Embedded AI
nostarch.comHas anyone read this yet? I'm extremely skeptical of any book published after ~2024 just because of how much AI slop is in physical books these days.
Looks interesting, but I'd like to see some reviews on the content first before buying.
Bill Pollock (who is nonstarch press) is a very serious editor so I would not worry about that with NSP books.
Of course it’s a small operation, and so isn’t under the same pressures of a big operation. When you’re a boutique operation your only differentiation is quality. Your rule of thumb is unfortunately probably pretty good in the general case.
The editor is not the one producing the text. For this book, the sample chapter seems to make heavy use of LLM output. Pangram agrees. I guess that for books about AI it's fair game? Eat your own dog food so to speak. People who don't like AI are not the target audience.
> extremely skeptical of any book published after ~2024
The problem is with that 'any':
> Drawing on more than 30 years of embedded engineering experience, David Such takes you through the complete engineering process
Would David Such ruin his reputation after 30 years building it?
Few reputations remain unruined now.
kind of the expensive side.
honest question, how is it better than posting toc on chatgpt and asking it to explain it to you
> honest question, how is [reading a book] better than posting toc on chatgpt and asking it to explain it to you
Since you're currently asking humans to explain this to you and not LLMs, you've already got your answer.
Have you noticed, as part of the over-process you imply, that LLMs absorb knowledge but do not produce it?
Nice to see NSP cover this space. Curious if it goes into quantization for real hardware targets, or stays at the framework level.