Authors: Lakshya A Agrawal, Shangyin Tan, Dilara Soylu, Noah Ziems, Rishi Khare, Krista Opsahl-Ong, Arnav Singhvi, Herumb Shandilya, Michael J Ryan, Meng Jiang, Christopher Potts, Koushik Sen, Alexandros G.
"the future of AI optimization may lie less in brute-force statistical methods and more in endowing our systems with the capacity for self-reflection. "
Counterpoint: Language allows sufficient dimensionality to escape local minimums when using inefficient but expansive search algorithms like genetic algorithms. If this is the case, it is revolutionary.
"the future of AI optimization may lie less in brute-force statistical methods and more in endowing our systems with the capacity for self-reflection. "
Counterpoint: Language allows sufficient dimensionality to escape local minimums when using inefficient but expansive search algorithms like genetic algorithms. If this is the case, it is revolutionary.
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