Neural Architecture Design
We came up with the breakethrough idea of new learning architecture that allows neural networks to get high accuracy in no time with less computation resources.
The future of AI training — coming soon.
Achieve 98+% accuracy for any dataset with less computations — powered by a new learning architecture.
Leaf is an API library that will allowed anyone to use a new powerful architecture for any dataset. It's perfect for dinamic tasks (where fast training and high accuracy are required) and large LLM models and very small datasets which is not big enought for classical Neural Networks' training (our archtecture will give high accuracy even with a small amount of data).
Rebuild how neural networks learn — faster, smarter, and more efficient.
Make advanced AI tools accessible to every creator and organization.
Smarter algorithms mean less power, less waste, and more impact.
We came up with the breakethrough idea of new learning architecture that allows neural networks to get high accuracy in no time with less computation resources.
We implemented the most important layers for Neural Network (e.g. CNN, RNN, Liner) using our new learning architecture with fresh view to date processing.
We made a class witch will create a custor Neural Network automatically specified for task and dataset.
Make time consuming computation in low-level programing language instead of Python.
Early access members get 1 month free API access after launch.
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