ChatGPT for Hardware Design

e.g. most recently, I needed a boost converter with at least 300mA sustained I at 3.3V coming from the lowest V source possible (alkaline battery powered gadget) After an hour or so of searching I had to choose between TLV61220 and TPS61021A . Maybe there is a better third chip? At this point I ran out of time to research and just figured this the TPS61021A would do.

Digikey/Mouser/etc have parametric filtering (when it works), but optimization among three variables is not the strong suit there, especially when you have, say, an 8mm square to fill and cost is a factor (and availability/flexibility between footprints)

I would love to use this as a fair recommendation engine (that isn't sponsored by TI, skewing all results towards their products) where I can give it my circuit's minimum/recommended/maximum parameters and have it suggest applicable parts, or even take my finished designs and suggest cheaper alternatives for parts that match the design's footprints but have lower capabilities, if that's all my circuit needed in the first place.

(just threw my query into chatgpt and it suggested https://www.ti.com/product/TPS61221) not bad.

I thought ML needs huge datasets? This is great for GitHub's Copilot as there is plenty of high quality, production, open source code they've used without authorisation from the creators (and possibly proprietary code).

But this dataset just doesn't exist for hardware development on the internet. Almost everything on the net is hobbyist stuff. Great for hand building 10 on a desk but absolute rubbish for a (even horribly) manufacturable and COMPLIANT product.

Further: an anecdotal, but to me very telling, one liner from the video "the component is "not use for new designs" but we can ignore that because there's 260,000 of them". I have personally sniped larger quantities than that from digikey. "Not for new design" means you don't use it in a new design. PERIOD. And ironically, for something like a Murata cap, they've probably literally changed one letter in the PN because they've made a tiny process or recepie change and its more a "move everyone to the new iteration" process.

I do sincerely wish them success and maybe they can carved out a small bit of the hobbyist market but that's probably it.

It is becoming possible for AI systems to rapidly design hardware and software systems from the requirements of individuals who do not necessarily understand the subject matter.

I give tech 10 years before most of it is accomplished by AI and most people in tech will be forced out. Like DC elevators, some will remain, but not like it was.