- See Also
-
Links
- “Google Is Asking Employees to Test Potential ChatGPT Competitors, including a Chatbot Called 'Apprentice Bard'”, Elias 2023
- “Creative Writing With Wordcraft, an AI-Powered Writing Assistant: Perspectives from Professional Writers”, Ippolito et al 2022
- “Language Model Cascades”, Dohan et al 2022
- “Exploring Length Generalization in Large Language Models”, Anil et al 2022
- “Least-To-Most Prompting Enables Complex Reasoning in Large Language Models”, Zhou et al 2022
- “Google Is Beta Testing Its AI Future: After Mistakes and Challenges, the Company Is Moving a Little Slower With AI Language Models”, Vincent 2022
- “PaLM: Scaling Language Modeling With Pathways”, Chowdhery et al 2022
- “Self-Consistency Improves Chain-Of-Thought Reasoning in Language Models”, Wang et al 2022
- “PromptChainer: Chaining Large Language Model Prompts through Visual Programming”, Wu et al 2022
- “Using Natural Language Prompts for Machine Translation”, Garcia & Firat 2022
- “Chain-Of-Thought Prompting Elicits Reasoning in Large Language Models”, Wei et al 2022
- “LaMDA: Language Models for Dialog Applications”, Thoppilan et al 2022
- “SynthBio: A Case Study in Faster Curation of Text Datasets”, Yuan et al 2022
- “Discovering the Syntax and Strategies of Natural Language Programming With Generative Language Models”, Jiang et al 2022
- “GLaM: Efficient Scaling of Language Models With Mixture-Of-Experts”, Du et al 2021
- “Show Your Work: Scratchpads for Intermediate Computation With Language Models”, Nye et al 2021
- “AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Prompts”, Wu et al 2021
- “A Recipe For Arbitrary Text Style Transfer With Large Language Models”, Reif et al 2021
- “GenLine and GenForm: Two Tools for Interacting With Generative Language Models in a Code Editor”, Jiang et al 2021b
- “FLAN: Finetuned Language Models Are Zero-Shot Learners”, Wei et al 2021
- “Program Synthesis With Large Language Models”, Austin et al 2021
- “Towards a Human-Like Open-Domain Chatbot”, Adiwardana et al 2020
- “LaMDA: Our Breakthrough Conversation Technology”
- Sort By Magic
- Miscellaneous
- Link Bibliography
See Also
Links
“Google Is Asking Employees to Test Potential ChatGPT Competitors, including a Chatbot Called 'Apprentice Bard'”, Elias 2023
“Creative Writing With Wordcraft, an AI-Powered Writing Assistant: Perspectives from Professional Writers”, Ippolito et al 2022
“Language Model Cascades”, Dohan et al 2022
“Exploring Length Generalization in Large Language Models”, Anil et al 2022
“Least-To-Most Prompting Enables Complex Reasoning in Large Language Models”, Zhou et al 2022
Least-to-Most Prompting Enables Complex Reasoning in Large Language Models
“Google Is Beta Testing Its AI Future: After Mistakes and Challenges, the Company Is Moving a Little Slower With AI Language Models”, Vincent 2022
“PaLM: Scaling Language Modeling With Pathways”, Chowdhery et al 2022
“Self-Consistency Improves Chain-Of-Thought Reasoning in Language Models”, Wang et al 2022
Self-Consistency Improves Chain-of-Thought Reasoning in Language Models
“PromptChainer: Chaining Large Language Model Prompts through Visual Programming”, Wu et al 2022
PromptChainer: Chaining Large Language Model Prompts through Visual Programming
“Using Natural Language Prompts for Machine Translation”, Garcia & Firat 2022
“Chain-Of-Thought Prompting Elicits Reasoning in Large Language Models”, Wei et al 2022
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
“LaMDA: Language Models for Dialog Applications”, Thoppilan et al 2022
“SynthBio: A Case Study in Faster Curation of Text Datasets”, Yuan et al 2022
“Discovering the Syntax and Strategies of Natural Language Programming With Generative Language Models”, Jiang et al 2022
“GLaM: Efficient Scaling of Language Models With Mixture-Of-Experts”, Du et al 2021
GLaM: Efficient Scaling of Language Models with Mixture-of-Experts
“Show Your Work: Scratchpads for Intermediate Computation With Language Models”, Nye et al 2021
Show Your Work: Scratchpads for Intermediate Computation with Language Models
“AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Prompts”, Wu et al 2021
“A Recipe For Arbitrary Text Style Transfer With Large Language Models”, Reif et al 2021
A Recipe For Arbitrary Text Style Transfer with Large Language Models
“GenLine and GenForm: Two Tools for Interacting With Generative Language Models in a Code Editor”, Jiang et al 2021b
GenLine and GenForm: Two Tools for Interacting with Generative Language Models in a Code Editor
“FLAN: Finetuned Language Models Are Zero-Shot Learners”, Wei et al 2021
“Program Synthesis With Large Language Models”, Austin et al 2021
“Towards a Human-Like Open-Domain Chatbot”, Adiwardana et al 2020
“LaMDA: Our Breakthrough Conversation Technology”
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.
ai-writing-aid
code-generation
prompt-engineering
language-modeling
Miscellaneous
-
https://blog.google/technology/ai/bard/-google-ai-search-updates/ -
https://medium.com/@blaisea/do-large-language-models-understand-us-6f881d6d8e75 -
https://wordcraft-writers-workshop.appspot.com/stories/allison-parrish -
https://wordcraft-writers-workshop.appspot.com/stories/diana-hamilton -
https://wordcraft-writers-workshop.appspot.com/stories/eugenia-triantafyllou -
https://www.technologyreview.com/2021/05/20/1025135/ai-large-language-models-bigscience-project/:
Link Bibliography
-
https://www.cnbc.com/2023/01/31/google-testing-chatgpt-like-chatbot-apprentice-bard-with-employees.html: “Google Is Asking Employees to Test Potential ChatGPT Competitors, including a Chatbot Called 'Apprentice Bard'”, Jennifer Elias -
https://arxiv.org/abs/2211.05030#google: “Creative Writing With Wordcraft, an AI-Powered Writing Assistant: Perspectives from Professional Writers”, Daphne Ippolito, Ann Yuan, Andy Coenen, Sehmon Burnam -
https://arxiv.org/abs/2205.10625#google: “Least-To-Most Prompting Enables Complex Reasoning in Large Language Models”, -
https://www.theverge.com/2022/5/11/23065072/google-ai-app-test-kitchen-future-io-2022: “Google Is Beta Testing Its AI Future: After Mistakes and Challenges, the Company Is Moving a Little Slower With AI Language Models”, James Vincent -
https://arxiv.org/abs/2204.02311#google: “PaLM: Scaling Language Modeling With Pathways”, -
https://arxiv.org/abs/2203.11171#google: “Self-Consistency Improves Chain-Of-Thought Reasoning in Language Models”, Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, Denny Zhou -
https://arxiv.org/abs/2202.11822#google: “Using Natural Language Prompts for Machine Translation”, Xavier Garcia, Orhan Firat -
https://arxiv.org/abs/2201.11903#google: “Chain-Of-Thought Prompting Elicits Reasoning in Large Language Models”, Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Ed Chi, Quoc Le, Denny Zhou -
2021-jiang-2.pdf: “GenLine and GenForm: Two Tools for Interacting With Generative Language Models in a Code Editor”, Ellen Jiang, Edwin Toh, Alejandra Molina, Aaron Donsbach, Carrie Cai, Michael Terry