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Siddhartha Gadgil
Works at Indian Institute of Science
Attended California Institute of Technology
Lives in Bangalore
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The Sports Gene by David Epstein
my review.
#SportsGene  

This is a brilliant book, concerning the nature vs nurture debate, or more accurately the "nurture only" vs "nature + nurture" question, in the context of sports. Unlike the case of two other recent books - Malcolm Gladwell's Outliers and Mathew Syed's Bounce (which are also very readable), the overwhelming conclusion is that high levels of skill are usually a combination of nature and nurture.  

This is neatly summarized in a chapter on `10,000 hours, give or take 10,000' - where the author looks at data from chess players from which the rule "that mastery comes from 10,000 hours of purposeful practice" was first advocated. While on an average it took these young players 10,000 hours, some needed a little over 2000 while others needed 10 times as much. And this  was from a pre-screened population.

The book is written in a spirit of enquiry (unlike Gladwell's and Syed's advocacy) and has many fascinating tales of the various aspects of nature and nurture that go into success (in sports), as well as surprising ways in which they interact. 

Somewhat surprisingly, the  conclusions from the role of talent (both genes and those environmental factors not in our control) is not fatalism but is both encouraging and practical. Firstly, as the chance that one has talent for some sport, or indeed some worthwhile activity in life, is naturally much higher that having talent for a specific sport, the obvious conclusion is to not overspecialize early, but try different things with an open mind to seek that for which you have a talent. I should add that fortunately many things like mathematics are naturally self-selecting - those without talent are unlikely to enjoy them (unless carried away by a romantic ideas of a field).  

Another positive and practical conclusion of the author, which as he points out Kenyan runners fortunately believe in, is that if you have a talent it is never too late to start - unlike the view from "nurture only", where one may conclude that it is too late to catch up on the nurture that others have.
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Scala is magic: apply+unapply replaces case class

My code uses a case class modelling the property that a function is positive:

case class FuncPositive(func : RealFunc, domain: Interval) extends ConstantTyp with Func

I needed to generalise this to bounds on functions. The brilliant abstract pattern matching in scala lets me replace this by:

case class FuncBound(func: RealFunc, domain: Interval, bound: Real, sign: Sign) extends ConstantTyp with Func with Bound

and

  object FuncPositive{
    def apply(func : RealFunc, domain: Interval) : ConstantTyp with Func = FuncBound(func, domain, 0 : Real, -1 : Sign)
    
    def unapply(typ: Typ): Option[(RealFunc, Interval)] = typ match {
      case fb @ FuncBound(func, domain, 0, -1) => Some((func, domain))
      case _ => None
    }
  }
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This is pretty useful for interaction with students.
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Very worrying. Would be more so if I was not on Linux.
Lenovo says that the Superfish adware it preinstalled on laptop computers isn't a security problem. That's not true. And guess what? It breaks Slack too.
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Theory in the age of heuristics

Heuristics algorithms - algorithms that work well but we do not know why or when, have come to dominate the world. What role does theory have in such a context? This was brilliantly answered in an afternoon of ICTS-Turing lectures a week ago here at IISc, Bangalore. The first of these, by Sanjeev Arora, was in part explicitly on this theme, with the other two fitting beautifully.

Sanjeev Arora started with a real, and important, problem - to learn to classify documents, say G+ posts, in an unsupervised way. This means that there are no hand-classified documents given, just the raw set of documents. As raw data is available in bucketfuls these days, unsupervised learning is very useful.

This problem is generally considered NP-hard (i.e., difficult). But the speaker pointed out that this merely means that we have drawn a circle around the original problem, and that circle contains hard problems. So we should look for a smaller circle containing the real problem - by making assumptions that hold in the real world. In various cases,  Sanjeev Arora as well as Ravi Kannan in a later talk, showed that we can make realistic assumptions and get fast algorithms.

The problem being real does not directly mean its solution is of use in the real world. But here there were examples from both Sanjeev Arora and Ravi Kannan of provable algorithms (for the problem with assumptions) being better in practice than the heuristic ones, and also examples where improvements in heuristic algorithms were inspired by the theoretical ones.

An afternoon of deeply impressive and inspiring talks. 
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Just trying to see if posting here is easier/harder than tweeting
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Also I found it difficult to search History in Google+ I have no idea about twitter though.
But i thought sharing links was more easier on G+
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Excellent piece in The New Yorker about Yitang Zhang and his groundbreaking work establishing that there is a bound on the gap between two consequent primes no matter how far along we are on the road to infinity.

Zhang's example shows that it's possible to do top level mathematical research outside of the academia. Good news for all of us, and... shame on you, academia!
Unable to get an academic position, Zhang kept the books for a Subway franchise. Credit Photograph by Peter Bohler
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Shinichi Mochizuki speaks to press, express anger over the slow progress in attempting to decipher his proof

It is now over 2 years since he published a  still unconfirmed proof of the ABC-conjecture which was thought  impenetrable hard to crack. The proof was base on years of work in a branch of mathematics  called 'inter-universal Teichmüller theory' that noone know or seems to understand. Following his steps and understand the proof is really difficult and would take years  of dedicated work in a field that may lead nowhere if the proof is wrong.

Up to now he has not been speaking to the press, but he has created a workshop where he will answer questions and help other mathematicians to understand it.

It is not that easy to explain what the ABC conjecture in a few lines, but more information can be found here:

https://plus.google.com/u/0/117663015413546257905/posts/Npu7xDniXMS
or
https://www.youtube.com/watch?v=RkBl7WKzzRw#t=346
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Have him in circles
906 people
Javaid Nizami's profile photo
Vienna Cars's profile photo
Jonathan Paprocki's profile photo
RiEKo IZaWa's profile photo
Matteo Bregol's profile photo
Hamilton Samraj's profile photo
Tim Sleppy's profile photo
Fransiskus Fallo's profile photo
Allen Sawyer's profile photo
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Mathematics (Low-dimensional topology), but trying to make computers make my job obsolete.
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  • Indian Institute of Science
    Professor, present
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  • California Institute of Technology
    Ph.D.(Mathematics)
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