About Us
Intelligent solutions to real-world problems demand artificial intelligence at scale. At the heart of most AI technology is a Deep-Learning architecture which is computationally intensive. At Aarish Technologies Inc. (ATI), we have addressed the computational AI problem using a two-pronged approach. We offer a patented technology that reduces computation in most CNN by 70-90%. This is a huge savings considering the total computation cost of a typical CNN engine.
High Performance machine learning compute platform
We offer world’s leading technology solution to the challenge of high-performance machine learning compute platform, best in class industry performance.
High Performance machine learning compute platform
We offer world’s leading technology solution to the challenge of high-performance machine learning compute platform, best in class industry performance.
Ultra-low power on-the-edge devices
We offer the industry lowest-power solution for any given CNN architecture through our patented technology to reduce CNN computation costs. Greater than 90% computation improvements are seen in some well-known CNN architectures without compromising on performance.
Integrating with Industry standard machine learning design flow
Seamlessly integrates with any of the industry standard deep-learning platforms. Offers developers their choice of CNN development framework for training their CNNs.
Integrating with Industry standard machine learning design flow
Seamlessly integrates with any of the industry standard deep-learning platforms. Offers developers their choice of CNN development framework for training their CNNs.
Extremely low-cost silicon
Our patented processor technology coupled with our patented AI system technology; we offer greater system performance which provides industry with the lowest cost solutions to some of the most challenging computational problems.
Highly Scalable
Our patented solution is highly scalable both on and off chip. Its unprecedented flexibility allows multiple parallel CNN architectures to be simultaneously implemented, and multiple chips to be cascaded to scale up to a desired solution.
Highly Scalable
Our patent solution offers a highly scalable solution both on and off chip. It offers flexibility such that multiple parallel CNN architectures could be simultaneously implemented and multiple chips could be cascaded to scale up to a desired solution.
Integrated Design Environment
Easy to use IDE with edit, compile-and-debug features and integration of Deep learning framework for: PyTorch, TensorFlow, Caffe and Matlab.
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