We held our next tinyML Talks webcast with two presentations: Rajen Bhatt from Qeexo has presented Qeexo’s Runtime-Free Architecture for Efficient Deployment of Neural Networks on Embedded Targets and Chandrasekar Vuppalapati from Hanumayamma Innovations and Technologies has presented Democratization of Artificial Intelligence (AI) to Small Scale Farmers - a framework to deploy AI Models to Tiny IoT Edges that operate in constrained environments on October 13, 2020 at 8:00 AM and 8:30 AM Pacific Time.
Rajen Bhatt (left) and Chandrasekar Vuppalapati (right)
Neural networks, including convolutional, feed-forward, recurrent, and convolutional-recurrent, are increasingly popular due to their recent successes in AI applications. Developing neural network models for tinyML applications can be very cumbersome due to constraints of embedded targets having low-power MCUs. Qeexo has developed a runtime-free architecture for efficiently converting TensorFlow-and-PyTorch-generated models to target libraries. This approach builds models which are orders of magnitude smaller than TensorFlow Lite Micro and does not compromise on latency or inference performance. The core of the architecture is made of two components: (1) Qeexo TensorFlow/PyTorch-to-C conversion utility (2) Qeexo Tensor Evaluation library. This talk will discuss the details of the architecture and its integration into Qeexo AutoML, an end-to-end tinyML development platform for sensor data. The talk will also cover Qeexo workflow for developing tinyML models and the comparison with TensorFlow Lite Micro on example ML applications built for the Arduino Nano 33 BLE Sense platform.
Rajen Bhatt is the Director of Engineering at Qeexo, leading a team of Machine Learning engineers to develop revolutionary ML platforms and products. His broad areas of expertise include machine learning, computational intelligence, computer vision, and product engineering. Dr. Bhatt has authored more than 35 peer-reviewed papers, a book on Pattern Classification Algorithms, and is the inventor/co-inventor of 20 granted patents in India, USA, and South Korea. Dr. Bhatt is an alumni of the Indian Institute of Technology Delhi, Senior Member of IEEE, a certified Product Engineering Leader, and has worked for Samsung and Bosch Research Centers in India, USA, and South Korea prior to joining Qeexo.
Big Data surrounds us. Every minute, our smartphone collects huge amounts of data from geolocations to the next clickable item on an ecommerce site. Data has become one of the most important commodities for individuals and companies. Nevertheless, this data revolution has not touched every economic sector, especially rural economies, e.g., small farmers have been largely passed over the data revolution, in the developing countries due to infrastructure and compute constrained environments. Not only isthis a huge missed opportunity for big data companies, it is one of the significant obstacles in the path towards sustainable food and a huge inhibitor closing economic disparities. The purpose of the talk is to present the TinyML framework to deploy artificial intelligence models in constrained compute environments that enable remote rural areas and small farmers to join the data revolution and start contribution to the digital economy and empowers the world through the data to create a sustainable food for our collective future.
Chandra Vuppalapati is a Software IT Executive with diverse experience in Software Technologies, Cloud Computing, and Product & Program Management. Chandra held engineering and leadership roles at GE Healthcare, Cisco Systems, St. Jude Medical ,and Lucent Technologies, a Bell Laboratories Company. Chandra teaches Software and Data Science for Masters program in San Jose State University and has published Building Enterprise IoT Applications book. Chandra graduated from San Jose State University Masters Program, specializing Software Engineering, and completed his Master of Business Administration from Santa Clara University, Santa Clara, California, USA.
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