pakl

10 ms·

61.
by pakl 10y ago
In a sense, I would say yes there are learning laws, but it's still early in codifying them. Along one axis, you could compare: supervised, semi-supervised, self-supervised and unsupervised learning. Along another axis, consider that t
62.
by pakl 10y ago
If the goal is to have AI that is aware of the real world (even a chatbot), then using game state is a crutch that doesn't help us solve the real problem.
63.
by pakl 10y ago
That's a great (and hard) problem! More generally, imagine AI that could learn the physics of the world. For example, if the ball is rolling away, the AI should be able to predict that the ball will look smaller on the next frame. Goin
64.
by pakl 10y ago
I take the point to be that there aren't "deeper" fundamental principles at play in these models. Tremendous progress has comes from simply tweaking of the numbers of layers, or how the feed forward to each other (skipping l
65.
by pakl 10y ago
What you mention in point #1 isn't the main issue with games, but with the "reactive" approach in AI. Reactive AI systems are necessarily going to be more limited than say, predictive AI systems (a new emerging class of AI m
66.
by pakl 10y ago
Well, it seems taking a principled approach helps avoid the WTFs :) Please see my other comment for informative video links reviewing recent work by community collaborators.
67.
by pakl 10y ago
For some recent information (mid/late 2016) on applying linguistic methodology to the Voynich Manuscript, see this two part video. It's really great to see how much progress the community has made. https://youtube.com&#
68.
by pakl 10y ago
Just define consciousness, and then maybe we can start to have a scientific discussion about it. ;)
69.
by pakl 10y ago
To see some concrete examples of how this sort of phenomenon causes surprising failures in deep networks classifying images, see "Intriguing properties of neural networks"[1] [1] https://cs.nyu.edu/~zaremba/do
70.
by pakl 10y ago
Yes, but in direct contrast to Chomsky (who would say there's not enough data/time for kids to learn from) I am saying that there is a ton of rich dynamical data in the world around us all the time. Plenty to learn from. Just plug
71.
by pakl 10y ago
Exactly! Now consider that deep networks that classify images are tasked with getting reliable statistics in very high dimensional spaces. Conv nets are being forced to map from high dimensional spaces down to a very low dimensional catego
72.
by pakl 10y ago
I commend you. Very few people actually try feeding images into these things to show how bad they are. For a real shock at how poor performance is, try feeding frames of video in. (Video is different because it generally doesn't have
73.
by pakl 10y ago
> There are too many hard cases for vision. Even worse, most machine learning vision approaches make the vision problem much harder on themselves. They do not treat the visual world as the dynamic physical interacting processes that give
74.
by pakl 10y ago
Agreed -- If you get away from traditional feedforward networks by adding recurrence throughout, then at least there is some chance of learning scale-free features and compositionality.
75.
by pakl 10y ago
You've hit on a key insight. Predicting the future (even by a bit) turns out to be a very powerful learning signal for building models of the world. It won't work on a traditional feedforward neural network but if you have feedbac
76.
by pakl 10y ago
If one wants general AI that can deal with/understand the world, the system needs to learn based on (raw, unadulterated) data from the world. These data are highly dynamic and rarely fit neatly into human-labeled categories. This is p
77.
by pakl 10y ago
There are some promising ideas out there based on unsupervised ("self-supervised") learning. There, the problem of needing big labeled datasets doesn't exist: just turn on a camera and have a motor point it at the surrounding
78.
by pakl 10y ago
I'm optimistic about what'll happen right after the upcoming AI winter. :) So long as AI remains tasked with categorizing human-taken photos or playing human-created games (no matter how "complex"), AI will remain just t
79.
by pakl 15y ago
Interesting point about reverse-engineering the brain possibly succeeding first. The result of logical AI, however, is likely to be fundamentally different from the human brain or human mind. (Recall how difficult even simple logic is for