead od pixels.

Re: Deep image prior 'learns' on just one image

#198

Post by toblender » Fri, Dec 01, 2017, 7:44 PM UTC

flyingspork wrote: post #33

JumpCrisscross wrote: post #24

Can someone break this down for this layman?

Not an expert so take this with a grain of salt; I could be misinterpreting the paper. It seems that the current accepted method is to train a network with distorted images as the input and the correct undistorted images as the targets. Then after training you can feed a new distorted image into the trained network and get the estimated "fixed" image. However this team actually uses the distorted image as both the in…

Wow thanks for the explanation, I would they would just use what you wrote for the abstract.

At first, I thought the machine learning algorithm was able to just bridge the gap in images from nothing...

CSI time: Enhance ... enhance... enhance!

Re: Deep image prior 'learns' on just one image

#199

Post by anchpop » Fri, Dec 01, 2017, 7:44 PM UTC

thefalcon wrote: post #189

theoh wrote: post #36

Earlier quoted context omitted.

Truly, an occasion for this koan: Sussman attains enlightenment In the days when Sussman was a novice, Minsky once came to him as he sat hacking at the PDP-6. “What are you doing?”, asked Minsky. “I am training a randomly wired neural net to play Tic-Tac-Toe” Sussman replied. “Why is the net wired randomly?”, asked Minsky. “I do not want it to have any preconceptions of how to play”, Sussman said. Minsky then shut hi…

Okay, I admit it, I'm not enlightened. Will somebody please Explain Like I'm 5?

Initializing a neural net with random weights =/= making a neural net with no preconceptions on how to play. It still has those preconceptions, you just don't know what they are.

Closing your eyes so you can't see the contents of a room =/= the room is empty. Not knowing what something is, is different from it not existing

Re: Deep image prior 'learns' on just one image

#200

Post by mjburgess » Fri, Dec 01, 2017, 9:00 PM UTC

ben_w wrote: post #193

mjburgess wrote: post #175

Earlier quoted context omitted.

Scientific claims are not necessities. I'm not saying I can prove consciousness is a biological process only that its overwhelming reasonable to suppose so. Emergence is a result of causal interactions between parts of a system being different than the internal causal interaction within one part. It doesnt mean "complexity" and it really has nothing to do with a machine. The oscillating electric field acquires no new…

> Of all the known things in the universe which think, to remove their nerves is to destroy their capacity to think. I cannot see any reason to suppose thinking is not merely their activity. You appear to be using circular reasoning. You assert that only biological-neuron entities are intelligent, use this assertion to create the set of intelligent entities, and then say that this is valid because to remove the neuro…

It would be circular if it were an argument. I haven't made an argument for it only offered it as the start of our scientific investigation. All observations of brute fact, phrased as arguments, are circular -- because the universe goes unargued for and merely exists.

What I mean is this:

You and I are having a conversation about consciousness. To do this scientifically we're going to have to point out those things in the universe that we're talking about. (We cannot begin, as socrates thought, with definitions because we dont know them yet).

So I shall collect for you all the things we have been talking about when we have said "this is conscious!". And you do the same. And my claim is that everything in this group is in this group... because ... it has a nervous system.

That is a hypothesis. My view is that this hypothesis is true and extremely well-evidence. My view is further that the only thing you can add to this group without a nervous system is something of pure imagination -- a cartoon character.

This is possible for any group: I draw a golden rabbit speaking to a silver duck. There are no such things because ducks cannot be both alive and made of gold -- as a brute fact about our universe that at its base causal interactions only play out in that way.

To believe that an electrified piece of metal could ever belong in the group of things united by their common feature "consciousness" is profound bizarre to me: what exactly is that thing meant to possess that I have?

Of what do I have when I am hungry and think of food that a piece of silicon may have? I dont know what that it, but it seems to throw away all known neuroscience to suppose it exists.

That is it not merely a cartoon fantasy, that really, the thing that makes me conscious is some peculiar abstract property of me that current running around a wire can also instance.

I have grave suspicions that neuroscientists will ever find that I possess this "structure", not least, because modifications to the way I think are easily done by insufflating cocaine (or whatever else). A drug which operates biochemically and yet modifies thought.

I'm not sure how a chemical modification to thought makes sense if the latter is an abstract property.