tinyML Summit 2022: 1 kB and not a bit more! The ideal weight for a tinyML model
tinyML Summit 2022
tinyML AutoML Session
1 kB and not a bit more! The ideal weight for a tinyML model
Blair NEWMAN, CTO, Neuton
Nowadays, we are witnessing how tiny smart devices increasingly expand capabilities and take over all domains of our lives. This generates a huge demand for automated tools that can support machine learning pipeline design and streamline the process of embedding ML models into the smallest apps.Our team has automated the best data science practices and created a unique no-code platform, Neuton. Thanks to a patented neural network algorithm under the hood, Neuton automatically creates machine learning models optimal in size and accuracy, eliminating the need for compression, quantization, and pruning.In our 10-minute tutorial, we’ll explain how Neuton enables embedded engineers to:
– automatically create compact ML models, up to 1,000x smaller than TensorFlow
– embed models into memory-constrained hardware, even with 8 and 16-bit precision
– perform tasks quickly and without any data science skills
We will demonstrate the capabilities of our platform and the tinyML approach by the case of determining food quality. You will learn the end-to-end process of creating a super tiny ML model, embedding it into an 8-bit sensor’s microcontroller, and monitoring the food quality based on the data from gas sensors.
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