At Visa GCC Connect 2025, bestselling author of The Black Swan and Antifragile, Nassim Nicholas Taleb, issued a stark warning: the real fragilities aren’t hidden, they’re in plain sight. From soaring Western debt to AI disrupting white-collar professions, Taleb argues that global power is shifting back to the East, with China and Africa on the rise. His advice: systems cannot be engineered top-down. True resilience comes from entrepreneurs, risk-takers, and bottom-up innovation. Speaking at Visa GCC Connect 2025, Milan, Italy.
Author: Admin
[X] Nassim Nicholas Taleb: Tutorial on n Trials With 1/n Probability

Link to Post on X – x.com/nntaleb/status/2046198980619505680
[X] Nassim Nicholas Taleb Releases Paper on the Lindy Effect
[X] Nassim Nicholas Taleb Says AI Is Reducing Wikipedia Traffic, Even in Stable Math Topics

Link to Post on X – x.com/nntaleb/status/2036156236140294255
[X] Nassim Nicholas Taleb on Aging, Memory Decline, and Filtering Information

Link to Post on X – x.com/nntaleb/status/2032861597413015670
Link to Nature article – nature.com/articles/d41586-026-00599-5
[X] Nassim Nicholas Taleb Says X Money Is “Much Smarter” Than Bitcoin

Link to Post on X – x.com/nntaleb/status/2031719331361427837
[X] Statistics for the Four Population Test
[Bloomberg] Nassim Taleb Warns About Software Bankruptcies, Volatility
Nassim Taleb, author of “The Black Swan” and distinguished scientist at Universa Investments, warns that markets are underpricing structural risks while overestimating the durability of recent AI leaders. Speaking with Bloomberg’s Natalia Kniazhevich, Taleb also weighs in on US tariff policy and the market impact of increasing tensions between Iran and the US.
[X] Hidden Optionalities and Risks in American Options

Link to Post on X – x.com/nntaleb/status/2021617572467368374
Link to Paper – arxiv.org/pdf/2602.14350
[X] Nassim Nicholas Taleb: Inequality Rises With the Expansion of the Sample Space
Link to Post on X – x.com/nntaleb/status/2015045285223838106
Links to Paper mentioned
On the Super-Additivity and Estimation Biases of Quantile Contributions – https://arxiv.org/pdf/1405.1791
Gini estimation under infinite variance – https://arxiv.org/pdf/1707.01370









