Sunday, December 13, 2020

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/

Monday, December 7, 2020

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. 

Sunday, November 22, 2020

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


Thursday, November 5, 2020

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.

Friday, October 9, 2020

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

Friday, October 2, 2020

The 5 Types of Inflation to examine for your business

COBI - Cost of Business Inflation COGI - Cost of Government Inflation COII - Cost of Investing Inflation COLI - Cost of Living Inflation

Friday, September 25, 2020

Richart Ruddie of Fort Lauderdale Florida Says this is 17.5x More Deadly than COVID-19

 




Cardiovascular diseases will be approximately 17.5 times more deadly than COVID-19. The big difference is that the ease in which you can catch COVID-19 and how rapidly it affects you and has the potential to activate other immunocompromised issues and kill you.

So it's not that COVID-19 is even nearly as deadly as other issues but it's more rapid. Only car accidents according to the chart above states that it's more deadly with little to no notice. So what do we do? Once COVID-19 is erradticated we should focus on curing cardiovascular diseases, cancers, and other lifestyle activities that cause these issues.

So don't be afraid because if you looked at the chart above you would think you're odds of dying are severly increased. Sometimes ignorance is bliss but make health conscious decisions to improve your lifestyle and logevity.
 
Official website