Ferhat Erata

Ferhat Erata

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Ferhat Erata is an AI application developed by a Computer Science PhD graduate from Yale University. The application focuses on training transformers to solve NP-complete problems using reinforcement learning and improving test-time compute strategies for reasoning. It also explores learning randomized reductions and program properties for security, privacy, and side-channel resilience. Ferhat Erata is currently an Applied Scientist at the Automated Reasoning Group at AWS, working on Neuro-Symbolic AI to prevent factual errors caused by LLM hallucinations using mathematically sound Automated Reasoning checks.

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Features

Advantages

  • Cutting-edge AI research and development
  • Focus on security and privacy
  • Utilizes reinforcement learning for problem-solving
  • Mathematically sound reasoning checks
  • Experienced team of researchers and scientists

Disadvantages

  • Complexity may require advanced understanding
  • Limited accessibility to non-experts
  • Resource-intensive computations

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