## [Relevant AI Chip Startups](https://www.crunchbase.com/lists/relevant-ai-chip-startups/922b3cf5-b19d-4c28-9978-4e66ccb52337/organization.companies)

## [Survey of Machine Learning Accelerators](https://knowen-production.s3.amazonaws.com/uploads/attachment/file/5151/MLAccelerators_HPEC_2020_Reuther_CameraReady.pdf) Albert Reuther



![ss](https://knowen-production.s3.amazonaws.com/uploads/attachment/file/5156/performance%2B-power.PNG 'ss')

- [The Syntiant NDP101 chip hSyntianti [51], [52] is the neural decision processor inside the Amazon Alexa products for attention phrase recognition.](https://www.eetimes.com/tech-heavyweights-back-ai-chip-startup/#) It is a processor-inmemory design, which performs inference weight computations in int4 and activation computation in int8 and
consumes less than 200 µW.

- [The Mythic Intelligent Processing Unit accelerator hMythici [53], [54] combines a RISC-V control processor, router, and flash memory that uses variable resistors (i.e., analog circuitry) to compute matrix multiplies.](https://www.nextplatform.com/2018/08/23/a-mythic-approach-to-deep-learning-inference/) The accelerators are aiming for embedded, vision, and data center applications.


• [The Perceive Ergo processor hPerceivei [55] is meant for battery-powered applications that require high performance.](https://www.forbes.com/sites/tiriasresearch/2020/04/06/perceive-exits-stealth-with-super-efficient-machine-learning-chip-for-smarter-devices/?sh=1a5099c6d9c2) Ergo can run multiple concurrent networks
with over 100 million weights in applications such as simultaneous video and audio processing

## [AI 100: The Artificial Intelligence Startups Redefining Industries](https://www.cbinsights.com/research/report/artificial-intelligence-top-startups/?utm_source=CB+Insights+Newsletter&utm_campaign=2b526dcf3a-newsletter_general_Thurs_20210428&utm_medium=email&utm_term=0_9dc0513989-2b526dcf3a-91934989)

Graphcore, Syntiant, Lightmatter, Xanadu, Neron