Billy Corgan is the Reason Courtney Love Married Kurt Cobain and changed music history

Sounds crazy but Courtney Love was dating her bandmate from Hole Eric but soon they broke up and stayed platonic. During that time in the early 90's Nirvana was getting to be huge but she was dating Billy Corgan of the Smashing Pumpkins. There was a show in Chicago where Corgan lived and Nirvana was playing and Courtney persuaded two music industry veterants one a Japanese man named Kaz to give her $1,000 each so she could make the trip to see Nirvana. What really happened was that she came to spy on Billy Corgan who had another girl at his home and kicked Courtney out.

What happened next is she ended up at the show and ended up on Kurts lap after the show and they were nearly inseperable ever since. This one night changed music history forever possibly... Had that girl not been at Corgans house would Courtney and Kurt ever fall in love? Would Kurt's addiction to Heroin and death be delayed? So many questions and what if's..

 

Find old Nirvana Interviews and more at this great time capsule of a websire recommended in the Goldberg Book Serving the Servant:

Note for when I want to find old Nirvana history: https://livenirvana.com/

Thrasio capitalizes on Amazon's Growth

 There are a thousand of ways to capitalize on the growth of the fastest growing platforms in the world. Facebook advertisers and developers profited as the social network grew, vendors who supply products to retail at Target benefit as they grow, I've benefited from the growth of Google and search, and now Thrasio is the type of website and business to benefit as Amazon retail grows by buying out merchants and taking over their companies and providing a fair earn out.

This is a story that we will see as online orders for products post pandemic continue to grow.

Thras.io says they are the fastest company to grow to a billion dollars.

Lenny Kravitz is an avid art collector

 At his Paris home he has some of the most beautiful art pieces from Andy Warhol & Jean-Michael Basquiat. Vogue did a nice piece and you can see the photos in one instagram slide here shared by our friends over at the Avant Gallery: https://www.instagram.com/p/CBxuhs1Bft1/

Andy Warhol Worked for a shoe manufacturer

 Before he became one of the worlds most famous artist's Andy Warhol was a shoe designer in New York. Born in Pittsburgh and migrated east to also work in the ad department of a magazine and as a designer for a shoe company. When he worked at these jobs he experimented with techniques that made him famous years later. 

For those who've been asking how you rank in Google

 After being asked about how you rank in Google there is a document you can send to those who are versed in mathematics. This documentation went beyond the traditional pointwise scoring functions and introduced a novel setting of group wise scoring functions (GSFs) in the learning-to-rank framework. 

The documentation implements GSFs using a deep neural network (DNN) that can efficiently handle large input spaces. If you read the link below you will see that GSFs can include several existing learning-to-rank models as special cases. They compared both  GSF models and tree-based models based on a standard learning-to-rank data set. Experimental results show that GSFs significantly benefit several state-of-the-art DNN and tree-based models, due to their ability to combine list wise loss and groupwise scoring functions. 

 The work compiled now opens up a few interesting future research directions: how to do inference with GSFs in a more principled way using techniques as well as helping readers, to define GSFs using more sophisticated DNN like CNN, rather than simple concatenation, and how to leverage the more advanced DNN matching techniques proposed in. 

Read more to understand:

https://storage.googleapis.com/pub-tools-public-publication-data/pdf/a995c37352b4b7d13923ca945cdcd03227c9023f.pdf

Success in Business is Mico Choices Over Time

 To be successful in business you need to take a deep look at outcomes and how they come about. Realizing that these outcomes are never the result of a single choice or action but many small actions built up over a long period of time.

Think about how the hedge fund Bridgewater was built by Ray Dalio argubulary one of the best funds of all time. As chronicled in Principals they cover how micro improvements and changes can add up to a big success over time. 

So remember when building a great company, life, or marriage that this is built up through many great micro choices over a period of time. Success is not a single choice based on one action but rather it is a series of actions over time.

If you enjoyed this advice follow my interview over at the Dotcom Magazine.

Why We're So Bad At Predictions

This piece from Nassim Taleb explains why we're so bad at predicting the pandemic and the outcomes of total deaths.

Source: https://forecasters.org/wp-content/uploads/Talebetal_25062020.pdf

MAIN STATEMENTS from the piece:

(i)– Forecasting single variables in fat-tailed domains is in violation of both common sense and probability theory. 

(ii)– Pandemics are extremely fat-tailed events, with potentially destructive tail risk. Any model ignoring this is necessarily flawed.

(iii)– Science is not about making single points predictions but about understanding properties (which can sometimesbe tested by single point estimates and predictions). 

(iv)– Sound risk management is concerned with extremes, tails and their full properties, and not with averages, the bulk of a distribution or naive estimates. 

(v)– Naive fortune-cookie evidentiary methods fail to work under both risk management and fat tails,because the absence of evidence can play a large role in the properties. 

(vi)– There are feedback mechanisms between forecast and reaction that cancels the invalidity of some predictions. 

(vii)– Exponential dynamics automatically satisfies the mathematical condition for chaos and its unpredictability

Other great data and information to help educate us and make us smarter while being more accountable you can read: https://forecasters.org/wp-content/uploads/Ioannidisetal25062020-1.pdf