TinyML Talks - The New Neuromorphic Analog Signal Processor Concept and Technology Platform

Explore the innovative Neuromorphic Analog Signal Processor (NASP) concept and technology platform in this tinyML talk. Dive into the world of neuromorphic computing and new architectures that mimic human brain systems, offering high accuracy and ultra-low power consumption. Learn about the NASP technology's major advances, including neural network operation in analog neuro cores with fixed weights and structures, and the T-compiler that transforms neural networks into analog representations. Discover how NASP chips aim to add intelligence to various sensors using artificial neurons and axons implemented with analog circuitry. Understand the hybrid core concept combining fixed neuromorphic analog cores for data pre-processing with flexible digital parts for final classification. Gain insights into applications such as Human Activity Recognition, Digital Fingerprint, and Narrow Voice, as well as design flow, business models, and partnerships in this emerging field.

Introduction
About tinyML
Core of technology
Physical layout
Design flow
Business model
Product line
Human Activity Recognition
Digital Fingerprint
Narrow Voice
Data Transfer
Partnership
Can you elaborate further on how the train neural network is converted to an AP
Can resistors representing weights be reprogrammed
Analog arrays vs gate arrays
Job opportunities
Typical number of neural network parameters
How is neural sense better than noise cancellation
Can neural net recognize music
Is the digital imprint application agnostic
Is there any correlation to neuromorphic processors
How can we use these models
What kind of tools can we use
Simulations
Direct sensor to spike converters
Publications
Mismatch
More questions
Precision
Conclusion
Strategic Partners