Antifragile: Things That Gain from Disorder

By Chris Arney. 2013

856 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/0f5db40de6d3a05476a3247195a2fe5a0a4da23c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Quoc V. Le
2. Barret Zoph
3. Yoshua Bengio
4. Yi Tay
5. Percy Liang
6. Sergey Levine
7. Mohit Bansal
8. Irwan Bello

Citations in the corpus

• A post COVID-19 future - tourism re-imagined and re-enabled (2020, background): “Rather than articulate tourism’s purpose, which represents a higher-order calling (Sinek et al., 2017), the explicit desire was only to maximize arrivals, lengths-ofstay, and expenditures.”
• Designing Effective Sparse Expert Models (2022, background): “Taleb (2012) argues that certain systems exhibit the property of anti-fragility, where they improve through noise.”
• Unsolved Problems in ML Safety (2021, background): “Since change is a part of all complex systems, and since not everything can be anticipated during training, models will also need to adapt to an evolving world and improve from novel experiences [131, 196, 180].”
• ST-MoE: Designing Stable and Transferable Sparse Expert Models (2022, background): “Taleb (2012) argues that certain systems exhibit the property of anti-fragility, where they improve through noise.”