Explore >> Select a destination
|
You are here 
|
blog.plover.com | ||
| | | | |
jaydaigle.net
|
|
| | | | | This week we continue our exploration of what numbers are, and where mathematicians keep finding weird ones. Last time we defined the real numbers, but it took a lot of work. Now we'll see how truly strange they are. They're so strange that it's tempting to avoid them and stick with something simpler. But the real numbers do a much better job of describing modeling the parts of the world we care about. Their weirdness is exactly what we need to guarantee that a bunch of | |
| | | | |
rjlipton.com
|
|
| | | | | How important is it to take sides in complexity? Barry Mazur has contributed to many areas of mathematics for many decades. His paper "Modular curves and the Eisenstein ideal" and related work furnished key ideas for Andrew Wiles' ultimately-successful strategy on Fermat's Last Theorem. Today Ken and I want to discuss how well we guess.... | |
| | | | |
scottaaronson.blog
|
|
| | | | | In Michael Sipser's Introduction to the Theory of Computation textbook, he has one Platonically perfect homework exercise, so perfect that I can reconstruct it from memory despite not having opened the book for over a decade. It goes like this: Let f:{0,1}*?{0,1} be the constant 1 function if God exists, or the constant 0 function... | |
| | | | |
blog.fastforwardlabs.com
|
|
| | | Research in machine learning has seen some of the biggest and brightest minds of our time - and copious amounts of funding - funneled into the pursuit of better, safer, and more generalizable algorithms. As the field grows, there is vigorous debate around the direction that growth should take (for a less biased take, see here). This week, I give some background on the major algorithm types being researched, help frame aspects of the ongoing debate, and ultimately conclude that there is no single direction to build toward - but that through collaboration, we'll see advances on all fronts. | ||
