Take a trip with me through the paper Large Language Models, A Survey, published on February 9th of 2024. All figures and tables mentioned throughout the episode can be found on the Into AI Safety podcast website.

00:36 - Intro and authors
01:50 - My takes and paper structure
04:40 - Getting to LLMs
07:27 - Defining LLMs & emergence
12:12 - Overview of PLMs
15:00 - How LLMs are built
18:52 - Limitations if LLMs
23:06 - Uses of LLMs
25:16 - Evaluations and Benchmarks
28:11 - Challenges and future directions
29:21 - Recap & outro

Links to all articles/papers which are mentioned throughout the episode can be found below, in order of their appearance.

• Large Language Models, A Survey
• Meysam's LinkedIn Post
• Claude E. Shannon
  • A symbolic analysis of relay and switching circuits (Master's Thesis)
  • Communication theory of secrecy systems
  • A mathematical theory of communication
  • Prediction and entropy of printed English
• Future ML Systems Will Be Qualitatively Different
• More Is Different
• Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training
• Are Emergent Abilities of Large Language Models a Mirage?
• Are Emergent Abilities of Large Language Models just In-Context Learning?
• Attention is all you need
• Direct Preference Optimization: Your Language Model is Secretly a Reward Model
• KTO: Model Alignment as Prospect Theoretic Optimization
• Optimization by Simulated Annealing
• Memory and new controls for ChatGPT
• Hallucinations and related concepts—their conceptual background