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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.

Neuromorphic control for optic-flow-based landings of MAVs using the Loihi processor Artificial Intelligence

Neuromorphic processors like Loihi offer a promising alternative to conventional computing modules for endowing constrained systems like micro air vehicles (MAVs) with robust, efficient and autonomous skills such as take-off and landing, obstacle avoidance, and pursuit. However, a major challenge for using such processors on robotic platforms is the reality gap between simulation and the real world. In this study, we present for the very first time a fully embedded application of the Loihi neuromorphic chip prototype in a flying robot. A spiking neural network (SNN) was evolved to compute the thrust command based on the divergence of the ventral optic flow field to perform autonomous landing. Evolution was performed in a Python-based simulator using the PySNN library. The resulting network architecture consists of only 35 neurons distributed among 3 layers. Quantitative analysis between simulation and Loihi reveals a root-mean-square error of the thrust setpoint as low as 0.005 g, along with a 99.8% matching of the spike sequences in the hidden layer, and 99.7% in the output layer. The proposed approach successfully bridges the reality gap, offering important insights for future neuromorphic applications in robotics. Supplementary material is available at

Intel rolls out second-gen Loihi neuromorphic chip with big results in optimization problems


Loihi 2, pronounced "Low-EE-he," cuts in half the size of the chip and multiplies eight-fold the number of artificial spiking neurons. Here, the exterior of the chip is seen with its contacts to connect to the circuit board. Intel on Thursday unveiled the second version of its Loihi neuromorphic chip, "Loihi 2," a processor for artificial intelligence that it claims more aptly reflects the processes that occur in the human brain compared to other AI technology. The new chip is shrunk in half in a more-advanced process node, now measuring 31 square millimeters, yet it contains one million artificial spiking neurons, eight times as many as its predecessor. Loihi, pronounced "low-EE-he," is named for a Hawaiian sea mount, a young volcano, "that is emerging from the sea anytime now," as Mike Davies, Intel's director of neuromorphic computing, puts it.

Intel Debuts Pohoiki Beach, Its 8M Neuron Neuromorphic Development System


Neuromorphic computing has received less fanfare of late than quantum computing whose mystery has captured public attention and which seems to have generated more efforts (academic, government, and commercial) but whose payoff also seems more distant. Intel's introduction this week of Pohoiki Beach – an 8-million-neuron, neuromorphic system using 64 Loihi research chips – brings some (needed) attention back to neuromorphic technology. The newest system will be available to Intel's roughly 60 neuromorphic ecosystem partners and represents a significant scaling up of its development platform with more to come; Intel reportedly plans to introduce a 768-chip, 100-million-neuron system (Pohoiki Springs) near the end of 2019. "Researchers can now efficiently scale up novel neural-inspired algorithms – such as sparse coding, simultaneous localization and mapping (SLAM), and path planning – that can learn and adapt based on data inputs. Pohoiki Beach represents a major milestone in Intel's neuromorphic research, laying the foundation for Intel Labs to scale the architecture to 100 million neurons later this year," according to the official announcement.

Sandia: Brain-like neurochips chips useful in supercomputers


Neuromorphic chips that mimic the way brains work may have broad applicability for high-performance computing applications and could be a better fit than CPUs and GPUs in some cases, according to Sandia National Laboratories in the US. Neuromorphic computing represents a fundamental change in the way data is processed and analyzed. Up until now, artificial intelligence has been promoted as the main use case, although IBM, which was far ahead of the commercially viable brain-inspired game with its True North devices once saw much broader applicability. Intel, for instance, positions its Loihi neurochips as the future of AI computing but as Sandia researchers demonstrated in a recent article in the peer-reviewed journal Nature Electronics, Intel's Loihi chips "can solve more complex problems than those posed by artificial intelligence and may even earn a place in high-performance computing." This includes problems like tracking X-rays passing through bone and soft tissue, data flows within social networks, financial market movements and disease spread within a population, among other things.