[P] Will Tsetlin machines reach state-of-the-art accuracy on CIFAR-10/CIFAR-100 anytime soon?

​

[A composite of specialized Tsetlin machines that enables plug-and-play collaboration.](https://preview.redd.it/0zsgtvzek0ob1.png?width=1194&format=png&auto=webp&s=8a4c6cbc939e84998f416065064ab003a3def8ed)

I have a love-and-hate relationship with CIFAR-10/100. I love the datasets for the challenge. On the other hand, they are two datasets where Tsetlin machines have struggled with getting state-of-the-art performance. (The Tsetlin machine is a low-energy logic-based alternative to deep learning that has done well on MNIST, Fashion-MNIST, CIFAR-2, and various NLP tasks.)

I have been working for some time now on figuring out a solution, and this …

accuracy art challenge cifar-10 datasets deep learning energy logic love low low-energy machine machinelearning machines mnist performance relationship state