research.md
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Bruto
### The original Three articles.
- https://www.oreilly.com/radar/what-we-learned-from-a-year-of-building-with-llms-part-i/
- https://www.oreilly.com/radar/what-we-learned-from-a-year-of-building-with-llms-part-ii/
- https://www.oreilly.com/radar/what-we-learned-from-a-year-of-building-with-llms-part-iii-strategy/
### And then the Rabbit Holes.
- https://www.microsoft.com/en-us/research/blog/the-power-of-prompting/ Microsoft's ideas on prompt engr rather than fine-tunning.
- https://www.linkedin.com/blog/engineering/generative-ai/musings-on-building-a-generative-ai-product LinkedIn's App work description.
- https://jxnl.github.io/blog/writing/2024/02/28/levels-of-complexity-rag-applications/ Some ideas on whata RAG app might look like.
Hamel Husain's ideas... very useful
- https://hamel.dev/blog/posts/evals/
- https://hamel.dev/blog/posts/prompt/
- https://gist.github.com/hamelsmu/d0d75bf702e56987f35cb715f7da4d6a
- https://hamel.dev/blog/posts/evals/#step-1-write-scoped-tests
Write the Tests!!
#### Andrej Karpathy is a demi-god.
- https://x.com/karpathy/status/1748043513156272416
#### More App example experiences.
- https://doordash.engineering/2020/08/28/overcome-the-cold-start-problem-in-menu-item-tagging/
description of DoorDash App.
- https://arxiv.org/pdf/2212.10481 Execution-Based Evaluation for Open-Domain Code Generation
- https://www.godaddy.com/resources/news/llm-from-the-trenches-10-lessons-learned-operationalizing-models-at-godaddy#h-1-sometimes-one-prompt-isn-t-enough
GoDaddy'ss LLM App Description.
- https://promptengineering.org/what-are-large-language-model-llm-agents/
what's a LLM-agent and why?
- https://github.com/daveshap/SparsePrimingRepresentations
a very clever way to condense knowledge to be used within prompts.
#### Prompt frameworks
- https://github.com/outlines-dev/outlines
- https://github.com/jxnl/instructor
#### SQL PaLM
- https://www.researchgate.net/publication/371223615_SQL-PaLM_Improved_Large_Language_ModelAdaptation_for_Text-to-SQL
#### Create a LLM from Scratch
- https://pbs.twimg.com/card_img/1799150371614437376/EcIpp2ov?format=jpg&name=small
#### Code-aid tool
- https://austinhenley.com/blog/codeaid.html
- https://austinhenley.com/pubs/Kazemitabaar2024CHI_CodeAid.pdf
- https://lancedb.com
a vector database for use to handle embedding and chunked text(?)
The original Three articles.
- https://www.oreilly.com/radar/what-we-learned-from-a-year-of-building-with-llms-part-i/
- https://www.oreilly.com/radar/what-we-learned-from-a-year-of-building-with-llms-part-ii/
- https://www.oreilly.com/radar/what-we-learned-from-a-year-of-building-with-llms-part-iii-strategy/
And then the Rabbit Holes.
- https://www.microsoft.com/en-us/research/blog/the-power-of-prompting/ Microsoft's ideas on prompt engr rather than fine-tunning.
- https://www.linkedin.com/blog/engineering/generative-ai/musings-on-building-a-generative-ai-product LinkedIn's App work description.
- https://jxnl.github.io/blog/writing/2024/02/28/levels-of-complexity-rag-applications/ Some ideas on whata RAG app might look like.
Hamel Husain's ideas... very useful
- https://hamel.dev/blog/posts/evals/
- https://hamel.dev/blog/posts/prompt/
- https://gist.github.com/hamelsmu/d0d75bf702e56987f35cb715f7da4d6a
- https://hamel.dev/blog/posts/evals/#step-1-write-scoped-tests Write the Tests!!
Andrej Karpathy is a demi-god.
More App example experiences.
- https://doordash.engineering/2020/08/28/overcome-the-cold-start-problem-in-menu-item-tagging/ description of DoorDash App.
- https://arxiv.org/pdf/2212.10481 Execution-Based Evaluation for Open-Domain Code Generation
- https://www.godaddy.com/resources/news/llm-from-the-trenches-10-lessons-learned-operationalizing-models-at-godaddy#h-1-sometimes-one-prompt-isn-t-enough GoDaddy'ss LLM App Description.
- https://promptengineering.org/what-are-large-language-model-llm-agents/ what's a LLM-agent and why?
- https://github.com/daveshap/SparsePrimingRepresentations a very clever way to condense knowledge to be used within prompts.
Prompt frameworks
SQL PaLM
Create a LLM from Scratch
Code-aid tool
-
https://austinhenley.com/pubs/Kazemitabaar2024CHI_CodeAid.pdf
-
https://lancedb.com a vector database for use to handle embedding and chunked text(?)