- See Also
- Gwern
-
Links
- “RAG vs Fine-Tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture”, Balaguer et al 2024
- “Inside the Chaos at OpenAI: Sam Altman’s Weekend of Shock and Drama Began a Year Ago, With the Release of ChatGPT”, Hao & Warzel 2023
- “Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation”, Ding et al 2023
- “Does GPT-4 Pass the Turing Test?”, Jones & Bergen 2023
- “PAIR: Jailbreaking Black Box Large Language Models in 20 Queries”, Chao et al 2023
- “Fine-Tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!”, Qi et al 2023
- “Non-Determinism in GPT-4 Is Caused by Sparse MoE”, 152334H 2023
- “Large Language Models As Superpositions of Cultural Perspectives”, Kovač et al 2023
- “AI Is a Lot of Work: As the Technology Becomes Ubiquitous, a Vast Tasker Underclass Is Emerging—And Not Going Anywhere”, Dzieza 2023
- “I’m Afraid I Can’t Do That: Predicting Prompt Refusal in Black-Box Generative Language Models”, Reuter & Schulze 2023
- “Why Didn'T DeepMind Build GPT-3?”, Godwin 2023
- “OpenAI’s Sam Altman Talks ChatGPT And How Artificial General Intelligence Can ‘Break Capitalism’”, Konrad & Cai 2023
- “GPT-3 As Knowledge Worker: A Zero-Shot Evaluation of (AI)CPA Capabilities”, Bommarito et al 2023
- “HALIE: Evaluating Human-Language Model Interaction”, Lee et al 2022
- “TruthfulQA: Measuring How Models Mimic Human Falsehoods”, Lin et al 2021
- “‘How GPT-3 Is Shaping Our AI Future’ With Sam Altman/Azeem Azhar (The Exponential View), Wednesday 7 October 2020”
- “Towards Synthesizing Complex Programs from Input-Output Examples”, Chen et al 2017
- “Genetics of Caffeine Consumption and Responses to Caffeine”, Yang et al 2010
- Sort By Magic
- Miscellaneous
- Link Bibliography
See Also
Gwern
“The Scaling Hypothesis”, Gwern 2020
Links
“RAG vs Fine-Tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture”, Balaguer et al 2024
RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture
“Inside the Chaos at OpenAI: Sam Altman’s Weekend of Shock and Drama Began a Year Ago, With the Release of ChatGPT”, Hao & Warzel 2023
“Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation”, Ding et al 2023
Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation
“Does GPT-4 Pass the Turing Test?”, Jones & Bergen 2023
“PAIR: Jailbreaking Black Box Large Language Models in 20 Queries”, Chao et al 2023
PAIR: Jailbreaking Black Box Large Language Models in 20 Queries
“Fine-Tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!”, Qi et al 2023
Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!
“Non-Determinism in GPT-4 Is Caused by Sparse MoE”, 152334H 2023
“Large Language Models As Superpositions of Cultural Perspectives”, Kovač et al 2023
Large Language Models as Superpositions of Cultural Perspectives
“AI Is a Lot of Work: As the Technology Becomes Ubiquitous, a Vast Tasker Underclass Is Emerging—And Not Going Anywhere”, Dzieza 2023
“I’m Afraid I Can’t Do That: Predicting Prompt Refusal in Black-Box Generative Language Models”, Reuter & Schulze 2023
I’m Afraid I Can’t Do That: Predicting Prompt Refusal in Black-Box Generative Language Models
“Why Didn'T DeepMind Build GPT-3?”, Godwin 2023
“OpenAI’s Sam Altman Talks ChatGPT And How Artificial General Intelligence Can ‘Break Capitalism’”, Konrad & Cai 2023
OpenAI’s Sam Altman Talks ChatGPT And How Artificial General Intelligence Can ‘Break Capitalism’
“GPT-3 As Knowledge Worker: A Zero-Shot Evaluation of (AI)CPA Capabilities”, Bommarito et al 2023
GPT-3 as Knowledge Worker: A Zero-Shot Evaluation of (AI)CPA Capabilities
“HALIE: Evaluating Human-Language Model Interaction”, Lee et al 2022
“TruthfulQA: Measuring How Models Mimic Human Falsehoods”, Lin et al 2021
“‘How GPT-3 Is Shaping Our AI Future’ With Sam Altman/Azeem Azhar (The Exponential View), Wednesday 7 October 2020”
“Towards Synthesizing Complex Programs from Input-Output Examples”, Chen et al 2017
Towards Synthesizing Complex Programs from Input-Output Examples
“Genetics of Caffeine Consumption and Responses to Caffeine”, Yang et al 2010
Sort By Magic
Annotations sorted by machine learning into inferred 'tags'. This provides an alternative way to browse: instead of by date order, one can browse in topic order. The 'sorted' list has been automatically clustered into multiple sections & auto-labeled for easier browsing.
