The technical report FKI-126-90 introduced several concepts that are now widely used: (1) planning with recurrent NNs (RNNs) as world models, (2) high-dimensional reward signals (also as inputs for a neural controller), (3) deterministic policy gradients for RNNs, (4) artificial curiosity ...
The technical report FKI-126-90 introduced several concepts that are now widely used: (1) planning with recurrent NNs (RNNs) as world models, (2) high-dimensional reward signals (also as ...
Pronounce: You_again Shmidhoobuh @SchmidhuberAI In 2020, we are celebrating the 10-year anniversary of our publication [MLP1] in Neural Computation (2010) on deep multilayer perceptrons ...
Juergen Schmidhuber believes that this decade will witness proliferation of Active AI in industrial processes and machines and robots.
Building machines that can learn from examples, experience, or even from another machines at human level are the main goal of solving AI…
Historical Overview The long and now rapidly flowing Artificial Intelligence (AI) river which courses through the global technoscape has several
The distribution Q(jd) produced by the recognition weights is a factorial distribu- tion in each hidden layer because the recognition weights produce stochastic states of units within a ...
The inability of Deep Learning to perform compositional learning is one of the main reasons for NNs most critical limitations, including…
Myth 1: TensorFlow is a Tensor manipulation library Myth 2: Image datasets are representative of real images found in the wild Myth 3: Machine Learning researchers do not use the test set ...
The watershed moment in Deep Learning is typically cited as 2012’s AlexNet, by Alex Krizhevsky and Geoffrey Hinton, a state of the art GPU accelerated Deep Learning network that won that ...
document on 2018 turing award