algorithm fragility
[/ˈælɡərɪðəm frəˈdʒɪləti/]
nounpl: algorithm fragilities
fragilidade do algoritmo
1. The susceptibility of an algorithm to fail or produce incorrect results when exposed to unexpected inputs, edge cases, or changes in operating conditions
The algorithm fragility became apparent when the system crashed with unusual data formats.
A fragilidade do algoritmo ficou evidente quando o sistema travou com formatos de dados incomuns.
2. The tendency of an algorithmic system to degrade in performance or reliability due to small perturbations or variations in its input or environment
Researchers identified algorithm fragility in the machine learning model when tested with real-world data.
Os pesquisadores identificaram fragilidade do algoritmo no modelo de aprendizado de máquina quando testado com dados do mundo real.
3. A critical vulnerability in algorithm design that makes it vulnerable to failure under specific conditions not anticipated during development
The algorithm fragility issue required a complete redesign of the error-handling mechanisms.
O problema de fragilidade do algoritmo exigiu uma reformulação completa dos mecanismos de tratamento de erros.
This is technical terminology primarily used in software development, computer science, and artificial intelligence sectors in both Brazil and the USA. In Brazil, the term is increasingly common in tech startups and universities, particularly in São Paulo and Rio de Janeiro. In the USA and Portugal, it's standard terminology in academic and professional computing contexts. The concept has gained prominence with the rise of AI and machine learning applications, where robustness and reliability are critical concerns.
Related Idioms & Phrases
break under pressure (algorithm breaks under edge cases)
weak link in the chain (algorithm is the weak point in the system)
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