According to RT, BRN will be located at booth 2-238 at the Embedded World 2023.
According to Embedded World's website, a company called AIZIP is in booth 2-238
AIZIP doesn't list BRN as partners but they do say they have new partnerships to be announced shortly.
Interestingly though AIZIP's link to their partnership with Renesas describes everything Akida does. (posted earlier
@VictorG)
Yep, got all that.
Just got my curiosity metre pinging when
@JK200SX said they were demonstrating Akida, which might not be quite right unless someone knows otherwise.
Aizip looks like an interesting startup, has a lot of very notable players following there progress.
Some of the people involved with Aizip include:
Yuan Lu
Yan Su
Yubei Chen
Weier Wan
Philip Wong
John Rea
Boltzmann Li
Taixiang Shi
Linked with Renesas
See video embedded in the link.
Saratoga, CA, July 29, 2021 – Aizip, Inc., a Silicon Valley startup company providing leading artificial intelligence (AI) models for the Internet of Things (IoT), the so-called tiny machine learning (TinyML), announced that it has reached an exclusive license agreement with Rice University for...
www.aizip.ai
Aizip Announces Processing-In-Memory License from Rice University
Saratoga, CA, July 29, 2021 – Aizip, Inc., a Silicon Valley startup company providing leading artificial intelligence (AI) models for the Internet of Things (IoT), the so-called TinyML, announced that it has reached an exclusive license agreement with Rice University for their Processing-In-Memory (PIM) technology.
Over the last decade, AI has proven to be of tremendous value in improving the quality of life on many fronts. One of the most critical areas in AI technology development is power efficiency. In the AI inference process in an existing chip, most of the power is wasted in the data transfer between memory and computing units. Analog computing inside the memory, i.e., PIM, is widely considered to be the ultimate solution to solve this challenge, especially in the IoT market where low power consumption and low chip costs are essential.
Assistant Professor Kaiyuan Yang, a recognized leader in PIM research at Rice University, had done pioneer research work which focuses on the design of PIM chips for low power and high throughput AI applications. In a paper recently published in IEEE Journal of Solid-State Circuits, Yang's group, in collaboration with Northeastern University, presented the results of the first PIM semiconductor chip fabricated with industry standard 6T-SRAM technology. At the core of their innovation is a cell cluster structure based on capacitive analog computing. The device has been fabricated and tested to show one of the smallest reported 0.35-LSB root-mean-square computing error, and superior area and energy efficiencies over other schemes being pursued worldwide.
"The successful demonstration of 6T-SRAM based PIM hardware is a major breakthrough in the path to ultra-low power and low-cost AI accelerators," noted Gene Frantz, a professor in the Practice at Rice University, a member of National Academy of Engineering, and fellow of IEEE. Frantz, who has been called the "father of digital signal processing," served as a Principle Fellow at Texas Instruments. "The work by Professor Yang and his team demonstrates that PIM can be realized in CMOS semiconductor technology with excellent performance and efficiency, showing considerable potential for its transition into commercial applications."
"We are very excited to work with Rice University to bring this innovation to the market," said Dr. Yuan Lu, co-founder and President of Aizip. Aizip believes PIM is a cornerstone in the future of AIoT, or TinyML, and "we have developed extensive IP in AI algorithms and architectures," according to Dr. Lu. He further stated that "the combination of Rice's IP in hardware and Aizip's IP in application and software will provide a complete solution in the fast-growing TinyML market." "I am glad to see the enthusiasm from industry on our research results and to see a path towards real world applications," remarked Professor Yang.
Many semiconductor companies have invested in PIM or have shown strong interest in PIM in recent years. The power consumption can be expected to reduce by 100x or more in IoT application, which should stimulate a new breed of applications, especially in battery-powered mobile scenarios. Aizip plans to work with IC partners to design and develop the next generation low power, analog PIM for AIoT applications.
Saratoga, CA, March 29, 2022 – Aizip, Inc., a Silicon Valley startup company providing leading artificial intelligence (AI) solutions for the Internet of Things (IoT), or the so-called tiny machine learning (TinyML), announced that its full-stack design services for Processing-In-Memory (PIM) AI...
www.aizip.ai
Cupertino, CA, August 30, 2022 – Aizip, Inc., a Silicon Valley startup company providing leading artificial intelligence (AI) solutions for the Internet of Things (IoT), congratulated its founding member Weier Wan for publishing his monumental research work on Processing-In-Memory AI chip in...
www.aizip.ai
Cupertino, CA, December 20, 2022 – Aizip, Inc., a technology leader in artificial intelligence (AI) for applications on the Internet of Things (IoT), also known as tiny machine learning (TinyML), announced today the volume shipping of robust vision models. Computer vision is one of the AI fields...
www.aizip.ai
I think Aizip is all about their PIM AI Chip tech
Any future partnership with Brainchip would obviously be very exciting, but can't see any current connection yet.
Apart from them sitting on each others lap in the booth at Embedded World