aidanrocke

11 ms·

61.
Elon Musk's Documentary Gets a Whole Lot Wrong About AI Risks(skynettoday.com)
2 points by aidanrocke 8y ago|0 comments
62.
Structured Variational Auto-Encoder code(github.com)
3 points by aidanrocke 8y ago|0 comments
63.
by aidanrocke 8y ago
For context, this occurred to me when I was trying to find a way to apply policy gradients to tic-tac-toe. I haven't compared it to the Gumbel-Softmax trick yet but empirically I can say that it works.
64.
A differentiable approximation to the max operator(paulispace.com)
3 points by aidanrocke 8y ago|1 comments
65.
The symmetries of Mandelbrot sets with integer exponents(keplerlounge.com)
2 points by aidanrocke 8y ago|0 comments
66.
Symmetries of Mandelbrot sets with integer exponents(math.stackexchange.com)
1 points by aidanrocke 8y ago|0 comments
67.
Controlling a unicycle with Policy Gradients(github.com)
1 points by aidanrocke 8y ago|0 comments
68.
Controlling a unicycle with Policy Gradients(paulispace.com)
2 points by aidanrocke 8y ago|0 comments
69.
by aidanrocke 8y ago
I'm generally interested in benchmarks and/or good tutorials on different methods for accumulating gradients in TensorFlow.
70.
Efficient and concise method for accumulating gradients in TensorFlow(stackoverflow.com)
1 points by aidanrocke 8y ago|1 comments
71.
by aidanrocke 8y ago
The following analysis grew out of a desire to address Elon Musk's ontological argument and the underlying Singularity hypothesis that is popular among AI researchers, AI engineers and the general public. In this essay I demonstrate th
72.
Elon Musk's ontological argument(github.com)
2 points by aidanrocke 8y ago|1 comments
73.
Elon Musk's ontological argument(aidanrocke.github.io)
3 points by aidanrocke 8y ago|0 comments
74.
Understanding the free energy principle(github.com)
1 points by aidanrocke 9y ago|0 comments
75.
Understanding the free energy principle(paulispace.com)
1 points by aidanrocke 9y ago|0 comments
76.
Is Causal Path Entropy an E=mc^2 for Intelligence?(paulispace.com)
2 points by aidanrocke 9y ago|0 comments
77.
Is Causal Path Entropy an E=mc^2 for Intelligence?(github.com)
2 points by aidanrocke 9y ago|0 comments
78.
Fractals with TensorFlow(paulispace.com)
2 points by aidanrocke 9y ago|0 comments
79.
Fractals with TensorFlow(github.com)
3 points by aidanrocke 9y ago|0 comments
80.
Normal approximation to a uniform distribution(paulispace.com)
2 points by aidanrocke 9y ago|0 comments
81.
Laplace's Demon and the Singularity(paulispace.com)
1 points by aidanrocke 9y ago|0 comments
82.
TensorFlow returns a positive log-probability(stackoverflow.com)
3 points by aidanrocke 9y ago|0 comments
83.
Is a thermostat conscious?(romainbrette.fr)
1 points by aidanrocke 9y ago|0 comments
84.
What is the role of logic in mathematics?(paulispace.com)
2 points by aidanrocke 9y ago|0 comments
85.
by aidanrocke 9y ago
I appreciate your feedback. The paper I referenced by Josef Urban et al. is representative of the state-of-the-art. That said, this is a first draft and I will make a lot of changes. Adding more references on ATP being one of them. If you h
86.
The Immaculate Conception of Mathematics(paulispace.com)
1 points by aidanrocke 9y ago|0 comments
87.
by aidanrocke 9y ago
That's a very good point. I also think there's a difference between Automated Theorem Proving and AGI since entities with high-functioning general intelligence(i.e. AGI) aren't necessarily good at mathematics. ATP is a specif
88.
Learning to Think and Argue: a path to automated theorem proving(paulispace.com)
3 points by aidanrocke 9y ago|4 comments
89.
Challenge Problems for Artificial Intelligence (1996)(erichorvitz.com)
46 points by aidanrocke 9y ago|0 comments
90.
What do we learn about development from baby robots?(onlinelibrary.wiley.com)
2 points by aidanrocke 9y ago|0 comments

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