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https://github.com/filipecalegario/awesome-generative-deep-art

A curated list of Generative AI tools, works, models, and references
https://github.com/filipecalegario/awesome-generative-deep-art

ai-art awesome awesome-list chatgpt dall-e dalle2 embeddings generative-ai gpt-4 llm llm-agent midjourney openai prompt-engineering semantic-search stable-diffusion text-to-image txt2img

Last synced: about 1 year ago
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A curated list of Generative AI tools, works, models, and references

Awesome Lists containing this project

README 

          
# Awesome Generative AI [![Awesome](https://awesome.re/badge.svg)](https://awesome.re)[![Track Awesome List](https://www.trackawesomelist.com/badge.svg)](https://www.trackawesomelist.com/filipecalegario/awesome-generative-deep-art/) 



> A curated list of Generative AI projects, tools, artworks, and models



- [Generative AI Area](#generative-ai-area)

  - [Generative AI history, timelines, maps, and definitions](#generative-ai-history-timelines-maps-and-definitions)

  - [Ethics, Philosophical questions and Discussions about Generative AI](#ethics-philosophical-questions-and-discussions-about-generative-ai)

  - [Critical Views about Generative AI](#critical-views-about-generative-ai)

  - [Generative AI Processes and Artifacts](#generative-ai-processes-and-artifacts)

  - [Generative AI Tools Directories](#generative-ai-tools-directories)

  - [Courses and Educational Materials](#courses-and-educational-materials)

  - [Human-AI Interaction](#human-ai-interaction)

  - [Papers Collection](#papers-collection)

  - [Online Tools and Applications](#online-tools-and-applications)

- [Code and Programming](#code-and-programming)

  - [Vibe Coding](#vibe-coding)

  - [AI-Powered Code Generation](#ai-powered-code-generation)

- [Text](#text)

  - [Everything to Markdown to LLMs](#everything-to-markdown-to-llms)

  - [Small Language Models](#small-language-models)

  - [Large Language Models (LLMs)](#large-language-models-llms)

    - [Model Context Protocol](#model-context-protocol)

    - [Programming Frameworks for LLMs](#programming-frameworks-for-llms)

    - [Prompt Engineering](#prompt-engineering)

      - [Prompt Optimizers](#prompt-optimizers)

      - [Prompt Engineering for Text-to-text](#prompt-engineering-for-text-to-text)

      - [Prompt Engineering for Text-to-image](#prompt-engineering-for-text-to-image)

    - [Mamba](#mamba)

    - [Running LLMs Locally](#running-llms-locally)

    - [Function Calling](#function-calling)

    - [GPTs and Assistant API](#gpts-and-assistant-api)

    - [Retrieval-Augmented Generation (RAG)](#retrieval-augmented-generation-rag)

    - [Embeddings and Semantic Search](#embeddings-and-semantic-search)

    - [Autonomous LLM Agents](#autonomous-llm-agents)

      - [Multi-agents](#multi-agents)

    - [LLM Evaluation](#llm-evaluation)

    - [LLMOps](#llmops)

    - [AI Engineering](#ai-engineering)

    - [Attacks on LLMs](#attacks-on-llms)

    - [LangChain](#langchain)

    - [ChatGPT](#chatgpt)

    - [Text-related Generative Tools](#text-related-generative-tools)

  - [Research AI Tools](#research-ai-tools)

    - [AI Tools for Research](#ai-tools-for-research)

    - [AI Tools for Searching](#ai-tools-for-searching)

- [Image](#image)

  - [Image Synthesis](#image-synthesis)

    - [Inbox: Stable Diffusion](#inbox-stable-diffusion)

      - [Stable Diffusion Deployed Web Tools](#stable-diffusion-deployed-web-tools)

      - [Web UI for Stable Diffusion via Google Colab](#web-ui-for-stable-diffusion-via-google-colab)

      - [References Collection about Stable Diffusion](#references-collection-about-stable-diffusion)

    - [Hypertechniques](#hypertechniques)

      - [ControlNet](#controlnet)

      - [Textual Inversion](#textual-inversion)

      - [DreamBooth](#dreambooth)

      - [Deforum](#deforum)

    - [Creative Uses of Generative AI Image Synthesis Tools](#creative-uses-of-generative-ai-image-synthesis-tools)

  - [Image Upscaling](#image-upscaling)

  - [Image Restoration](#image-restoration)

  - [Image Segmentation](#image-segmentation)

- [Video and Animation](#video-and-animation)

- [Audio and Music](#audio-and-music)

- [Speech](#speech)

  - [Text-to-speech (TTS) and avatars](#text-to-speech-tts-and-avatars)

    - [Podcast generators](#podcast-generators)

  - [Speech-to-text (STT) and spoken content analysis](#speech-to-text-stt-and-spoken-content-analysis)

- [Games](#games)

- [Multimodal](#multimodal)

  - [Multimodal Embedding Space](#multimodal-embedding-space)

- [Datasets](#datasets)

- [Misc](#misc)

  - [AI and Education](#ai-and-education)

  - [People and works](#people-and-works)

    - [Interesting Twitter Accounts](#interesting-twitter-accounts)

    - [Interesting Instagram Accounts, Posts and Reels](#interesting-instagram-accounts-posts-and-reels)

    - [Interesting Youtube Channels](#interesting-youtube-channels)

    - [Interesting GitHub Repositories](#interesting-github-repositories)

    - [Artists and Artworks](#artists-and-artworks)

    - [Galleries](#galleries)

  - [Related Awesome Lists](#related-awesome-lists)

  - [Bio experiments](#bio-experiments)

  - [Jobs in Generative AI](#jobs-in-generative-ai)

  - [Improving Google Colab experience](#improving-google-colab-experience)

  - [Auxiliary tools and concepts](#auxiliary-tools-and-concepts)

    - [Dimension reduction techniques](#dimension-reduction-techniques)

  - [Roadmaps, Tracks, Rails](#roadmaps-tracks-rails)

  - [Stargazers over time](#stargazers-over-time)

  - [Contribute](#contribute)

  - [License](#license)



## Repository Introduction



Welcome to our Awesome List of Generative AI resources! This repository is a curated collection of references in the dynamic field of Generative AI, equipped with various sources such as academic papers, technical articles, online courses, tutorials, and software.



### Structure



1. **Sections**: Each section represents a different Generative AI-related category (e.g., LLMs, prompt engineering, image synthesis, educational resources, etc.). The Inboxes are the more general references of a category. When a new category emerges, it becomes a specific subsection.



2. **References within sections**: Inside each section, references are listed in reverse chronological order, with the most recent one at the top. This order signifies the ever-evolving landscape of Generative AI, keeping you up-to-date with the latest developments.



This repository is designed to offer you the most recent advancements at your fingertips, allowing you to explore the depth of older resources at your own pace. It's regularly updated, ensuring you're always on track with the rapidly progressing world of Generative AI.



