Rapid advances in the development of ever-more-complex machine learning algorithms and an explosion in the use of machine learning to introduce AI into all walks of life is massively increasing demand for compute capacity and the energy required to power it. The need for low latency in real-time applications is exacerbating that trend. Currently, data centers are the fourth largest consumer of power behind only China, the US and the EU, while performance and power consumption remain significant hurdles to the adoption of machine learning at the edge. Growth is unsustainable using traditional software-only solutions.

Our vision is to produce machine learning inference solutions which meet these exacting demands using minimum compute capacity and minimum energy, thus advancing the vast potential of machine learning to enhance our lives without costing the planet.