Has this been put into practice in any AI to date?
Does TensorFlow count as a Gödel Machine? ML is basically the machine deciding its own weights right? Is that the same thing? Or have we not crossed into "writing its own code" territory?
And if we haven't, why not? This seems like the kind of thing we already have the technology for.
Meta-learning, where you also learn hyper-parameters (including potentially the architecture) are closer to that, see for example:
- Google Vizier: https://ai.google/research/pubs/pub46180
- Microsoft neural architecture search: https://github.com/Microsoft/nni
But this is still far from a true Godel machine.
0. https://arxiv.org/abs/1703.03400
Meta-learning is an active subfield of research in machine learning. Gödel machines may overlap with program synthesis as well which is another subfield.
> Does TensorFlow count as a Gödel Machine?
No. TF is itself is static and not self-improving. Most standard machine learning models are also not typically self-improving, though you can implement meta-learning with TF.
A big challenge with meta-learning is scale. It's relatively easy to solve multi-armed bandit problems but complex tasks are still challenging.