### Contribute to our Repository



Your contributions are welcome and greatly appreciated! If you have a valuable resource that you believe should be on this list, or if you see any outdated information, please make a Pull Request. This will help us maintain the quality and relevance of our Awesome List.



Follow this roadmap, keep learning, and enjoy your journey through Generative AI!



# Generative AI Area



## Generative AI history, timelines, maps, and definitions



* [Agents Marketplace](https://marketplace.agen.cy/agents)

* [🔥] [2024 AI Timeline](https://huggingface.co/spaces/reach-vb/2024-ai-timeline): a Hugging Face Space by reach-vb

* [Cartography of generative AI](https://cartography-of-generative-ai.net/): "What set of extractions, agencies, and resources allow us to converse online with a text-generating tool or to obtain images in a matter of seconds?"

* [The Rise of Generative AI Large Language Models (LLMs)](https://informationisbeautiful.net/visualizations/the-rise-of-generative-ai-large-language-models-llms-like-chatgpt/): interactive timeline visualization made by Information Is Beautiful 

* [The AI Timeline (@TheAITimeline) / X](https://x.com/TheAITimeline)

* [Generative AI for Beginners: Part 1 — Introduction to AI | by Raja Gupta | Medium](https://medium.com/@raja.gupta20/generative-ai-for-beginners-part-1-introduction-to-ai-eadb5a71f07d) 

* [Artificial Intelligence Learning Roadmap [AI Roadmap] 2024](https://www.mltut.com/artificial-intelligence-learning-roadmap/)

* [A Brief History of Generative AI - DATAVERSITY](https://www.dataversity.net/a-brief-history-of-generative-ai/) 

* [A Simple Guide To The History Of Generative AI | Bernard Marr](https://bernardmarr.com/a-simple-guide-to-the-history-of-generative-ai/) 

* [Generative AI Timeline from January 2023 to July 2023](https://generativeaitimeline.com/) 

* [The rise of generative AI: A timeline of triumphs, hiccups and hype | CIO Dive](https://www.ciodive.com/news/generative-ai-one-year-chatgpt-openai-timeline/698110/) 

* [Brief History In Time: Decoding the Evolution of Generative AI | LinkedIn](https://www.linkedin.com/pulse/brief-history-time-decoding-evolution-generative-ai-csmtechnologies/) 

* [🔥🔥🔥] [FirstMark | 2024 MAD (ML/AI/Data) Landscape](https://mad.firstmark.com/): Full Steam Ahead The 2024 MAD (Machine Learning, AI & Data) Landscape

* [Timeline of AI forecasts - AI Digest](https://theaidigest.org/timeline)

* [Generative AI Iceberg](https://icebergcharts.com/i/Generative_AI) 

* [🔥🔥🔥] [Generative AI in a nutshell](https://blog.crisp.se/wp-content/uploads/2024/01/generative-AI-in-a-nutshell.png): a map with the most common Generative AI' concepts by Henrik Kniberg [Youtube Video explaining the map](https://www.youtube.com/watch?v=2IK3DFHRFfw) 

* [60+ Generative AI Terms You Must Know By Heart](https://www.analyticsvidhya.com/blog/2024/01/generative-ai-terms/): by Analytics Vidhya

* [The Four Wars of the AI Stack (Dec 2023 Recap)](https://www.latent.space/p/dec-2023): "recap of top items for the AI Engineer from Dec 2023" ("The Data Wars, The War of the GPU Rich/Poor, The Multimodality War, The RAG/Ops War")

* [GenAI Prism Infographic by Brian Solis](https://briansolis.com/2023/12/introducing-the-genai-prism-infographic-a-framework-for-colalborating-with-generative-ai/): A Framework for Collaborating with Generative AI

* [LLM Visualization](https://bbycroft.net/llm)

* [[2310.04438] A Brief History of Prompt: Leveraging Language Models](https://arxiv.org/abs/2310.04438): the paper presents an exploration of the evolution of prompt engineering. The author, Golam Md Muktadir, extensively used ChatGPT for content generation

* [An AI Engineer’s Guide to Machine Learning and Generative AI | by ai geek (wishesh) | Oct, 2023 | Medium](https://medium.com/@_aigeek/an-ai-engineers-guide-to-machine-learning-and-generative-ai-b7444941ccee) 

* [Emerging Trends in Generative AI Research: A Selection of Recent Papers](https://txt.cohere.com/top-nlp-papers-september-2023/) 

* [The architecture of today's LLM applications - The GitHub Blog](https://github.blog/2023-10-30-the-architecture-of-todays-llm-applications/) 

* [🔥🔥🔥] [[2310.07127] An HCI-Centric Survey and Taxonomy of Human-Generative-AI Interactions](https://arxiv.org/abs/2310.07127): "a survey of 154 papers, providing a novel taxonomy and analysis of Human-GenAI Interactions from both human and Gen-AI perspectives".

* [The Building Blocks of Generative AI | by Jonathan Shriftman | Medium](https://shriftman.medium.com/the-building-blocks-of-generative-ai-a75350466a2f) 

* [🔥] [Generative AI exists because of the transformer](https://ig.ft.com/generative-ai/): a visual story by Financial Times

* [Early days of AI - by Elad Gil](https://blog.eladgil.com/p/early-days-of-ai): thoughts about AI as "an entirely new era and discontinuity from the past"

* [The Next Token of Progress: 4 Unlocks on the Generative AI Horizon | Andreessen Horowitz](https://a16z.com/2023/06/23/the-next-token-of-progress-4-unlocks-on-the-generative-ai-horizon/) 

* [[2309.07930] Generative AI](https://arxiv.org/abs/2309.07930): discusses a model-, system-, and application-level view on generative AI.

