Of course, it is a riff on The Fortune at the Bottom of the Pyramid.
It was popularized by “CK”:
Coimbatore Krishna Rao Prahalad.
This post is created by “TR”:
Tayur Raghavendra Rao Sridhar.
Village-Name Father’s-Name Rao First-Name
is a fairly common naming structure among our Madhva community. (My father’s younger brother’s name is Prahalad.)
Sometime in 2006, when I was the CEO of SmartOps, I was in Chicago, meeting the CEO of a consulting company to evaluate partnership opportunities. After my meeting, I was invited to dinner at Charlie Trotter’s along with a small group of senior executives from Fortune 500 companies. I was to be picked up in a limo from my hotel, and was informed that I would be sharing the ride with CK, the guest speaker, who I had not met before. As I opened the door, and sat in the limo, CK exclaimed:
Sridhar! Nice to finally meet you.
Oh, you know who I am?
Of course. We are also related.
Your mother’s sister’s husband’s cousin’s daughter is married to my…
We had a good chat, switching back and forth between English and some Kannada, discussing family, business and life. It was fun. I am so happy that I got to spend the ride with him. His dinner speech was, likewise, quite enlightening. It was enjoyable to see his “charm” up close and personal.
Maximally Inverse to CK – who was non-mathy/Strategy University Professor at Michigan-Ross (I am a mathy/OM University Professor at CMU-Tepper) and hoped to eradicate poverty through commerce at the bottom of the pyramid – my first practical quantum computing project – in 2021, adapting Graver Augmented Multi-seed Algorithm (GAMA), that I previously mentioned in KaRmA – was with QuantBot – a $4.5 Billion Hedge Fund manager – that showed that they could increase their returns by 12% with lower risk (Sharpe Ratio up by 20%), as mentioned in (to appear in MBR, a start-up journal founded by the energetic Kalyan Singhal, co-authored with Mohan Sodhi):
Putting it indelicately, an alternate expansion of BLM can be:
Billionaire Lives Matter.😏
Obviously, I cannot resist:
The Wolf of Wall Street is a 2013 American biographical crime black comedy film directed by Martin Scorsese and written by Terence Winter, based on the 2007 memoir by Jordan Belfort. It recounts Belfort’s perspective on his career as a stockbroker in New York City and how his firm, Stratton Oakmont, engaged in rampant corruption and fraud on Wall Street, which ultimately led to his downfall. Leonardo DiCaprio, who was also a producer on the film, stars as Belfort, with Jonah Hill as his business partner and friend, Donnie Azoff, Margot Robbie as his wife, Naomi Lapaglia, and Kyle Chandler as FBI agent Patrick Denham, who tries to bring Belfort down. It was a major commercial success, grossing $392 million worldwide (on a budget of $100 million) during its theatrical run, becoming Scorsese’s highest-grossing film. The film received generally positive reviews from critics, along with some moral censure. It was nominated for several awards, including five at the 86th Academy Awards ceremony: Best Picture, Best Director, Best Adapted Screenplay, Best Actor (for DiCaprio) and Best Supporting Actor (for Hill).
From my previous post, you know I was at Cornell yesterday – hosted by (the very creative) Sid Banerjee (also IIT-Madras alum), who gave the best intro before my talk (tied with the amazing intro I received at Aspen Conference), comparing me with Leonardo DiCaprio using four movies as examples (Titanic, Aviator, The Wolf of Wall Street, Inception) and it was great to meet my students Vince and Nagesh, have dinner with David Shmoys, Jack Muckstadt and Shane Henderson, and catch up with (in addition to several PhD students) Tony Simione, Lynden Archer, Brenda Dietrich, Peter McMahon, Christina Yu, Mark Lewis, Nathan Kallus, Omar El Housni and Andreea Minca.
In addition to the Quantbot application, I presented the “Poor Man’s Ising Machine” (the winner of the 2020 Tayur Prize), as we are finalizing the invited paper (to a special issue of the Philosophical Transactions of the Royal Society, Series A):
Optimization with photonics wave based annealers.