For my first tweet storm, I wanted to share a bit about the @sourcedtech open-source stack and how recent releases and announcements fit into the bigger picture.
In the coming years we believe #MLonCode will start to drastically change developer tooling in the following areas:
For #MLonCode to make an impact in these areas we believe the following ingredients are needed:
1. Large datasets of millions of repositories (thank you, @github)
To make this accessible to others, we released Public Git Archive:
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2. A language-agnostic representation of code
* Universal Abstract Syntax Trees
* Abstractions for high-level concepts (functions, imports etc.)
* Ability to resolve cross-references
Which is why we're working on Babelfish, check it out here: dashboard.bblf.sh
3. Ability to query the history of millions of repositories, their source code, and the language agnostic representations of it
8. And the most important: an #MLonCode community of ML researchers, PL enthusiasts, dev. tooling engineers, data engineers, dev. advocates, PM's, designers and many other profiles that believe in the future of a language-agnostic ML powered development experience.
We believe these are the fundamental components for building #MLonCode applications (and here we'll have some exciting announcements as well coming up later this summer).
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This release of FractalAI, shows a vastly more efficient and completely different way to do imagination based planning (deepmind.com/blog/agents-im…). Providing a highly efficient way to balance exploration of state space, of RAM or pixels, with exploitation.
The inspiration and foundation of this work couldn't have happened without @alexwg's paper on Causal Entropic Forces (alexwg.org/publications/P…)
FractalAI leverages the information contained in the entropy of any state space, together with any reward function.