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I think things like computer vision would be more accurately labeled as "drawing conclusions" rather than "making predictions". And if you can get your predicti

by pnloyd 8y ago

I think things like computer vision would be more accurately labeled as "drawing conclusions" rather than "making predictions". And if you can get your prediction success rate close to 100% that seems more like drawing a conclusion as well.

sewercake 8y ago
hmm. This might just be a clarification of terms, but couldn't you say that 'predicting' something is merely a type of conclusion where the information used in the process of reasoning is incomplete or noisy? So all predictions are conclusions but not all conclusions are predictions. I.e, a deductive argument comes to a conclusion, but, as we know, inferential methods aren't deductive.
- jeffmcmahan 8y ago
  Humans are not predicting what a photo depicts when they look at it. They more or less immediately come to a definite conclusion.
  - pnloyd 8y ago
    Ya that's what I was basing my comment on mostly. I do understand your parents reasoning though, although it is comming from a more logical perspective than I was. I was commenting from the perspective of an analogy from personal experience of my own conscious.
  - deleted 8y ago
    [deleted]
  - sewercake 8y ago
    Some people disagree: https://www.quantamagazine.org/to-make-sense-of-the-present-brains-may-predict-the-future-20180710/ https://www.quantamagazine.org/to-make-sense-of-the-present-... This is a pop-sci article, so take it with a grain of salt, but there is a growing body of research that attempts to frame many cognitive processes as inherently predictive (inferential?). I think this view arises pretty naturally when you start thinking about us having a 'model' of reality that we is updated based on sensory information, but I digress. I think I see where you're coming from. A human might not be 'predicting', since the term has some kind of temporal element connotation. But we could say that it's 'inferring' what the photo represents?
  - venachescu 8y ago
    No, we are absolutely predicting when we are looking at a photo; firstly, we really do not see the ‘whole thing’, our eyes make quick, stereotyped (cough predictive cough) movements to a few spots on the image and mentally imagine the rest. Secondly, that’s assuming we recognized something in the image, if it’s unclear, like a grainy photo or lots of shadows, we start to make informed guesses about what could be there. All of our sensory systems work this way - we use an enormous amount of context to bubble up predictive categories and the collect marginal amounts of information until one prediction dominates over all others. When one doesn’t, we get gestalt like illusions; like the cubes that are projected both forwards or backwards - or dresses that are blue and black and white and gold - or laurel and yanni in perfect harmony, etc.
denimalpaca 8y ago
I would say it's making a prediction because to me the phrase "drawing conclusions" implies a conscious mental model of information from which a result is established. Making a prediction is not necessarily reliant on these mental models - especially conscious ones - it's about making an inference based on available information. Another way to put it is a person would look at a person and notice fur, eyes, paws, ears, and the specific shapes and colors of these things and conclude it's a cat. Take away a leg, or an ear, or have it half out of frame, and most likely a person would still recognize it as a cat. The idea of "cat" exists in the mind of the agent in this case, but a computer may predict cat only if the animal is fully in frame and not missing any parts. The machine is entirely reliant on features whereas a person is reliant on a mental model that has more elasticity in what it defines.
- dismantlethesun 8y ago
  Computers can and do label objects missing most of their features. This is especially important in computer vision work for cars, as inaccurately labeling an arm and a head as "not human" could lead to tragedy. Now, I am sure you know this, so I don't know why you chose to use an example that's inaccurate in practice.
  - denimalpaca 8y ago
    I chose this example because, in practice, sometimes changing a single feature does ruin the prediction, especially in computer vision. Often, the systems are somewhat resilient to these kinds of errors, but often not also. The fact that a computer can label an object missing many features does not imply that it cannot also make a mistake doing so. Like the Tesla that couldn't recognize a truck right in front of it. Then there's Google's Deep Dream, which did silly things like think that all hammers had arms attached to them. Then there's also this: http://www.evolvingai.org/fooling http://www.evolvingai.org/fooling and many other examples like it. I chose a simple example that would be maximally relatable and still accurate even with respect to state of the art algorithms and datasets with billions of samples.
robertk 8y ago
There exists some way to state this formally that shows these formulations are isomorphic, like a statistical Church-Turing thesis. Does a tree that falls alone in the forest make a sound? Potato, potatoe. shrug
- bordercases 8y ago
  Show me!
taneq 8y ago
Wouldn't you say that a conclusion is a prediction about the results of further investigations? Say you have a photo, and your image tagger says it's a photo of an apple. What that really means is "if I were to go to the place and time where this photo was taken, there would be an apple there in front of the camera".