* [The state of AI in 2023: Generative AI’s breakout year | McKinsey](https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2023-generative-ais-breakout-year#/) 

* [A jargon-free explanation of how AI large language models work | Ars Technica](https://arstechnica.com/science/2023/07/a-jargon-free-explanation-of-how-ai-large-language-models-work/) 

* [The Generative AI Revolution: Exploring the Current Landscape | by Towards AI Editorial Team | Jun, 2023 | Towards AI](https://pub.towardsai.net/the-generative-ai-revolution-exploring-the-current-landscape-4b89998fcc5f)

* [The Story of AI Winters and What it Teaches Us Today](https://www.turingpost.com/p/aiwinters)

* [There Would Have Been No LLMs Without This (episode#3 in the History series)](https://www.turingpost.com/p/llmshistory3): timeline of LLMs by Turing Post

* [The Next Token of Progress: 4 Unlocks on the Generative AI Horizon | Andreessen Horowitz](https://a16z.com/2023/06/23/the-next-token-of-progress-4-unlocks-on-the-generative-ai-horizon/): critical innovations on the horizon: steering, memory, ability to use tools, and multimodality

* [The economic potential of generative AI: The next productivity frontier](https://www.linkedin.com/posts/genai-works_gen-ai-activity-7074980736268726272-LiiG): report by McKinsey Jun 2023

* [A survey of Generative AI Applications | arxiv](https://arxiv.org/abs/2306.02781): "this survey aims to serve as a valuable resource for researchers and practitioners to navigate the rapidly expanding landscape of generative AI"

* [Paper Digest - ChatGPT](https://www.paperdigest.org/2023/01/recent-papers-on-chatgpt/): Recent Papers on ChatGPT

* [AI Index Report 2023 – Artificial Intelligence Index](https://aiindex.stanford.edu/report/): report that measures trends in AI written by the Human-Centered Artificial Intelligence from Stanford University

* [A Survey of Large Language Models](https://arxiv.org/abs/2303.18223): paper that summarizes the evolution of language models, with a focus on LLMs, discussing their advances, techniques, and impact on AI development and usage

* [The Generative AI Timeline](https://www.linkedin.com/feed/update/urn:li:activity:7044233450295316480): post in Linkedin by David Foster

* [Who Owns the Generative AI Platform? | Andreessen Horowitz](https://a16z.com/2023/01/19/who-owns-the-generative-ai-platform/): this article discusses the generative AI market and presents an interesting technology stack of the area

* [A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT | arxiv](https://arxiv.org/abs/2303.04226)

* [🔥🔥] [Toward General Design Principles for Generative AI Applications](https://arxiv.org/abs/2301.05578): this paper presents a set of seven principles for the design of generative AI applications

* [🔥] [The landscape of generative AI landscape reports | by Ramsri Goutham | Jan, 2023 | Medium](https://ramsrigoutham.medium.com/the-landscape-of-generative-ai-landscape-reports-615a417b15d): a meta report on the reports published by 9 venture capital firms

* [Generative AI with Cohere: Part 1 - Model Prompting](https://txt.cohere.ai/generative-ai-part-1/): overview of Generative AI by Cohere AI

* [Generative AI with Cohere: Part 2 - Use Case Ideation](https://txt.cohere.ai/generative-ai-part-2/): a list of Generative AI use cases by Cohere AI

* [Large Language Models and Where to Use Them: Part 1](https://txt.cohere.ai/llm-use-cases/): a list of LLM use cases by Cohere AI

* [Large Language Models and Where to Use Them: Part 2](https://txt.cohere.ai/llm-use-cases-p2/)

* [What's the big deal with Generative AI? Is it the future or the present?](https://txt.cohere.ai/generative-ai-future-or-present/): summarization of the area of Generative AI by Cohere AI

* [Timeline of AI and language models](https://lifearchitect.ai/timeline/): LLM timeline organized by Dr Alan D. Thompson from Life Architect

* [A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT | arxiv](https://arxiv.org/abs/2302.09419)

* [A Review of Generative AI from Historical Perspectives](https://www.techrxiv.org/articles/preprint/A_Review_of_Generative_AI_from_Historical_Perspectives/22097942): paper by Dipankar Dasgupta, Deepak Venugopal and Kishor Datta Gupta

* [Matt Shumer on Twitter: "The definitive AI market map Twitter thread"](https://twitter.com/mattshumer_/status/1620465468229451776): "The definitive AI market map Twitter thread"

* [🔥] [Base11 Research - generative-ai](https://base10.vc/research/generative-ai): report about Generative AI produced by the investment firm Base10

* [Engines of Wow: AI Art Comes of Age – Steve Murch](https://www.stevemurch.com/engines-of-wow-ai-art-comes-of-age/2022/12)

* [AI exploded on the scene at the end of 2022 / Twitter](https://twitter.com/RamaswmySridhar/status/1613271413020037120): categories for analyzing tools of Generative AI

* [🔥🔥🔥] [Mapping the Generative AI landscape | Antler](https://www.antler.co/blog/generative-ai) 

* [🔥🔥🔥] [AI Timeline](https://www.fabianmosele.com/ai-timeline): A history of text-to-image ML models by Fabian Mosele

* [AI-Generated Art](https://www.v7labs.com/blog/ai-generated-art): From Text to Images & Beyond Examples

* [1 week of Stable Diffusion | multimodal.art](https://multimodal.art/news/1-week-of-stable-diffusion)



## Ethics, Philosophical questions and Discussions about Generative AI



* [🔭 The Einstein AI model](https://thomwolf.io/blog/scientific-ai.html)

* [Machines of Loving Grace - How AI Could Transform the World for the Better by Dario Amodei](https://darioamodei.com/machines-of-loving-grace)

* [The Five Stages Of AI Grief - NOEMA](https://www.noemamag.com/the-five-stages-of-ai-grief/) 

* [Generative AI Ethics: 8 Biggest Concerns and Risks](https://www.techtarget.com/searchenterpriseai/tip/Generative-AI-ethics-8-biggest-concerns) 

* [Automated Social Science: Language Models as Scientist and Subjects | NBER](https://www.nber.org/papers/w32381) 

* [It’s time to retire the term “user”](https://www.technologyreview.com/2024/04/19/1090872/ai-users-people-terms/): the proliferation of AI means we need a new word

* [Understanding how personality traits, experiences, and attitudes shape negative bias toward AI-generated artworks | Scientific Reports](https://www.nature.com/articles/s41598-024-54294-4) 

* [Tracking AI](https://trackingai.org/): Monitoring Bias in Artificial Intelligence Chatbots

* [Will AI’s Next Wave of Super Intelligence Replace Human Ingenuity? It’s Complicated - Grit Daily News](https://gritdaily.com/will-ais-super-intelligence-replace-human-ingenuity/) 

* [Who is Afraid of Frankenstein? And of Generative AI? | Fast Company Brasil](https://fastcompanybrasil.com/tech/inteligencia-artificial/quem-tem-medo-do-frankenstein-e-da-ia-generativa/) [PT-BR]

* [Hito Steyerl, Mean Images, NLR 140/141, March–June 2023](https://newleftreview.org/issues/ii140/articles/hito-steyerl-mean-images) 

* [The copyright conundrum of AI art - The Verge](https://www.theverge.com/23961021/ai-art-copyright-training-ownership-fair-use) 

* [Recommendations for the advancement of artificial intelligence in Brazil – ABC](https://www.abc.org.br/evento/doc-ia-no-brasil/) [PT-BR]

* [We must stop AI replicating the problems of surveillance capitalism](https://www.ft.com/content/d9063c16-a4d2-4580-b8f6-a4872083d0fa) 

* [Artificial Intelligence at the Service of Collective Intelligence](https://intlekt.io/2023/10/29/artificial-intelligence-at-the-service-of-collective-intelligence/) 

