Darwin Approves: Berkeley Evolves Analog Design

Digital design is hard. But in the right environment, digital circuits are more forgiving than analog. That 3.3V signal coming out of the chip has to drop a lot along the way to not be a logic level at the destination. If you are trying to push the boundary then digital design has much of analog design, but mostly you get a bit of a pass on many things that plague analog designers. Berkeley’s AI research group has been experimenting with using deep learning to evolve analog IC design.

Analog ICs are plagued with noise sources and often don’t have the margins that digital circuit designers enjoy. According to the post by [Kourosh Hakhamaneshi], designers often build a few blocks and attempt to lay them out in a way that should work and meet other requirements. Then they employ simulation, make changes as required, and simulate again. Accurate simulations can be very time intensive. You can read the actual paper, too, should you want to dig into the details.

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You Can Have My LM386s When You Pry Them From My Cold Dead Hands

Everyone has a chip-of-shame: it’s the part that you know is suboptimal but you keep using it anyway because it just works well enough. Maybe it’s not what you would put into a design that you’re building more than a couple of, but for a quick and dirty lashup, it’s just the ticket. For Hackaday’s [Adam Fabio], that chip is the TIP120 transistor. Truth be told, we have more than one chip of shame, but for audio amplification purposes, it’s the LM386.

The LM386 is an old design, and requires a few supporting passive components to get its best performance, but it’s fundamentally solid. It’s not noise-free and doesn’t run on 3.3 V, but if you can fit a 9 V battery into your project and you need to push a moderate amount of sound out of a speaker, we’ll show you how to get the job done with an LM386.

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