Enhancing Human Capabilities with Valuable Edge Insights
With an ever growing amount of data being captured by devices all around us it is becoming extremely costly and inefficient to depend on the cloud for analytics and insights.
Edge machine learning is one of the most promising innovations of the last few years, enabling Al at the edge across a wide variety of use cases. With the market estimated to exceed an annual shipment of 2 billion devices by the end of 2022, the market opportunities are massive.
Wearable technology combined with edge machine learning is enabling companies to build devices to enhance human capabilities. One can now check key bodily metrics to make better health decisions and improve one’s quality of life. For instance, some devices monitor glucose levels, stress, fix circadian rhythms, and help regulate body temperature. Using edge machine learning, these wearable devices are bringing unique solutions to problems.
In this talk, Alessandro Grande, Head of Product at Edge Impulse, will explore the real market opportunities, and existing gaps before discussing the opportunities, providing recommendations, and sharing best practices to accelerate enterprise adoption of edge ML to enhance human lives.
About Alessandro Grande
Alessandro is a physicist, an engineer and a communicator with a visceral passion for empowering humans to build products that developers and enterprises love to use. Alessandro is the Head of Product at Edge Impulse and the co-organiser of the TinyML EMEA Forum, as well as the co-founder of the TinyML group in the UK and in Italy. Prior to Edge Impulse, Alessandro previously worked at Arm where he focussed on building technologies and ecosystems to help accelerate the adoption of Edge ML and IoT.