* [New Training Method Helps AI Generalize like People Do - Scientific American](https://www.scientificamerican.com/article/new-training-method-helps-ai-generalize-like-people-do/) 

* [[2310.01405] Representation Engineering: A Top-Down Approach to AI Transparency](https://arxiv.org/abs/2310.01405): "an approach to enhancing the transparency of AI systems that draws on insights from cognitive neuroscience"

* [Generative AI Resources for Berkeley Law Faculty & Staff - Berkeley Law](https://www.law.berkeley.edu/library/legal-research/chatgpt/)

* [Licensing is neither feasible nor effective for addressing AI risks](https://www.aisnakeoil.com/p/licensing-is-neither-feasible-nor) 

* [Generative AI companies must publish transparency reports](https://www.aisnakeoil.com/p/generative-ai-companies-must-publish) 

* [Does ChatGPT have a liberal bias?](https://www.aisnakeoil.com/p/does-chatgpt-have-a-liberal-bias) 

* [More human than human: measuring ChatGPT political bias | Public Choice](https://link.springer.com/article/10.1007/s11127-023-01097-2) 

* [Redefining Bias: The Human Prejudice Against AI | Medium](https://johnnosta.medium.com/redefining-bias-the-human-prejudice-against-ai-a1f225b0b2c2) 

* [AI Art and its Impact on Artists](https://dl.acm.org/doi/10.1145/3600211.3604681): paper published in the Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society

* [The Age of AI has begun | Bill Gates](https://www.gatesnotes.com/The-Age-of-AI-Has-Begun) 

* [The AIKEA Effect](https://piszek.com/2023/08/28/aikea-effect/): by Artur Piszek

* [Ethics of Artificial Intelligence: Case Studies and Options for Addressing Ethical Challenges | SpringerLink](https://link.springer.com/book/10.1007/978-3-031-17040-9) 

* [Embracing change and resetting expectations | Microsoft Unlocked](https://unlocked.microsoft.com/ai-anthology/terence-tao/): text by Terence Tao

* [Art and the science of generative AI | Science](https://www.science.org/doi/10.1126/science.adh4451) 

* [Where AI evolves from here](https://www.axios.com/2023/05/18/ai-agi-artificial-general-intelligence) 

* [The Age of AI has begun](https://www.gatesnotes.com/The-Age-of-AI-Has-Begun): notes by Bill Gates

* [GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models](https://arxiv.org/abs/2303.10130): OpenAI's paper that discusses the possible implications of GPTs on the U.S. labor market 

* [Why generative AI scares artists but not content writers](https://www.fastcompany.com/90848228/why-generative-ai-scares-artists-but-not-writers)

* [Cultures in AI/AI in Culture](https://ai-cultures.github.io/): NeurIPS 2022 Workshop webpage

* [AI Data Laundering - Waxy.org](https://waxy.org/2022/09/ai-data-laundering-how-academic-and-nonprofit-researchers-shield-tech-companies-from-accountability/): How Academic and Nonprofit Researchers Shield Tech Companies from Accountability

* [🔥🔥🔥] [(1232) The End of Art: An Argument Against Image AIs - YouTube](https://www.youtube.com/watch?v=tjSxFAGP9Ss&t=193s): video essay by Steven Zapata

* [🔥🔥🔥] [The End of Art: An Argument Against Image AIs (Public) - Google Docs](https://docs.google.com/document/d/128yey0VfYhM9eUdvkvCpk5zvvoIkqXfI4hEPAYeJCHU/edit): transcript of the video essay by Steven Zapata

* [🔥🔥🔥] [Generative AI: A Creative New World | Sequoia Capital US/Europe](https://www.sequoiacap.com/article/generative-ai-a-creative-new-world/): report by Sequoia Capital about the possible applications of Generative AI

* [Synthetic Creativity - by Cavin - Deep Markets](https://deepmarkets.substack.com/p/synthetic-creativity)

* [Our Vision for the Future of Synthetic Media | by Victor Riparbelli | Medium](https://vriparbelli.medium.com/our-vision-for-the-future-of-synthetic-media-8791059e8f3a)

* [Deep Else](https://dejangrba.github.io/deep-else/): A Critical Framework for AI Art

* [How Photography Became An Art Form | Aaron Hertzmann’s blog](https://aaronhertzmann.com/2022/08/29/photography-history.html)

* [Can Computers Create Art? by Aaron Hertzmann](https://www.mdpi.com/2076-0752/7/2/18): 2018's essay published on the Arts Journal

* [Text Is the Universal Interface - Scale](https://scale.com/blog/text-universal-interface) 

* [This artist is dominating AI-generated art. And he’s not happy about it. | MIT Technology Review](https://www.technologyreview.com/2022/09/16/1059598/this-artist-is-dominating-ai-generated-art-and-hes-not-happy-about-it/)

* [The REAL fight over AI art: StableDiffusion | Reddit](https://www.reddit.com/r/StableDiffusion/comments/xgu2uo/the_real_fight_over_ai_art/)

* [Rutkowski battling AI art overlord | Reddit](https://www.reddit.com/r/StableDiffusion/comments/xgv0dw/rutkowski_battling_ai_art_overlord/)

* [Instead of mining cryptocoins with GPUs, are we now mining art? | Reddit](https://www.reddit.com/r/StableDiffusion/comments/xg8s8e/instead_of_mining_cryptocoins_with_gpus_are_we/) 

* [Using AI to create art is NOT art! | Reddit : ArtistLounge](https://www.reddit.com/r/ArtistLounge/comments/xczk89/using_ai_to_create_art_is_not_art/) 

* [Appreciating the Poetic Misunderstandings of A.I. Art | The New Yorker](https://www.newyorker.com/culture/infinite-scroll/appreciating-the-poetic-misunderstandings-of-ai-art?s=09)



## Critical Views about Generative AI



* [Why handing over total control to AI agents would be a huge mistake | MIT Technology Review](https://www.technologyreview.com/2025/03/24/1113647/why-handing-over-total-control-to-ai-agents-would-be-a-huge-mistake)

* [Collection of "The Most Thoughtful Writing about Generative AI" by Eryk Salvaggio](https://bsky.app/profile/eryk.bsky.social/post/3lccavgstkk2s)

* [AI Snake Oil: Separating Hype from Reality | TechPolicy.Press](https://www.techpolicy.press/ai-snake-oil-separating-hype-from-reality/) 

* [Deconstructing the AI Myth: Fallacies and Harms of Algorithmification](https://www.researchgate.net/publication/382802495_Deconstructing_the_AI_Myth_Fallacies_and_Harms_of_Algorithmification) 

* [Challenging The Myths of Generative AI | TechPolicy.Press](https://www.techpolicy.press/challenging-the-myths-of-generative-ai/) 

