Laguna Hills, Calif. – April 5, 2022 – BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY), the world's first commercial producer of ultra-low power neuromorphic AI chips and IP, and SiFive, Inc., the founder and leader of RISC-V computing, have combined their respective technologies to offer chip designers optimized AI/ML compute at the edge. BrainChip's AkidaTM is a revolutionary advanced neural networking processor architecture that brings AI to the edge in a way that existing technologies are not capable, with high performance, ultra-low power, and on-chip learning. SiFive Intelligence solutions with their highly configurable multi-core, multi-cluster capable design, integrate software and hardware to accelerate AI/ML applications. The integration of BrainChip's Akida technology and SiFive's multi-core capable RISC-V processors will provide a highly efficient solution for integrated edge AI compute. SiFive Intelligence -based processors offer industry leading performance and efficiency for AI and ML workloads.

In brief An AI system has bested nearly 1,300 human competitors in the annual American Crossword Puzzle Tournament to achieve the top score. The computer, named Dr Fill, is the brainchild of computer scientist Matt Ginsberg, who designed its software to automatically fill out crosswords using a mixture of "good old-fashioned AI" and more modern machine-learning techniques, according to Slate. It was able to solve multiple word conundrums fast with fewer errors than its opponents. Dr Fill, however, was not eligible for the $3,000 cash prize, which instead went to the best human player, a man named Tyler Hinman, who presumably isn't feeling somewhat redundant. Ginsberg's machine contained a computer running a 64-core CPU and two GPUs, and was trained on tons of text scraped from Wikipedia to learn words, and a database of crossword clues and their answers to parse the competition questions.

Aerendir Mobile Inc. will merge its mathematical deep learning cores and AI infrastructure with innovative SiFive, Inc., RISC-V Core IP to enable a new low-cost board format for deep learning. This combined, unique approach will radically decrease the cost of true AI, allowing it to be enabled at the IoT Edge and End Point inside affordable devices. Aerendir and SiFive expect that the IoT market, bolstered by future 5G networks, will require the most cost-effective high-end distributed learning capabilities. As data collection continues to grow and outstrip the ability of datacenters to store, process and analyze new devices at the edge, end point can help to make accurate machine learning decisions. Local data analysis reduces network congestion and latency, improving local device performance and helping to send important data to the cloud for further analysis.

SANTA CLARA, Calif. and HSINCHU, Taiwan, Nov. 5, 2019 – GLOBALFOUNDRIES (GF) and SiFive, Inc. announced today at GLOBALFOUNDRIES Technology Conference (GTC) in Taiwan that they are working to extend high DRAM performance levels with High Bandwidth Memory (HBM2E) on GF's recently announced 12LP FinFET solution, with 2.5D packaging design services to enable fast time-to-market for Artificial Intelligence (AI) applications. In order to achieve the capacity and bandwidth for data-intensive AI training applications, system designers are challenged with squeezing more bandwidth into a smaller area while maintaining a reasonable power profile. SiFive's customizable high bandwidth memory interface on GF's 12LP platform and 12LP solution will enable easy integration of high bandwidth memory into a single System-on-Chip (SoC) solutions to deliver fast, power-efficient data processing for AI applications in the computing and wired infrastructure markets. As a part of the collaboration, designers will also have access to SiFive's RISC-V IP portfolio and DesignShare IP ecosystem, which will leverage GF's 12LP Design Technology Co-Optimization (DTCO), enabling them to significantly increase silicon specialization, improve design efficiency and deliver differentiated SoC solutions quickly and cost-effectively. "Extending SiFive's reference IP platform, with HBM2E, on GF's best-in-class performance 12LP solution delivers new levels of performance and integration for next generation SoCs and accelerators," said Mohit Gupta, vice president and general manager, IP Business Unit at SiFive.

The RISC-V instruction-set architecture, which started as a UC Berkeley project to improve energy efficiency, is gaining steam across the industry. The RISC-V Foundation's member roster gives an indication who is behind this effort. Members include Google, Nvidia, Qualcomm, Rambus, Samsung, NXP, Micron, IBM, GlobalFoundries, UltraSoC, Siemens, among many others. One of the key markets for this technology involves storage controllers with multiple companies, said Krste Asanovic, co-founder and chief architect at SiFive, and chairman of the RISC-V Foundation. He described it as integration with memory, along with a PCIe slave that plugs into the back of a server, to provide very high performance flash storage.