For Data Scientists and ML Engineers
Perforated AI empowers data scientists to build smarter, smaller, and more accurate neural networks with less effort and cost. By incorporating artificial Dendrites into your neural networks, Perforated AI not only saves time and resources but also enhances model performance, making improving the impact each data scientist can make for their organizations.
A New Tool in your Toolbelt
Creating Neural Networks:
Unleash the power of Perforated AI to get the most out of your neural networks. Save countless hours on architecture design and parameter optimization, achieving next years results today.
Building More Efficient Architecture:
With Perforated AI, effortlessly build more efficient neural network architectures. Our advanced algorithms ensure your models are not only smaller but also more accurate, giving you the edge in performance.
Being the Heroes:
Become your team's hero with Perforated AI by delivering unparalleled accuracy and efficiency in your models. Become the hero of sales by providing smarter and smaller models to drive customer satisfaction and retention.
Perforated AI Use Cases
Our users and researchers have run successful experiments on all the architectures and data formats listed here. This list is ever expanding. We are confident that this algorithm Is compatible with anything built using PyTorch, as long as the right choices are made about how the system is integrated with the original.
Language Modeling - 89% Compression - 17% Reduced Error
Amino Acid Classification - 79% Compression
Image Classification on the Edge - 35% Compression - 6% Reduced Error
ICU Outcome Prediction - 91% Compression - 4% Reduced Error
Drug Discovery - 40.9% Reduced Error
Stock Forecasting - 35% Improved Precision
Parameter Efficient Fine Tuning - 16% Reduced Error
Image Segmentation - 35% improved DICE score
Our Patent Protected Algorithm
Perforated Backpropagation™ introduces a new artificial neuron inspired by modern insights in neuroscience research. The new neurons enhance your existing models with a extension to PyTorch installed via pip and integrated into your training pipelines with minutes of coding. By adding Artificial Dendrites that work alongside traditional neurons, our approach boosts data processing and learning efficiency without changing your network’s architecture. This means you can achieve significant compression and accuracy improvements on your next training run.
Ready to see how it works in detail? Check out a longer description or our paper.