* [I am tired of AI | On Test Automation](https://www.ontestautomation.com/i-am-tired-of-ai/) 

* [Critique of Generative AI Can Harm Learning Study Design  by Steffi Tan, Vaikunthan Rajaratnam :: SSRN](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4898213)

* [Generative AI Can Harm Learning by Hamsa Bastani, Osbert Bastani, Alp Sungu, Haosen Ge, Özge Kabakcı, Rei Mariman :: SSRN](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4895486) 

* [I Taught for Most of My Career. I Quit Because of ChatGPT | TIME](https://time.com/7026050/chatgpt-quit-teaching-ai-essay/) 

* [AI Risks that Could Lead to Catastrophe | CAIS](https://www.safe.ai/ai-risk) 

* [The AI Risk Repository](https://airisk.mit.edu/)

* [[2406.17864] AI Risk Categorization Decoded (AIR 2024)](https://www.arxiv.org/abs/2406.17864): From Government Regulations to Corporate Policies

* ["AI for Good" Campaigns Are the Wrong Approach - IEEE Spectrum](https://spectrum.ieee.org/ai-for-good) 

* [Generative AI is not the panacea we’ve been promised | Eric Siegel for Big Think+ - YouTube](https://www.youtube.com/watch?v=B2zCWJBnfuE) 

* [Thoughts on GenAI by James Gosling](https://www.linkedin.com/pulse/thoughts-genai-james-gosling-nab0c/) 

* [Automated Social Science: Language Models as Scientist and Subjects | NBER](https://www.nber.org/papers/w32381) 

* [When Will the GenAI Bubble Burst? - by Gary Marcus](https://garymarcus.substack.com/p/when-will-the-genai-bubble-burst) 

* [Nightshade, the tool that ‘poisons’ data, gives artists a fighting chance against AI | TechCrunch](https://techcrunch.com/2024/01/26/nightshade-the-tool-that-poisons-data-gives-artists-a-fighting-chance-against-ai/)

* [How AI Fails Us | Edmond & Lily Safra Center for Ethics](https://ethics.harvard.edu/how-ai-fails-us) 

* [Generative AI Has a Visual Plagiarism Problem - IEEE Spectrum](https://spectrum.ieee.org/midjourney-copyright): "Experiments with Midjourney and DALL-E 3 show a copyright minefield"

* [[2308.03762] GPT-4 Can't Reason](https://arxiv.org/abs/2308.03762): "despite the genuinely impressive improvement, there are good reasons to be highly skeptical of GPT-4's ability to reason"

* [Risk and Harm: Unpacking Ideologies in the AI Discourse | Proceedings of the 5th International Conference on Conversational User Interfaces](https://dl.acm.org/doi/10.1145/3571884.3603751) 

* [[2305.18654] Faith and Fate: Limits of Transformers on Compositionality](https://arxiv.org/abs/2305.18654) 

* [[2210.02667] A Human Rights-Based Approach to Responsible AI](https://arxiv.org/abs/2210.02667)

* [On the Dangers of Stochastic Parrots | Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency](https://dl.acm.org/doi/10.1145/3442188.3445922) 

* [This new data poisoning tool lets artists fight back against generative AI | MIT Technology Review](https://www.technologyreview.com/2023/10/23/1082189/data-poisoning-artists-fight-generative-ai/) 

* [The Short-Term Effects of Generative Artificial Intelligence on Employment: Evidence from an Online Labor Market by Xiang Hui, Oren Reshef, Luofeng Zhou :: SSRN](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4527336) 

* [AI in Education Group Meeting Notes - Google Docs](https://docs.google.com/document/d/1PPHwa3KmoeRZwaoxjOS568aF2E-kUngOA2oI45G2Iaw/edit)

* [Syllabi Policies for AI Generative Tools - Google Docs](https://docs.google.com/document/d/1RMVwzjc1o0Mi8Blw_-JUTcXv02b2WRH86vw7mi16W3U/edit#heading=h.1cykjn2vg2wx) 

* [Five takeaways from UK’s AI safety summit at Bletchley Park | Artificial intelligence (AI) | The Guardian](https://www.theguardian.com/technology/2023/nov/02/five-takeaways-uk-ai-safety-summit-bletchley-park-rishi-sunak) 

* [Frontier AI: capabilities and risks – discussion paper - GOV.UK](https://www.gov.uk/government/publications/frontier-ai-capabilities-and-risks-discussion-paper) 

* [AI Safety Summit Policy Updates | AISS 2023](https://www.aisafetysummit.gov.uk/policy-updates/#company-policies) 

* [Responsible enterprise decisions with knowledge-enriched generative AI | Deloitte Netherlands](https://www.deloitte.com/nl/en/services/risk-advisory/perspectives/responsible-enterprise-decisions-knowledge-enriched-ai.html)

* [[2310.13149] Understanding Generative AI in Art: An Interview Study with Artists on G-AI from an HCI Perspective](https://arxiv.org/abs/2310.13149) 

* [[2309.12338] Artificial Intelligence and Aesthetic Judgment](https://arxiv.org/abs/2309.12338): "as generative AI influences contemporary aesthetic judgment we outline some of the pitfalls and traps in attempting to scrutinize what AI generated media means"

* [AI Worship | Marginal REVOLUTION](https://marginalrevolution.com/marginalrevolution/2023/10/ai-worship.html) 

* [Artificial intelligence technology behind ChatGPT was built in Iowa — with a lot of water | AP News](https://apnews.com/article/chatgpt-gpt4-iowa-ai-water-consumption-microsoft-f551fde98083d17a7e8d904f8be822c4) 

* [ChatGPT is fun, but not an author | Science](https://www.science.org/doi/10.1126/science.adg7879) 

* [Behind the AI boom, an army of overseas workers in ‘digital sweatshops’ | The Washington Post](https://www.washingtonpost.com/world/2023/08/28/scale-ai-remotasks-philippines-artificial-intelligence/): Scale AI’s Remotasks workers in the Philippines cry foul over low pay

* [It’s Not Intelligent If It Always Halts: A Critical Perspective on Current Approaches to AGI | Life Is Computation](https://www.lifeiscomputation.com/it-is-not-intelligent-if-it-always-halts/) 

* [The human costs of the AI boom | TechCrunch](https://techcrunch.com/2023/08/21/the-human-costs-of-the-ai-boom/) 

* [AI Scams, Spam, Hacking, Are Ruining the Internet](https://www.businessinsider.com/ai-scam-spam-hacking-ruining-internet-chatgpt-privacy-misinformation-2023-8) 

* [The ChatGPT revolution is another tech fantasy](https://www.disconnect.blog/p/the-chatgpt-revolution-is-another) 

* [Why AI Will Save the World | Andreessen Horowitz](https://a16z.com/2023/06/06/ai-will-save-the-world/) 

