65% of Americans own smart devices at home. These include speakers, kitchen appliances, security systems, and lighting systems. In the past 5 years, the interest and the demand for TinyML has skyrocketed, as this Google Trends graph suggests.Each device must function efficiently, learn about usage patterns, and adapt to the household’s needs. Moreover, technology is shrinking in general. Computers that used to occupy whole rooms now occupy just a lap space. Smartphones are becoming smaller and thinner. But we must maintain quality, regardless of the size.TinyML is important because it allows us to perform the same advanced machine learning functions on smaller devices. The model is optimized to run on smaller devices that don’t have as much memory and computational power. An average TinyML model is just 18 KB, while the size of some regular neural networks can reach 0.8TB.