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Intel Scales Neuromorphic Research System to 100 Million Neurons Intel Newsroom


What's New: Today, Intel announced the readiness of Pohoiki Springs, its latest and most powerful neuromorphic research system providing the computational capacity of 100 million neurons. The cloud-based system will be made available to members of the Intel Neuromorphic Research Community (INRC), extending their neuromorphic work to solve larger, more complex problems. The system enables our research partners to explore ways to accelerate workloads that run slowly today on conventional architectures, including high-performance computing (HPC) systems." What It is: Pohoiki Springs is a data center rack-mounted system and is Intel's largest neuromorphic computing system developed to date. Loihi processors take inspiration from the human brain.

Neuromorphic engineering - Wikipedia


Neuromorphic engineering, also known as neuromorphic computing,[1][2][3] is a concept developed by Carver Mead,[4] in the late 1980s, describing the use of very-large-scale integration (VLSI) systems containing electronic analog circuits to mimic neuro-biological architectures present in the nervous system.[5] In recent times, the term neuromorphic has been used to describe analog, digital, mixed-mode analog/digital VLSI, and software systems that implement models of neural systems (for perception, motor control, or multisensory integration). The implementation of neuromorphic computing on the hardware level can be realized by oxide-based memristors,[6] spintronic memories,[7] threshold switches, and transistors.[8] A key aspect of neuromorphic engineering is understanding how the morphology of individual neurons, circuits, applications, and overall architectures creates desirable computations, affects how information is represented, influences robustness to damage, incorporates learning and development, adapts to local change (plasticity), and facilitates evolutionary change. Neuromorphic engineering is an interdisciplinary subject that takes inspiration from biology, physics, mathematics, computer science, and electronic engineering to design artificial neural systems, such as vision systems, head-eye systems, auditory processors, and autonomous robots, whose physical architecture and design principles are based on those of biological nervous systems.[9]

Neuromophic Computing


I saw a video article on Neuromorphic Computing the other day - something I had not really heard much about, though it ties in heavily to Artificial Intelligence which I, of course, do know about. Wow.. the possibilities are now endless. This is what Techopedia says about Neuromorphic Computing... Neuromorphic computing utilizes an engineering approach or method based on the activity of the biological brain. This type of approach can make technologies more versatile and adaptable, and promote more vibrant results than other types of traditional architectures, for instance, the von Neumann architecture that is so useful in traditional hardware design. Neuromorphic computing is also known as neuromorphic engineering.

EETimes - Intel Scales Neuromorphic Computer to 100 Million Neurons -


Intel has scaled up its neuromorphic computing system by integrating 768 of its Loihi chips into a 5 rack-unit system called Pohoiki Springs. This cloud-based system will be made available to Intel's Neuromorphic Research Community (INRC) to enable research and development of larger and more complex neuromorphic algorithms. Pohoiki Springs contains the equivalent of 100 million neurons, about the same number as in the brain of a small mammal such as a mole rat or a hamster. Neuromorphic Chip Intel debuted its Loihi neuromorphic chip for research applications in 2017. It mimics the architecture of the brain, using electrical pulses known as spikes, whose timing modulates the strength of the connections between neurons.

Why neuromorphic technology is the key to future AI


The idea is to develop microprocessors configured more like human brains than traditional silicon chips with the aim of making computers more astute about the environment; this is seen as step-forwards with artificial intelligence. Neuroinformatics refers to the creation of neuromorphic chips that can replicate the brain's information processing capabilities in real-time. Key players in the development of neuromoprhic computing are Qualcomm, IBM, HRL Laboratories and the Human Brain Project. The Human Brain Project is a 10-year project seeking to simulate a complete human brain in a supercomputer using biological data. With the commercial developments, a neuromorphic chip made by IBM contains five times as many transistors as a standard Intel processor, Wired reports, yet it consumes only 70 milliwatts of power.