* [Hollywood studios proposed AI contract that would give them likeness rights ‘for the rest of eternity’ - The Verge](https://www.theverge.com/2023/7/13/23794224/sag-aftra-actors-strike-ai-image-rights) 

* [The shady world of Brave selling copyrighted data for AI training](https://stackdiary.com/brave-selling-copyrighted-data-for-ai-training/) 

* [Inside the AI Factory: the humans that make tech seem human - The Verge](https://www.theverge.com/features/23764584/ai-artificial-intelligence-data-notation-labor-scale-surge-remotasks-openai-chatbots?s=08)

* [Why transformative artificial intelligence is really, really hard to achieve](https://thegradient.pub/why-transformative-artificial-intelligence-is-really-really-hard-to-achieve/) 

* [AI and the automation of work — Benedict Evans](https://www.ben-evans.com/benedictevans/2023/7/2/working-with-ai) 

* [Yuval Noah Harari argues that AI has hacked the operating system of human civilisation](https://www.economist.com/by-invitation/2023/04/28/yuval-noah-harari-argues-that-ai-has-hacked-the-operating-system-of-human-civilisation) 

* [Generative AI Takes Stereotypes and Bias From Bad to Worse](https://www.bloomberg.com/graphics/2023-generative-ai-bias/) 

* [Governance of superintelligence by OpenAI](https://openai.com/blog/governance-of-superintelligence) 

* [AIAAIC - AIAAIC Repository](https://www.aiaaic.org/aiaaic-repository): "The independent, open, public interest resource detailing incidents and controversies driven by and relating to artificial intelligence, algorithms, and automation"

* [Just Calm Down About GPT-4 Already - IEEE Spectrum](https://spectrum.ieee.org/gpt-4-calm-down) 

* [Pause Giant AI Experiments: An Open Letter - Future of Life Institute](https://futureoflife.org/open-letter/pause-giant-ai-experiments/) 

* ["OpenAI released plugins for ChatGPT"](https://twitter.com/thealexbanks/status/1639620659142881283): tweet from [@thealexbanks](https://twitter.com/thealexbanks) with a list of reflections about the impact of ChatGPT plugins

* [Is a socially fair Artificial Intelligence possible? | Uma Inteligência Artificial socialmente justa é possível?](https://www.mabuse.art.br/post/uma-intelig%C3%AAncia-artificial-socialmente-justa-%C3%A9-poss%C3%ADvel): post in Portuguese by H.D. Mabuse

* [Noam Chomsky on ChatGPT: It's "Basically High-Tech Plagiarism" and "a Way of Avoiding Learning" | Open Culture](https://www.openculture.com/2023/02/noam-chomsky-on-chatgpt.html)

* [Despite Their Feats, Large Language Models Still Haven't Contributed to Linguistics | Towards Data Science](https://towardsdatascience.com/despite-their-feats-large-language-models-still-havent-contributed-to-linguistics-657bea43a8a3) 

* [Will ChatGPT Kill the Student Essay? | The Atlantic](https://www.theatlantic.com/technology/archive/2022/12/chatgpt-ai-writing-college-student-essays/672371/)

* [What ChatGPT and generative AI mean for science | Nature](https://www.nature.com/articles/d41586-023-00340-6)

* [ChatGPT Is a Bullshit Generator Waging Class War](https://www.vice.com/en/article/akex34/chatgpt-is-a-bullshit-generator-waging-class-war) 

* [Some thoughts about generative AI and the future of education – Mark Carrigan](https://markcarrigan.net/2023/01/15/some-thoughts-about-generative-ai-and-the-future-of-education/) 

* [Educator Considerations for ChatGPT - OpenAI API](https://platform.openai.com/docs/chatgpt-education) 

* [Stable Diffusion Frivolous · Because lawsuits based on ignorance deserve a response.](http://www.stablediffusionfrivolous.com/): a community response for the "Stable Diffusion litigation"

* [Stable Diffusion litigation · Joseph Saveri Law Firm & Matthew Butterick](https://stablediffusionlitigation.com/)

* [Generative Language Models and Automated Influence Operations: Emerging Threats and Potential Mitigations | OpenAI](https://cdn.openai.com/papers/forecasting-misuse.pdf) 

* [Abstracts written by ChatGPT fool scientists](https://www.nature.com/articles/d41586-023-00056-7) 

* [When Machines Change Art | Aaron Hertzmann’s blog](https://aaronhertzmann.com/2022/12/17/when-tech-changes-art.html)

* [The Dark Risk of Large Language Models | WIRED UK](https://www.wired.co.uk/article/artificial-intelligence-language)

* [ChatGPT, DALL-E 2 and the collapse of the creative process](https://theconversation.com/chatgpt-dall-e-2-and-the-collapse-of-the-creative-process-196461)

* [What AI-Generated Art Really Means for Human Creativity | WIRED](https://www.wired.com/story/picture-limitless-creativity-ai-image-generators/)

* [Forecasting Potential Misuses of Language Models for Disinformation Campaigns—and How to Reduce Risk](https://openai.com/blog/forecasting-misuse/) 

* [The Dark Side of AI Art: 4 Potential Issues With the Growing Trend](https://www.makeuseof.com/dark-side-of-ai-art-potential-issues/) 

* [Armed With ChatGPT, Cybercriminals Build Malware And Plot Fake Girl Bots](https://www.forbes.com/sites/thomasbrewster/2023/01/06/chatgpt-cybercriminal-malware-female-chatbots/?sh=6019f4315534)

* [ChatGPT And The Mass Production Of Office Work - Farsight](https://farsight.cifs.dk/chatgpt-and-the-mass-production-of-office-work/)

* [The Danger Of ChatGPT Nobody Talks About | by Jacob Ferus | Dec, 2022 | Medium](https://medium.com/@dreamferus/the-danger-of-chatgpt-nobody-talks-about-9aff94e5dea6)

* [Mind Control in the Metaverse. If we’ve learned anything about… | by Louis Rosenberg | Predict | Dec, 2022 | Medium](https://medium.com/predict/mind-control-in-the-metaverse-48dfbd88c2ae)

* [The Brilliance and Weirdness of ChatGPT - The New York Times](https://www.nytimes.com/2022/12/05/technology/chatgpt-ai-twitter.html)

* [Como o texto gerado por Inteligência Artificial está envenenando a Internet - MIT Technology Review](https://mittechreview.com.br/como-o-texto-gerado-por-inteligencia-artificial-esta-envenenando-a-internet/)

* [O ChatGPT é o momento “Jurassic Park” da inteligência artificial - NeoFeed](https://neofeed.com.br/blog/home/o-chatgpt-e-o-momento-jurassic-park-da-inteligencia-artificial/)

