We significantly enhance processor efficiency by 'neuromorphic architecture', reducing data movement from the place where data is stored, effectively mimicking the brain architecture.
Pre-trained AI models are stored and executed directly on your device, enabling seamless and efficient computation without relying on external data transfer.
The team boasts diverse experience in memory, processor, and consumer and enterprise data center product, providing a complete hardware/software solutions to run your AI model from your devices.
As a founding member of the 4-bits/cell NAND flash memory controller team at Samsung Electronics, I delved into the challenges of flash memory reliability—a pivotal research topic.
A Flash-SRAM-ADC-Fused Plastic Computing-in-Memory Macro for Learning in Neural Networks in a Standard 14nm FinFET Process
ANAFLASH is sponsoring the upcoming TinyML Summit. We welcome AI suppliers, end-users, developers, and business leaders interested in on-device AI.