Aspinity Blog
Tiny Machine Learning Happens in Analog
Join Aspinity at the upcoming tinyML Summit and learn more about the inner workings of an Aspinity analogML chip. Read more
Myth #5: AnalogML™ is just for machine learning applications
AnalogML™ is not just an ultra low-power analog neural network, but has other sophisticated analog processing functionality that together reduce power, size, and cost in always-on endpoints. Read more
Myth #4: CMOS Process Variations Make AnalogML™ Unpredictable
How does analogML™ overcome the repeatability challenges associated with analog process variation? Read our latest installment of our 5 Myths about AnalogMl™ series to find out. Read more
Myth #3: AnalogML™ extends battery life at the expense of wake word accuracy
How do newer, lower-power system architectures that rely on analog sound data to activate the WWE manage preroll to maintain wake word accuracy? They can't - EXCEPT for those using the analogML core. Read more
Myth #2: AnalogML™ replaces my favorite DSP/MCU
Read the second installment of our 5 Myths about AnalogML blog series, which addresses the most common misconceptions about the analogML core. Read more