• Home
  • Technology
  • Gaming
  • Entertainment
  • World & Business
  • Science
  • Sports
  • AI
HomeTechnologyGamingEntertainmentWorld & BusinessScienceSportsAI
AI
Announcement

Deep Learning Alchemy class pairs small language model experiments with prediction quizzes

A co-instructor says seven exams account for 85% of the grade, with in-person discussion assessments making up 15%.

Tatsunori HashimotoTH
1 Source, 1h ago, first seen 1h ago

TLDR

A co-instructor says Deep Learning Alchemy will have students experiment with small language models, then predict the effects of unseen code changes in quizzes. Students can use AI agents for assignments but must demonstrate mastery on exams without access to those assignments. The assignments and quizzes are public, and lecture recordings will be released later through Stanford Online.

Combined views

—

1 Source, first seen 1h ago

— likes— comments— saves— reposts

Combined views

—

1 Source, first seen 1h ago

— likes— comments— saves— reposts

Sentiment

Positive——Negative

Summary

Not enough discussion yet.

No sentiment analysis available yet.

Featured Source

Sentiment

Positive——Negative

Summary

Not enough discussion yet.

No sentiment analysis available yet.

1 Source

Tatsunori Hashimoto@tatsu_hashimotoDeep learning is often taught as a sanitized collection of facts and math. But work at the frontier of AI is messy and empirical. Our new class, Deep Learning Alchemy, aims to teach the art and science of deep learning in the hands-on spirit of Language Modeling From Scratch. Students build intuition by running experiments on small LMs, then test it through prediction quizzes: given an unseen code diff, can you predict what happens? https://t.co/0H82T1yyam My co-instructor @kothasuhas and I think there's significant demand for classes that treat students as serious learners who want to be assessed for what they’ve learned, and so we're trying a new exam-heavy approach to the class (7 exams, 85% of the grade, with the remaining 15% in-person discussion assessments). We’ve designed the class so students can use AI agents to run their experiments and do their assignment, but they then have to demonstrate that mastery on exams without access to the assignment, and any partial credit on the exam has to come through citations to the assignment, incentivizing them to know what’s in their write-up. The same assignments and quizzes are public for anyone to try (lecture recordings will be released through @StanfordOnline with some delay). We have some very fun assignments and quizzes covering both classic topics (like NQM, run-to-run stochasticity, and scaling laws) and new and timely topics like muP or hyperball. Made by some real experts like @TristanThrush and @wen_kaiyue Try some quizzes below!1h
    • Home
    • Technology
    • Gaming
    • Entertainment
    • World & Business
    • Science
    • Sports
    • AI

    1 Source

    Tatsunori Hashimoto@tatsu_hashimotoDeep learning is often taught as a sanitized collection of facts and math. But work at the frontier of AI is messy and empirical. Our new class, Deep Learning Alchemy, aims to teach the art and science of deep learning in the hands-on spirit of Language Modeling From Scratch. Students build intuition by running experiments on small LMs, then test it through prediction quizzes: given an unseen code diff, can you predict what happens? https://t.co/0H82T1yyam My co-instructor @kothasuhas and I think there's significant demand for classes that treat students as serious learners who want to be assessed for what they’ve learned, and so we're trying a new exam-heavy approach to the class (7 exams, 85% of the grade, with the remaining 15% in-person discussion assessments). We’ve designed the class so students can use AI agents to run their experiments and do their assignment, but they then have to demonstrate that mastery on exams without access to the assignment, and any partial credit on the exam has to come through citations to the assignment, incentivizing them to know what’s in their write-up. The same assignments and quizzes are public for anyone to try (lecture recordings will be released through @StanfordOnline with some delay). We have some very fun assignments and quizzes covering both classic topics (like NQM, run-to-run stochasticity, and scaling laws) and new and timely topics like muP or hyperball. Made by some real experts like @TristanThrush and @wen_kaiyue Try some quizzes below!1h
    Today's Rank

    —

    Not ranked yet

    Today's Rank

    —

    Not ranked yet