## commercial companies

- [Intel dumps its Nervana neural network processors for Habana’s AI chips](https://siliconangle.com/2020/02/02/intel-dumps-nervana-neural-network-processors-habanas-ai-chips/)

[The First AI Chip Startup with Naveen Rao, Nervana System‪s‬ - FYI - For Your Innovation](https://podcasts.apple.com/gb/podcast/fyi-for-your-innovation/id1271691895?i=1000499936500)

- 2020 [**Apple buys edge-based AI startup Xnor.ai for a reported 200M**](https://techcrunch.com/2020/01/15/apple-buys-edge-based-ai-startup-xnor-ai-for-a-reported-200m/?guccounter=1&guce_referrer=aHR0cHM6Ly93d3cuZ29vZ2xlLmNvbS8&guce_referrer_sig=AQAAACQ2Pdxdyw0ekFeJaOYj2NJxsmksYYBVNHe0aMaWbOAPU0OzwbdW_NEKsFqvKr10qKgbpo5JiFkIZqRfwQ_3PSfbIPCYi4Oh_XcCslqeWKtMEde65htpixUV_iUQdHbCVzMGShDwMBOnjGsPAlZl2GL8fsEP4ZKpITAlS136B07-)

https://www.crunchbase.com/organization/xnor-ai

2020 [Exclusive: Apple acquires Xnor.ai, edge AI spin-out from Paul Allen’s AI2, for price in 200M range](https://www.geekwire.com/2020/exclusive-apple-acquires-xnor-ai-edge-ai-spin-paul-allens-ai2-price-200m-range/)

[Xnor’s saltine-sized, solar-powered AI hardware redefines the edge](https://techcrunch.com/2019/02/13/xnors-saltine-sized-solar-powered-ai-hardware-redefines-the-edge/?guccounter=1)

- https://groq.com/about/

> ...Google’s TPU effort as a 20% project where he designed and implemented the core elements of the original chip

- https://www.untether.ai/

In-memory computing with Flash.... 100m, but results???
https://en.wikipedia.org/wiki/Digital_signal_processor#Overview

- https://plumerai.com/



**BNN with microcontrollers**

podcast [Using Existing Edge Hardware for New AI Capabilities - with Roeland Nusselder of Plumera‪i‬](https://podcasts.apple.com/gb/podcast/ai-in-business/id670771965?i=1000492081227)

- https://landing.ai/


- NeuralMagic [The startup making deep learning possible without specialized hardware](https://s3.amazonaws.com/knowen-production/big_attachments/bde6e89c7c2f1a0a1b4e8fbc30d403ae/Untitled+42.pdf)

> It redesigned deep-learning algorithms to run more efficiently on a CPU by
> utilizing the chips’ large available memory and complex cores. While the approach loses the speed
> achieved through a GPU’s parallelization, it reportedly gains back about the same amount of time by
> eliminating the need to ferry data on and off the chip. The algorithms can run on CPUs “at GPU
> speeds,” the company says—but at a fraction of the cost.



- https://www.mythic-ai.com/, see in [more detail here](https://knowen.org/nodes/27246)


## NY Times articles

[Moore’s Law Running Out of Room, Tech Looks for a Successor](https://knowen-production.s3.amazonaws.com/uploads/attachment/file/5063/Moores%2BLaw%2BRunning%2BOut%2Bof%2BRoom%2BTech%2BLooks%2Bfor%2Ba%2BSuccessor%2B-%2BThe%2BNew%2BYork%2BTimes.pdf)

[Chips Off the Old Block: Computers Are Taking Design Cues From Human Brains](https://knowen-production.s3.amazonaws.com/uploads/attachment/file/5064/Chips%2BOff%2Bthe%2BOld%2BBlock%2BComputers%2BAre%2BTaking%2BDesign%2BCues%2BFrom%2BHuman%2BBrains%2B-%2BThe%2BNew%2BYork%2BTimes.pdf)

## conferences

https://aihardwaresummit.com/events/ai-hardware-summit-2021#prospectus

https://www.aihardwaresummit.com/events/edge-ai-summit-2021

https://www.kisacoresearch.com/sites/default/files/agendas/kr_tech_sponsorship_prospectus_-_public.pdf

http://isscc.org/