miniF2F
Formal to Formal Mathematics Benchmark (by openai)
FL
FL language specification and reference implementations (by waveworks-ai)
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
miniF2F
Posts with mentions or reviews of miniF2F.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-02-11.
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[D] Have their been any attempts to create a programming language specifically for machine learning?
That said, you *can* write down a desired type and have a system write down a ton of type annotations or generate a bunch of code to prove that the type you wrote down is satisfied by your program. There's been recent work on this in deep learning for theorem proving, such as this work which uses GPT for proving theorems in Lean, a dependently type programming language and theorem prover. A better approach though would be to combine this with an actual tree search algorithm to allow a more structured search over the space of proofs, instead of trying to generate full correct proofs in one shot. Hypertree Proof Search does this, using a variant of AlphaZero to search and fine-tune the neural net. Unfortunately it hasn't been open-sourced though, and it's pretty compute intensive, so we can't use this for actual type inference yet. But yeah there's active interest in doing this kind of thing, both as a proving ground for using RL for reasoning tasks and from mathematicians for theorem-proving.
- [D] First Author Interview: AI & formal math (Formal Mathematics Statement Curriculum Learning)
- [D] OpenAI tackles Math - Formal Mathematics Statement Curriculum Learning (Paper Explained Video)
- MiniF2F
FL
Posts with mentions or reviews of FL.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-02-11.
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[D] Have their been any attempts to create a programming language specifically for machine learning?
I absolutely agree with the OP. Out of the same frustration I actually ended up designing my own language and wrote a compiler for it, and now I use it for all my ML modelling. It probably only solves my particular problems and I don't expect it to be very useful for anyone else, but here goes, in case anyone is curious: https://github.com/waveworks-ai/fl
What are some alternatives?
When comparing miniF2F and FL you can also consider the following projects:
tensor_annotations - Annotating tensor shapes using Python types
einops - Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
torchtyping - Type annotations and dynamic checking for a tensor's shape, dtype, names, etc.
dex-lang - Research language for array processing in the Haskell/ML family
jaxtyping - Type annotations and runtime checking for shape and dtype of JAX/NumPy/PyTorch/etc. arrays. https://docs.kidger.site/jaxtyping/
hasktorch - Tensors and neural networks in Haskell
MindsDB - The platform for customizing AI from enterprise data
tiny-cuda-nn - Lightning fast C++/CUDA neural network framework