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Foundation Models: Strengths, Weaknesses, and Future Implications - Session 4

Foundation Models: Strengths, Weaknesses, and Future Implications - Session 4

Alan Turing Institute via YouTube Direct link

calibrated probabilities

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calibrated probabilities

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Classroom Contents

Foundation Models: Strengths, Weaknesses, and Future Implications - Session 4

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  1. 1 Introduction
  2. 2 What are foundation models
  3. 3 Are foundation models limitless
  4. 4 Knowledge of language
  5. 5 Linear scaling
  6. 6 Bullshit machines
  7. 7 Data choice
  8. 8 How to make them more sustainable
  9. 9 Concerns
  10. 10 Realistic
  11. 11 Should you want school
  12. 12 Black boxes
  13. 13 calibrated probabilities
  14. 14 conclusion

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