➀ Innatera launched Pulsar, the world’s first neuromorphic microcontroller, using brain-inspired Spiking Neural Networks (SNNs) and combining a RISC-V CPU with hardware accelerators for mixed AI processing;

➁ The chip achieves ultra-low power consumption (e.g., 600 µW for radar-based detection) and reduces latency by 100x while enabling on-device sensor data processing for wearables, IoT, and automotive applications;

➂ Pulsar supports standalone intelligent sensor modules, eliminates cloud dependency, enhances data privacy, and allows on-device adaptive learning for edge systems.

➀ NY CREATES and Fraunhofer IPMS formalized a Joint Development Agreement (JDA) to co-develop advanced 300mm wafer-scale memory devices, focusing on ferroelectric memory technology using hafnium oxide (HfO₂);

➀ The collaboration aims to enhance energy-efficient, scalable memory solutions for neuromorphic computing applications, leveraging Fraunhofer IPMS's expertise in HfO₂-based memory and NY CREATES' Albany NanoTech Complex facilities;

➂ The partnership builds on prior agreements and aligns with U.S. initiatives like the CHIPS for America EUV Accelerator to strengthen semiconductor R&D leadership and economic growth.

➀ This study explores hexagonal boron nitride (h-BN) atomristors for their potential in energy-efficient neuromorphic computing;

➁ The researchers demonstrate the large memory window, low leakage current, and minimal power consumption of h-BN atomristors;

➂ The study highlights the potential of h-BN for high-performance applications in neuromorphic computing systems.

➀ IBM's researchers are inspired by the human brain to develop neuromorphic computing, aiming to mimic the brain's efficiency in processing vast amounts of data required for tasks like AI.

➁ The concept of neuromorphic computing involves designing a computing system that reflects the efficiency of the human brain, which consumes very little power and solves tasks effectively even with ambiguous or undefined data.

➂ IBM's NorthPole chip, an example of neuromorphic architecture, integrates memory and computation on the same chip to overcome the von Neumann bottleneck and reduce energy consumption.

➃ IBM's research teams are working on materials and algorithms to improve the performance and efficiency of neuromorphic chips, with the goal of creating more powerful and energy-efficient AI accelerators.