by pnloyd 8y ago

sewercake 8y ago

hmm. This might just be a clarification of terms, but couldn't you say that 'predicting' something is merely a type of conclusion where the information used in the process of reasoning is incomplete or noisy? So all predictions are conclusions but not all conclusions are predictions. I.e, a deductive argument comes to a conclusion, but, as we know, inferential methods aren't deductive.

jeffmcmahan 8y ago
Humans are not predicting what a photo depicts when they look at it. They more or less immediately come to a definite conclusion.
- pnloyd 8y ago
  Ya that's what I was basing my comment on mostly. I do understand your parents reasoning though, although it is comming from a more logical perspective than I was. I was commenting from the perspective of an analogy from personal experience of my own conscious.
- deleted 8y ago
  [deleted]
- sewercake 8y ago
  Some people disagree: https://www.quantamagazine.org/to-make-sense-of-the-present-brains-may-predict-the-future-20180710/ https://www.quantamagazine.org/to-make-sense-of-the-present-... This is a pop-sci article, so take it with a grain of salt, but there is a growing body of research that attempts to frame many cognitive processes as inherently predictive (inferential?). I think this view arises pretty naturally when you start thinking about us having a 'model' of reality that we is updated based on sensory information, but I digress. I think I see where you're coming from. A human might not be 'predicting', since the term has some kind of temporal element connotation. But we could say that it's 'inferring' what the photo represents?
- venachescu 8y ago
  No, we are absolutely predicting when we are looking at a photo; firstly, we really do not see the ‘whole thing’, our eyes make quick, stereotyped (cough predictive cough) movements to a few spots on the image and mentally imagine the rest. Secondly, that’s assuming we recognized something in the image, if it’s unclear, like a grainy photo or lots of shadows, we start to make informed guesses about what could be there. All of our sensory systems work this way - we use an enormous amount of context to bubble up predictive categories and the collect marginal amounts of information until one prediction dominates over all others. When one doesn’t, we get gestalt like illusions; like the cubes that are projected both forwards or backwards - or dresses that are blue and black and white and gold - or laurel and yanni in perfect harmony, etc.

denimalpaca 8y ago

I would say it's making a prediction because to me the phrase "drawing conclusions" implies a conscious mental model of information from which a result is established. Making a prediction is not necessarily reliant on these mental models - especially conscious ones - it's about making an inference based on available information. Another way to put it is a person would look at a person and notice fur, eyes, paws, ears, and the specific shapes and colors of these things and conclude it's a cat. Take away a leg, or an ear, or have it half out of frame, and most likely a person would still recognize it as a cat. The idea of "cat" exists in the mind of the agent in this case, but a computer may predict cat only if the animal is fully in frame and not missing any parts. The machine is entirely reliant on features whereas a person is reliant on a mental model that has more elasticity in what it defines.

dismantlethesun 8y ago
Computers can and do label objects missing most of their features. This is especially important in computer vision work for cars, as inaccurately labeling an arm and a head as "not human" could lead to tragedy. Now, I am sure you know this, so I don't know why you chose to use an example that's inaccurate in practice.
- denimalpaca 8y ago
  I chose this example because, in practice, sometimes changing a single feature does ruin the prediction, especially in computer vision. Often, the systems are somewhat resilient to these kinds of errors, but often not also. The fact that a computer can label an object missing many features does not imply that it cannot also make a mistake doing so. Like the Tesla that couldn't recognize a truck right in front of it. Then there's Google's Deep Dream, which did silly things like think that all hammers had arms attached to them. Then there's also this: http://www.evolvingai.org/fooling http://www.evolvingai.org/fooling and many other examples like it. I chose a simple example that would be maximally relatable and still accurate even with respect to state of the art algorithms and datasets with billions of samples.

robertk 8y ago

There exists some way to state this formally that shows these formulations are isomorphic, like a statistical Church-Turing thesis. Does a tree that falls alone in the forest make a sound? Potato, potatoe. shrug

bordercases 8y ago
Show me!

taneq 8y ago

Wouldn't you say that a conclusion is a prediction about the results of further investigations? Say you have a photo, and your image tagger says it's a photo of an apple. What that really means is "if I were to go to the place and time where this photo was taken, there would be an apple there in front of the camera".