* [Por favor, mais racionalidade e menos frenesi em relação ao chatGPT (Parte 1 de 2) | by Cezar Taurion | Dec, 2022 | Medium](https://c-taurion.medium.com/por-favor-mais-racionalidade-e-menos-frenesi-em-rela%C3%A7%C3%A3o-ao-chatgpt-parte-1-de-2-1d7637e2a854)

* [E se estivermos usando uma IA pseudocientífica? - Diogo Cortiz](https://diogocortiz.com.br/computacao-afetiva-e-os-desafios-das-ias-pseudocientificas/)

* [As limitações da sensação tecnológica de 2023: o ChatGPT | IAgora? | Época NEGÓCIOS](https://epocanegocios.globo.com/colunas/iagora/coluna/2023/01/as-limitacoes-da-sensacao-tecnologica-de-2023-o-chatgpt.ghtml)

* [7 Revealing Ways AIs Fail - IEEE Spectrum](https://spectrum.ieee.org/ai-failures) 



## Generative AI Processes and Artifacts






More info



**Generative AI** is a branch of artificial intelligence that focuses on creating new data based on patterns learned from existing data. Here's a step-by-step explanation of the process:



1. **Starting with Data**: Every Generative AI process begins with data. This can be in various forms such as text, images, sounds, or other datasets. This data serves as the foundational material that the AI uses to recognize and understand patterns.



2. **Training the AI**: With the data in hand, the next step is 'training'. During this phase, the AI processes the data multiple times to learn and internalize the patterns present. The outcome of this stage is a 'model', which acts like a digital representation of the knowledge derived from the data.



3. **Fine-Tuning**: At times, there's a need for the AI to focus on specific nuances or characteristics. In such cases, an additional set of data is used to 'fine-tune' the already trained model, enhancing its capabilities in the desired direction.



4. **Using the Model**: After training, the model is prepared to make inferences, which means using its acquired knowledge to process new data and come up with relevant outputs. This inference process can be executed locally on a machine or can be accessed remotely through an 'API'. The choice between local execution and API access often depends on factors like computational resources, application needs, and user preferences. Whether locally or via an API, the goal is to leverage the model's capabilities to derive meaningful results from new data inputs.



5. **Generating New Data**: With the model set up, the AI can now produce or 'generate' new data. By giving the AI certain 'input parameters' or guidelines, it returns with 'generated output', which is the newly created content.



6. **Applications**: The output generated by the AI can be incorporated into a range of applications, be it websites, mobile apps, or other digital platforms. The 'interface' refers to the user-facing portion of these applications, enabling users to interact with and benefit from the AI's capabilities.



In essence, Generative AI is about feeding an AI system vast amounts of data, training it to grasp underlying patterns, and then utilizing that trained knowledge to produce novel data. The potential applications and benefits of this technology are vast and continue to grow as the field evolves.



## Generative AI Tools Directories



* [AI Presentation Makers](https://www.aipresentationmakers.com/): In-depth reviews of dozens of AI presentation makers

* [A.I. Productivity Tools](https://www.aiproductivitytoolkit.com/) 

* [ToolList.ai](https://toollist.ai/): AI Tools Aggregator

* [Toolify](https://www.toolify.ai/): AI Tools Directory & AI Tools List

* [LLM Explorer](https://llm.extractum.io/): A Curated LLM List. Explore LLM List of the Open-Source LLM Models

* [OrbicAI](https://orbic.ai/): "The Larget AI Directory, GPT Stores, AWS PartyRocks Apps and Lots of Free AI Tools"

* [Altern](https://altern.ai/): "Gateway to AI Discoveries"

* [ainave](https://www.ainave.com): "navigate the world of AI with ease", curated AI Tools and AI News

* [AI Search](https://ai-search.io): Find AI Tools & Apps | Search The Most Complete AI Tools Directory | AI Search

* [AiSuperSmart Ai Tool Directory](https://aisupersmart.com/ai-tools-directory/): Find Ai Tools According to your Use Cases!

* [HD Robots](https://hdrobots.com/): AI tools directory with chatbot assistant

* [AIForme](https://www.aiforme.wiki/): AI tools discovery platform with comparison feature

* [Technologies in LabLab](https://lablab.ai/tech): list of AI tools suggested by [lablab.ai](https://lablab.ai) for their hackathons

* [Vondy - Next Generation AI Apps](https://www.vondy.com/): collection of AI tools organized by tasks 

* [AI Tool Master List](https://doc.clickup.com/25598832/d/h/rd6vg-14247/0b79ca1dc0f7429/rd6vg-12207): directory maintained by ClickUp

* [AI Valley](https://aivalley.ai/): "The Newest AI Tools And Prompts"

* [AI Finder](https://ai-finder.net/): repository with more than 1500 AI tools 

* [BestWebbs](https://bestwebbs.com/): "one-stop destination for all AI Tools"

* [Future Tools - Find The Exact AI Tool For Your Needs](https://www.futuretools.io/): list of AI tools

* [Futurepedia - The Largest AI Tools Directory | Home](https://www.futurepedia.io/): directory of AI tools

* [There's An AI For That](https://theresanaiforthat.com/): AI database

* [AI Depot - Discover New AI Tools](https://aidepot.co/): collection of AI tools organized by tags and presented in a card format

* [Generative AI Database](https://aaronsim.notion.site/Generative-AI-Database-Types-Models-Sector-URL-API-more-b5196c870594498fb1e0d979428add2d): a database in Notion with types, models, sectors, URLs, and APIs

* [Altern](https://altern.ai) - The place to discover new AI tools and products.

* [The Generative AI Landscape](https://ai-collection.org/): "a collection of awesome generative AI applications"

* [The ultimate list of AI tools for creators | Descript](https://www.descript.com/blog/article/the-ultimate-list-of-ai-tools-for-creators): collection organized by Descript

* [Maxim AI](https://www.getmaxim.ai): a generative AI evaluation and observability platform

* [AI Tool List](https://www.aitoollist.org): An awesome directory of AI tools



## Courses and Educational Materials



* [Gemini by Example](https://geminibyexample.com): Learn the Gemini SDK through (annotated) code examples.

* [Niraj-Lunavat/Artificial-Intelligence](https://github.com/Niraj-Lunavat/Artificial-Intelligence?tab=readme-ov-file#researchers): Awesome AI Learning with +100 AI Cheat-Sheets, Free online Books, Top Courses, Best Videos and Lectures, Papers, Tutorials, +99 Researchers, Premium Websites, +121 Datasets, Conferences, Frameworks, Tools

* [Generative AI Explained by NVIDIA](https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+S-FX-07+V1): A no-coding course by NVIDIA that presents Generative AI concepts and applications, as well as the challenges and opportunities in the field 

* [Paulescu/hands-on-rl: Free course that takes you from zero to Reinforcement Learning PRO 🦸🏻‍🦸🏽](https://github.com/Paulescu/hands-on-rl) 

* [DataCamp's Become a Generative AI Developer series](https://www.datacamp.com/ai-code-alongs): 9 code-alongs on building chatbots using LangChain and the OpenAI and Pinecone APIs, and working with the Hugging Face ecosystem. Free, for a limited time only.

