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NJIT AI Safety Association
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Fellowships
Intro to AI Safety FellowshipTechnical AI Safety Fellowship
Resources
About
Fellowships
Intro to AI Safety FellowshipTechnical AI Safety Fellowship
Resources

← Intro fellowship curriculum

Week 1 — Timelines & Threat Models

This week builds a grounded picture of where frontier AI capabilities are headed and how quickly they may improve. We will review evidence on scaling drivers—compute, data, algorithmic efficiency, and inference-time scaling—alongside time-horizon forecasting.

Open the Week 1 curriculum in Google Docs ↗

Core resources

  • Task-Completion Time Horizons of Frontier AI Models (METR, 2026) ↗
  • Can AI scaling continue through 2030? (Epoch AI, 2024) ↗
  • What is the orthogonality thesis? (AISafety.info) ↗
  • An Overview of Catastrophic AI Risks (Center for AI Safety, 2023) ↗

Recommended resources

  • What will AI look like in 2030? (Epoch AI, 2025) ↗
  • When AI builds itself (Anthropic, 2026) ↗
  • Inference Scaling and the Log-x Chart (Toby Ord, 2025) ↗
  • From AGI to Superintelligence: the Intelligence Explosion (Leopold Aschenbrenner, 2024) ↗
  • Future ML Systems will be Qualitatively Different (Steinhardt, 2022) ↗

Further readings

  • Biological Anchors: A Trick That Might Or Might Not Work (Alexander, 2022) ↗
  • Training Compute-Optimal Large Language Models (GDM, 2022) ↗
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