FWIW- below post liked by Intel’s senior process engineer.
“As I have been reading several of my "go-to" tech publications I was struck by the sheer quantity of headlines about the incredible compute power of hardware built to run AI workloads such as training generative AI models in data centers. Yet a plethora of companies are waiting to get their hands on powerful AI chips that can handle complex computing at the edge while operating on small power supplies and requiring little or no dependency on cloud connectivity.
BrainChip and its remarkable team have met these challenging requirements. The company specializes in developing advanced artificial intelligence and machine learning hardware that leverages neuromorphic computing, a method of computer engineering where elements of a computer are modeled after systems in the human brain and nervous system. Brainchip’s technical staff developed a unique architecture and have become the world’s first commercial producer of ultra-low power, fully digital, event-based, neuromorphic AI IP, which they’ve dubbed Akida.
According to Brainchip, Akida can operate complex inference and learning on extremely low-power AI devices to deliver highly accurate, intelligent, responsive, real-time applications that provide enhanced reliability and security while connecting through a mesh network. Akida has the flexibility of integrating into SoCs that use existing process technologies and a developer platform that empowers partners to test and deploy their AI models using standard workflows.
Their robust offering has attracted the interest of leading companies like Teksun Inc, which focuses on end-to-end IoT and AI product development for applications where processing capability from “vision to decision” is crucial. For example, think of an industrial manufacturing environment where humans and machines are working together and physical safety, production efficiency, machine uptime, and data acquisition are all critical.”
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“As I have been reading several of my "go-to" tech publications I was struck by the sheer quantity of headlines about the incredible compute power of hardware built to run AI workloads such as training generative AI models in data centers. Yet a plethora of companies are waiting to get their hands on powerful AI chips that can handle complex computing at the edge while operating on small power supplies and requiring little or no dependency on cloud connectivity.
BrainChip and its remarkable team have met these challenging requirements. The company specializes in developing advanced artificial intelligence and machine learning hardware that leverages neuromorphic computing, a method of computer engineering where elements of a computer are modeled after systems in the human brain and nervous system. Brainchip’s technical staff developed a unique architecture and have become the world’s first commercial producer of ultra-low power, fully digital, event-based, neuromorphic AI IP, which they’ve dubbed Akida.
According to Brainchip, Akida can operate complex inference and learning on extremely low-power AI devices to deliver highly accurate, intelligent, responsive, real-time applications that provide enhanced reliability and security while connecting through a mesh network. Akida has the flexibility of integrating into SoCs that use existing process technologies and a developer platform that empowers partners to test and deploy their AI models using standard workflows.
Their robust offering has attracted the interest of leading companies like Teksun Inc, which focuses on end-to-end IoT and AI product development for applications where processing capability from “vision to decision” is crucial. For example, think of an industrial manufacturing environment where humans and machines are working together and physical safety, production efficiency, machine uptime, and data acquisition are all critical.”
Justin Kinsey on LinkedIn: #semiconductors #ai #machinelearning
As I have been reading several of my "go-to" tech publications I was struck by the sheer quantity of headlines about the incredible compute power of hardware…
/CNN/RNN
