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[] Debugability
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Classroom Contents
The Myth of AI Breakthroughs - Cutting Through Hype in Neural Network Research
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- 1 [] Jonathan's preferred coffee
- 2 [] Takeaways
- 3 [] LM Avalanche Panel Surprise
- 4 [] Adjunct Professor of Law
- 5 [] Low facial recognition accuracy
- 6 [] Automated decision making human in the loop argument
- 7 [] Control vs. Outsourcing Concerns
- 8 [] perpetuallineup.org
- 9 [] Face Recognition Challenges
- 10 [] The lottery ticket hypothesis
- 11 [] Mosaic Role: Model Expertise
- 12 [] Expertise Integration in Training
- 13 [] SLURM opinions
- 14 [] GPU Affinity
- 15 [] Breakthroughs with QStar
- 16 [] Deciphering the noise advice
- 17 [] Real Conversations
- 18 [] How to cut through the noise
- 19 [] Research Iterations and Timelines
- 20 [] User Interests, Model Limits
- 21 [] Debugability
- 22 [] Wrap up
