Tiny machine learning is broadly defined as a fast growing field of machine learning technologies and applications including hardware, algorithms and software capable of performing on-device sensor data analytics at extremely low power, typically in the mW range and below, and hence enabling a variety of always-on use-cases and targeting battery operated devices.
tinyML Talks: How to design a power frugal hardware for AI – the bio-inspiration path
September 23, 2021
tinyML Talks: An Introduction to TinyML for all backgrounds with hands on introduction to Edge Impulse
September 24, 2021
tinyML Talks: A Practical Guide to Neural Network Quantization
September 28, 2021
tinyML Vision Challenge
Create inspiring new applications using tinyML on computer vision and win prizes and recognition! The tinyML Vision Challenge has over $10,000 in prizes and is accepting contest submissions until August 20th.
Himax and tinyML Foundation share the same vision that tinyML technology can enable a new world with trillions of distributed intelligent devices that can accurately identify and classify what they see or sense in ultralow power and battery-powered features. To accelerate growth of the emerging tinyML field, the open knowledge exchange between developers and industries is of great importance. Hence, this tinyML Vision Challenge competition stimulates…
From cars and TVs to lightbulbs and doorbells. So many of the objects in everyday life have ‘smart’ functionality because the manufacturers have built chips into them.
But what if you could also run machine learning models in something as small as a golf ball dimple? That’s the reality that’s being enabled by TinyML…