Thursday, September 6, 2018

"12 AI Hardware Startups Building New AI Chips"

This piece is a year old but I wanted it searchable on the blog for some stuff we have coming in the next couple months.

From Nanalyze, May 12, 2017:
In a recent article we talked about how NVIDIA (NASDAQ:NVDA) seems to be dominating “artificial intelligence (AI) hardware” with their GPUs. The only other major provider of GPUs, AMD (NASDAQ:AMD), doesn’t seem to be all that interested in aggressively marketing to an AI audience. In that same article, we also talked about how Intel (NASDAQ:INTC) and Microsoft (NASDAQ:MSFT) are placing bets on FPGAs as being the future of AI chips. With somewhere between 1,500 – 2,000 AI startups out there right now, there is plenty of opportunity for more than one winner especially when you consider how big the market for AI chips is expected to get.
After our recent analysis of AMD GPUs vs NVIDIA GPUs, we wanted to take an inventory of all AI hardware startups to keep an eye on. The last time we did this was about a year ago when we published an article on “5 Startups Building Artificial Intelligence Chips“. Since then, one of those startups, Nirvana, was acquired by Intel. Let’s see what’s been happening with the rest of them and also take a look at a few new names we came across.

12 AI Hardware Startups Building New AI Chips

Click to go to company websiteSince KnuEdge “emerged from stealth” last year, the company has gone quiet and not offered up any additional information about what they’ve been up to. According to an article in VentureBeat, we know that KnuEdge has already been generating revenue and that they were considering raising more funding this year in addition to the $100 million in “patient money” they have already raised. Their website contains next to no information aside from employee profiles. At an Xconomy conference a few weeks ago, the Company talked about “cloud-based machine intelligence as a service” that is “supposed to be rolled out sometime this year“. UPDATE: 7/30/2018 – Looks like that money will need to be really patient. KnuEdge may have gone bust, with speculation being raised that they couldn’t find any more money. You can read more about it in this May 2018 article by the San Diego Business Journal, and the fact that their website no longer functions leads us to believe that KnuEdge may have gone kaput.

Click to go to company websiteChinese startup Horizon Robotics joined forces with Intel to showcase an Advanced Driver Assistance System (ADAS) at CES 2017 which is a single camera that can see stuff and identify it. They also teamed up with Midea and launched an intelligent air conditioner that no doubt solves loads of first world problems including home security. No news yet on when we can expect their Brain Processing Unit (BPU) to debut but it was supposed to be “in early 2017“. The founder and CEO of Horizon Robotics, Dr. Kai YU, used to be the Head of Baidu Institute of Deep Learning so we’re expecting some great things from this startup which has taken in an undisclosed amount of funding so far.

Click to go to company websiteThis crowdfunding effort made its way into our original article on AI chips so it’s only fair we include it in this one. While it is not actually possible to pick a worse name for your startup than “krtkl”, at least the product name is manageable. Snickerdoodle is “reconfigurable hardware for building intelligent systems” (think Raspberry Pi). A crowdfunding effort for Snickerdoodle raised $224,876 and they’re currently shipping. If you pre-order one, they’ll deliver it by summer. The palm-sized unit uses the Zynq “System on Chip” (SoC) from Xilinix (NASDAQ:XLNX).

Click to go to company websiteEyeriss is a project being worked on by MIT which is an “energy-efficient reconfigurable accelerator for deep convolutional neural networks” and it remains a project still. As investors, we start showing interest once these cool ideas have been vetted by venture capitalists who then give their stamp of approval in the form of an investment. While the technology is getting favorable press mentions, we’re waiting to see if it actually makes it out of the lab and into the hands of some savvy business people who can then monetize it.

Click to go to company websiteFounded in 2016, Toronto-based startup Tenstorrent took in an undisclosed amount of seed funding this month to create “the next generation of high-performance processor ASICs, specifically engineered for deep learning and smart hardware“. Their team is made up of alumni from hardware industry leaders like NVIDIA and AMD. Not much else is known about this stealthy startup.

Click to go to company websiteFounded in 2016, San Francisco startup Cerebras has taken in $25 million from a single Series A funding round. Little is known about this stealthy hardware startup. Their website says they are “a stealth mode startup backed by premier venture capitalists and the industry’s most successful technologists“. They also like to work hard but still maintain a sense of humor. That’s about all we know right now.
Update 7/31/18: Cerebras has now taken in $112 million in funding. The latest round was a $60 million Series C which closed in January of 2017 giving Cerebras an $860 million valuation. While they remain in stealth, speculations are being made that their hardware will be made specifically for the training aspects of machine learning.

Click to go to company websiteFounded in 2012, Texas-based startup Mythic (formerly known as Isocline) has taken in $9.5 million in funding with Draper Fisher Jurvetson as the lead investor. Prior to receiving any funding, the startup has taken in $2.5 million in grants. Mythic is developing an AI chip that “puts desktop GPU compute capabilities and deep neural networks onto a button-sized chip – with 50x higher battery life and far more data processing capabilities than competitors“. Essentially, that means you can give voice control and computer vision to any device locally without needing cloud connectivity.
Update 7/31/18: Mythic recently took in $40 million from a funding round led by Softbank Ventures to improve the efficiency of their inference-focused AI chips to deliver almost GPU-like speeds. This brings the company’s total funding to $55.2 million.
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