The opening quote is probably from Richard Hamming, not Richard Feyman:<p><a href="https://news.ycombinator.com/item?id=2301089" rel="nofollow">https://news.ycombinator.com/item?id=2301089</a> (found through Google)<p><a href="https://www.cs.virginia.edu/~robins/YouAndYourResearch.html" rel="nofollow">https://www.cs.virginia.edu/~robins/YouAndYourResearch.html</a><p>Although maybe they knew each other and both gave the same advice ...<p>Actually that 2011 HN thread links to this paper, which attributes the same sentiment to Feynman, without an exact quote:<p><a href="https://people.tamu.edu/~huafei-yan//Rota/tenlesses.pdf" rel="nofollow">https://people.tamu.edu/~huafei-yan//Rota/tenlesses.pdf</a>
I like the paper idea - that paper and ink becomes an extension of our bodily selves (probably more priopeeception than some spiritual thing).<p>I mean I can remember and riff off a great paragraph in physical book, where the book is on the shelf, which page the writing is on, did I write next to it? But doing something like that on this iPhone - forget it, it is not "there" in any useful sense
For many years my "big question" has been "why do software engineering projects fail at a disproportionally higher rate than other engineering fields?"<p>Though I have to say the other engineering fields are not doing so hot lately either, so I might have the wrong question.
<i>> You have to keep a dozen of your favourite problems constantly present in your mind, although by and large they will lay in a dormant state. Every time you hear or read a new trick or result, test it against each of your twelve problems to see whether it helps.</i><p>Reminds me of similar patterns elsewhere. People keep "tabs" open on specific topics and add information over time.<p>- Mathematician Serge Lang kept correspondence and related documentation in extensive "files"<p>- Tony Fadell says you should keep coming back to ideas that you can't stop thinking about and add more insights over time
Great idea!
I think ten problem is too much for me, 2-5 is more suitable for me.
One of my problems is that, is big model the direction of Strong Artificia intelligence (Artificial general intelligence) ? text-to-picture and text-to-video task have a big upgrade in AI field, that seems main rely more data and bigger model, The explanatory seems don’t improve much.
my big question is:
what frequency (or should I say spectrum) is smell.<p>and more new from one man's prophecy that said that whole cities will get their energy from a device as small as matchbox... how can that huge energy come out even because ou need thick wires..