Beginning with the newest annotation, it uses the embedding of each annotation to attempt to create a list of nearest-neighbor annotations, creating a progression of topics. For more details, see the link.
language-models
openai-drama
gpt-evolution
Miscellaneous
-
/doc/ai/nn/transformer/gpt/3/2019-11-07-amodei-aiandcompute-twodistincteras-gpt3modified.png: -
https://andrewmayne.com/2023/11/14/is-the-reversal-curse-real/:View External Link:
https://andrewmayne.com/2023/11/14/is-the-reversal-curse-real/ -
https://barryzhang.substack.com/p/our-humble-attempt-at-fine-tuning -
https://openai.com/blog/gpt-3-5-turbo-fine-tuning-and-api-updates -
https://twitter.com/somefoundersalt/status/1708599134960398586: -
https://twitter.com/yoheinakajima/status/1670557048743010305 -
https://www.cerebras.net/blog/introducing-gigagpt-gpt-3-sized-models-in-565-lines-of-code -
https://www.reddit.com/r/mlscaling/comments/146rgq2/chatgpt_is_running_quantized/
Link Bibliography
-
https://arxiv.org/abs/2401.08406#microsoft: “RAG vs Fine-Tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture”, -
https://www.theatlantic.com/technology/archive/2023/11/sam-altman-open-ai-chatgpt-chaos/676050/: “Inside the Chaos at OpenAI: Sam Altman’s Weekend of Shock and Drama Began a Year Ago, With the Release of ChatGPT”, Karen Hao, Charlie Warzel -
https://arxiv.org/abs/2310.08419: “PAIR: Jailbreaking Black Box Large Language Models in 20 Queries”, Patrick Chao, Alexander Robey, Edgar Dobriban, Hamed Hassani, George J. Pappas, Eric Wong -
https://152334h.github.io/blog/non-determinism-in-gpt-4/: “Non-Determinism in GPT-4 Is Caused by Sparse MoE”, 152334H -
https://arxiv.org/abs/2307.07870: “Large Language Models As Superpositions of Cultural Perspectives”, Grgur Kovač, Masataka Sawayama, Rémy Portelas, Cédric Colas, Peter Ford Dominey, Pierre-Yves Oudeyer -
https://www.theverge.com/features/23764584/ai-artificial-intelligence-data-notation-labor-scale-surge-remotasks-openai-chatbots: “AI Is a Lot of Work: As the Technology Becomes Ubiquitous, a Vast Tasker Underclass Is Emerging—And Not Going Anywhere”, Josh Dzieza -
https://arxiv.org/abs/2306.03423: “I’m Afraid I Can’t Do That: Predicting Prompt Refusal in Black-Box Generative Language Models”, Max Reuter, William Schulze -
https://www.forbes.com/sites/alexkonrad/2023/02/03/exclusive-openai-sam-altman-chatgpt-agi-google-search/: “OpenAI’s Sam Altman Talks ChatGPT And How Artificial General Intelligence Can ‘Break Capitalism’”, Alex Konrad, Kenrick Cai -
https://arxiv.org/abs/2301.04408: “GPT-3 As Knowledge Worker: A Zero-Shot Evaluation of (AI)CPA Capabilities”, Jillian Bommarito, Michael Bommarito, Daniel Martin Katz, Jessica Katz -
https://arxiv.org/abs/2109.07958: “TruthfulQA: Measuring How Models Mimic Human Falsehoods”, Stephanie Lin, Jacob Hilton, Owain Evans