I gave a lightning talk at @PyData NYC giving a short intro to e-graphs as well as this example of compiling scikit-learn to numba https://t.co/nBEuPpxDuV
@SShanabrook@numba_jit@AesaraDevs We're in the process of moving some of our symbolic work from @AesaraDevs into the the LLM space, and we might end up using egglog and the new RVSDG support in @numba_jit to do that.
@SShanabrook@numba_jit@AesaraDevs The plan with @AesaraDevs was always to shed the tensor library elements and focus on building useful domain-specific relations using whatever frameworks are most effective. egglog and @numba_jit are shaping up to be those frameworks, and that's exciting!
In the end, I'm glad to have gotten the chance to implement and demonstrate some of the features I always wanted in a PPL, and I still hope to see one that realizes them all--even if it ends up being in Julia!
At some point I'll start putting out write-ups about some of the most interesting domain-specific rewrites and optimizations we added, and some details about the automated sampler construction process and its potential.
I'm glad that my adhoc transpilation approach was able to breathe new life into an old project like Theano, but tighter integration with better compilation targets are necessary.
Aesara was designed to fulfill a very specific backwards compatibility requirement that ultimately complicated its true goals: domain-specific symbolic rewriting. We're very proud of what we were able to accomplish under those constraints, but the way forward can't have them.
Regarding our original mission with @AesaraDevs, we believe that projects like @numba_jit, its push for RVSDG support, and projects like the ones by @SShanabrook are good ways forward in this space.
Simply put, the projects have gone through a lot in the past year and we've moved on to some exciting new ventures. We're bringing similar symbolic thinking and approaches to a new space: LLMs.
I just wrote a reply involving questions about @AesaraDevs, and it reminded me that we need to provide some updates regarding the projects: https://t.co/RO4U17mT4i
@AesaraDevs At this point, this is unsurprising and expected of all Python libraries that wish to be fast, and therefore is unsuitable as an April Fool’s prank.
@vboykis@remilouf If you need meta-programming, i.e. the ability to reason at runtime about your model and modify it. Aesara represents the model as a graph of mathematical operations. See https://t.co/ixUQbTSRYA for an example where it is used, and https://t.co/Y0DNKrfnH5 for ideas.
Then we'll implement a high-level DSL to simplify the construction of complex samplers with Blackjax, and use AeMCMC to automatically compile samplers thet are adapted to your model.
https://t.co/uilvUEfZUt