))
MINISODE: "LLMs, a Survey"
Manage episode 403264357 series 3536907
Contenu fourni par Jacob Haimes. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Jacob Haimes ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.
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
19 episodes
Partager
