MIPI C-PHY v1.2 D-PHY v2.1 TX 3 trios/4 Lanes in TSMC (16nm, N7, N5A)
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AI Inference IP. Ultra-low power, tiny, std CMOS. ~ 100K parameter RNN
Blumind's all analog AMPL™ neural signal processor IP for edge AI applications is designed on standard advanced node CMOS technology and can be integrated into high volume SoC and MCU products.
Ideal for always on voice detection, key word spotting. speech-to-intent commands (10), time series health or industrial sensor data etc.
Input from analog (or digital sensors) our IP has a fall-through neural network architecture that results in only active neuron consumming power.
Our NN core is tiny taking ~1mm2 and about 2x that area including analog preprocessing and 2 second audio buffer options.
Ideal for always on voice detection, key word spotting. speech-to-intent commands (10), time series health or industrial sensor data etc.
Input from analog (or digital sensors) our IP has a fall-through neural network architecture that results in only active neuron consumming power.
Our NN core is tiny taking ~1mm2 and about 2x that area including analog preprocessing and 2 second audio buffer options.
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