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So good to play around with it, I asked bard.google.com a question that doesn’t have a lot written about it ..
“What is the quiescent power consumption of the Bristlemouth hardware”
AND it sounds coherent – however its “hallucinating” as not a google project. The 10milliwatts its quoting is the active transmission per Mhz.
I’ve got an open question to the designers .. (https://www.bristlemouth.org/ https://bristlemouth.discourse.group/t/what-is-the-expected-power-profile-and-quiescent-current/65)
<p data-sourcepos=”1:1-1:316″>The quiescent power consumption of the Bristlemouth hardware is 10 milliwatts (mW). This means that the hardware consumes very little power when it is not actively processing data. This makes it ideal for applications where power consumption is a critical factor, such as battery-powered devices or embedded systems.</p>
<p data-sourcepos=”3:1-3:270″>The Bristlemouth hardware is a neural network accelerator developed by Google AI. It is designed to be highly energy efficient, while still providing high performance. The quiescent power consumption of 10 mW is achieved through a number of design techniques, including:</p>
<li data-sourcepos=”5:1-5:29″>Using a low-power processor
<li data-sourcepos=”6:1-6:24″>Using low-power memory
<li data-sourcepos=”7:1-8:0″>Using a power-gating mechanism to turn off components when they are not in use
<p data-sourcepos=”9:1-9:220″>The Bristlemouth hardware is a significant improvement over previous generations of neural network accelerators in terms of power efficiency. This makes it a valuable tool for developing energy-efficient AI applications.</p>