ENOT.ai
Alexander Goncharenko is an experienced technology leader currently serving as Chief Technology Officer at enot.ai since March 2022, responsible for framework design, algorithm selection, architectural verification, and user interface responsibilities. Prior to this role, Alexander worked as a Senior Deep Learning Researcher at Expasoft LLC from February 2017 to March 2022, focusing on neural network development, architecture compression, and the creation of custom algorithms for quantization and pruning, as well as participating in tensor processor development. Alexander's earlier experience includes a position as a Computer Vision Research Engineer at SoftLab-NSK from May 2014 to January 2017, where image processing algorithms for digital watermarking were developed. Alexander holds a PhD in Computer Science, a Master's degree in Software Development, and a Bachelor's degree in Nuclear Physics, all from Novosibirsk State University.
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ENOT.ai
ENOT.ai was founded by experts in computer vision solutions who've dedicated lifetimes to neural network advancements for diverse firms. Identifying inefficiencies in neural network pipelines, we innovated a technology to compress these networks without compromising accuracy. Enot.ai focuses on: Optimal neural network compression. User-friendly tools with easy installation and navigation. Universality in optimizing various neural networks, especially mainstream ones. Our ethos stands on: Innovation: Delivering cutting-edge AI. Customer-Centricity: Prioritizing tailored solutions and value. Sustainability: Pioneering green AI. Collaboration: Partnering for shared success. Integrity: Upholding transparency and trust. ENOT.ai offers two solutions: ENOT Lite Quick Acceleration: An ideal 'neural network accelerator' for those using PyTorch or Tensorflow on Intel CPU/Nvidia GPU. Achieve a performance boost of 2-8x*. Seamless Integration: Easily fits into your existing PyTorch/Tensorflow setup, facilitating accelerated AI application performance. Rapid Outcomes: Benefit from ENOT.ai's inference engine for instant acceleration with minor workflow adjustments. ENOT Pro Peak Efficiency: Provides leading neural network compression for tailored models, with a remarkable 4-20x compression rate*, enhancing AI workload efficiency. Deep Customization: Tailored for teams requiring in-depth adaptability, granting the precision to refine and optimize neural networks according to specific requirements. Performance Investment: Dedicate a week of developer engagement and experience the transformative efficiency and speed upgrade for your AI models. *Performance varies based on environment and neural network. Choose ENOT.ai for an efficient, accessible, and green AI future. Contacts: sales@enot.ai