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MINISODE: "LLMs, a Survey"
Manage episode 403264357 series 3536907
Sisällön tarjoaa Jacob Haimes. Jacob Haimes tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.
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
- 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
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