Machine Learning Street Talk (MLST)

#038 - Professor Kenneth Stanley - Why Greatness Cannot Be Planned

93 snips
Jan 20, 2021
Professor Kenneth Stanley, a research science manager at OpenAI and a key figure in neuroevolution, discusses his groundbreaking ideas on innovation and creativity. He argues that rigid objectives limit genuine progress and creativity, promoting a shift towards open-ended exploration instead. Stanley critiques conventional benchmarks and highlights how true breakthroughs often emerge from unplanned avenues. He explains the importance of fostering interestingness and autonomy in research, encouraging listeners to embrace uncertainty for greater achievements.
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ANECDOTE

ICML 2019 and Open-Endedness

  • Yannick Kilcher's ICML 2019 tutorial on open-endedness and POET inspired a YouTube video.
  • This sparked interest in AI-generating algorithms.
INSIGHT

Limitations of Genetic Algorithms

  • Current genetic algorithms lack divergence, a key aspect of real evolution.
  • They converge on local optima due to fixed objectives.
ANECDOTE

Machine Learning Stagnation

  • Mark Sarafim criticizes the "great stagnation" in machine learning, where researchers prioritize risk-free, incremental work.
  • He argues for more ambitious, risk-taking research.
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