* [rasbt/LLMs-from-scratch](https://github.com/rasbt/LLMs-from-scratch): Implementing a ChatGPT-like LLM from scratch, step by step

* [Introduction to Generative AI | SqillPlan](https://sqillplan.com/course?hash=-4862018582618510846): introduction to Generative AI, including models such as GANs, Variational Autoencoders, Autoregressive Models, and their applications, evaluation, ethics, and challenges

* [udlbook/udlbook](https://github.com/udlbook/udlbook): Understanding Deep Learning by Professor Simon J.D. Prince

* [Book: Understanding Deep Learning](https://udlbook.github.io/udlbook/): website with the book draft and Google Colabs of the book by Simon J.D. Prince

* [List of Generative AI Learning resources from AWS and Google](https://www.linkedin.com/posts/aagarwal29_generativeai-learn-aws-activity-7081761811129118720-i128/): list organized as a LinkedIn post by Ankit Agarwal

* [How AI chatbots like ChatGPT or Bard work – visual explainer | The Guardian](https://www.theguardian.com/technology/ng-interactive/2023/nov/01/how-ai-chatbots-like-chatgpt-or-bard-work-visual-explainer) 

* [🔥🔥] [Generative AI for Beginners](https://microsoft.github.io/generative-ai-for-beginners/#/): introductory 12 lesson course by Microsoft

* [Introduction to Generative AI](https://www.linkedin.com/posts/youssef-hosni-b2960b135_if-you-want-to-start-studying-generative-activity-7125908710702350336-vhsm/): series of Medium articles by Youssef Hosni

* [Animated AI](https://animatedai.github.io/): animations and instructional videos about neural networks

* [Deep Learning AI - Learn the fundamentals of generative AI for real-world applications](https://www.deeplearning.ai/courses/generative-ai-with-llms/): created in partnership with AWS, this course presents the fundamentals of how generative AI works and how to deploy it in real-world applications.

* [Google Cloud Skills Boost - Introduction to Generative AI](https://www.cloudskillsboost.google/course_templates/536): an introductory level microlearning course covering Google Tools aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods.

* [Google Cloud Skills Boost: Generative AI learning path](https://www.cloudskillsboost.google/journeys/118): curated content on Generative AI "from the fundamentals of Large Language Models to how to create and deploy generative AI solutions on Google Cloud"

* [AI for Industrial Design](https://industrialdesign.ai/): "students at the National University of Singapore explore AI’s capability for design in a semester course and share what they learned. Directed by Donn Koh at the Division of Industrial Design, NUS."

* [Let Us Show You How GPT Works — Using Jane Austen - The New York Times](https://www.nytimes.com/interactive/2023/04/26/upshot/gpt-from-scratch.html) 

* [🔥🔥🔥] [ChatGPT Prompt Engineering for Developers - DeepLearning.AI](https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/): short course taught by Isa Fulford (OpenAI) and Andrew Ng (DeepLearning.AI) that provide best practices for prompt engineering

* [🔥🔥🔥] [DAIR.AI](https://github.com/dair-ai): Democratizing Artificial Intelligence Research, Education, and Technologies

* [Welcome to the 🤗 Deep Reinforcement Learning Course](https://huggingface.co/deep-rl-course/unit0/introduction?fw=pt): a Hugging Face Course on Deep Reinforcement Learning

* [Crash course in AI art generation by PromptHero](https://prompthero.com/academy): paid ($99) course focused on prompt engineering

* [Visual intuition for diffusion models and AI art. #stablediffusionart #aiart #aiartwork #aiartcommunity](https://www.tiktok.com/@ham_made_art/video/7154863972729113899) 

* [The Illustrated Stable Diffusion by Jay Alammar](https://jalammar.github.io/illustrated-stable-diffusion/): "gentle introduction [on] how Stable Diffusion works"

* [🔥][johnowhitaker/tglcourse](https://github.com/johnowhitaker/tglcourse): The Generative Landscape - a course on generative modelling (currently unfinished)

* [Words are Images | BustBright - Machine Learning Art](https://www.bustbright.com/product/words-are-images-7-week-online-class-starting-october-24th-2022-/331): 7-week Online class starting October 24th, 2022 by [Derrick Schultz](https://twitter.com/dvsch/)

* [Grokking Stable Diffusion.ipynb - Colaboratory - Part 1](https://colab.research.google.com/drive/1dlgggNa5Mz8sEAGU0wFCHhGLFooW_pf1?usp=sharing): notebook by [@johnowhitaker](https://twitter.com/johnowhitaker) exploring Stable Diffusion details

* [Grokking Stable Diffusion: Textual Inversion.ipynb - Colaboratory - Part 2](https://colab.research.google.com/drive/1RTHDzE-otzmZOuy8w1WEOxmn9pNcEz3u?usp=sharing): sequel to Grokking Stable Diffusion by [@johnowhitaker](https://twitter.com/johnowhitaker) that focus on Text Inversion

* [GitHub - johnowhitaker/aiaiart](https://github.com/johnowhitaker/aiaiart): Course content and resources for the AIAIART course

* [Implementation/tutorial of stable diffusion with side-by-side notes by labml.ai | Twitter](https://twitter.com/labmlai/status/1571080112459878401)

* [Practical Deep Learning for Coders 2023 - Part II](https://www.youtube.com/watch?v=_7rMfsA24Ls&list=PLfYUBJiXbdtRUvTUYpLdfHHp9a58nWVXP): continuation of the course focusing on the implementation of Stable Diffusion from scratch.

* [Practical Deep Learning for Coders 2022 - Part I](https://www.youtube.com/playlist?list=PLfYUBJiXbdtSvpQjSnJJ_PmDQB_VyT5iU): "free course designed for people with some coding experience who want to learn how to apply deep learning and machine learning to practical problems" by Jeremy Howard



## Human-AI Interaction



* [UX for AI: How to Power Human Experiences with AI - Design Tool Tuesday - YouTube](https://www.youtube.com/watch?v=50Of7_lubN4) 

* [Behind-the-Design: Meet Copilot by Microsoft Design](https://medium.com/microsoft-design/behind-the-design-meet-copilot-2c68182a0e70) 

* [🔥🔥🔥] [[2310.07127] An HCI-Centric Survey and Taxonomy of Human-Generative-AI Interactions](https://arxiv.org/abs/2310.07127): "a survey of 154 papers, providing a novel taxonomy and analysis of Human-GenAI Interactions from both human and Gen-AI perspectives".

* [Guidelines for Human-AI Interaction - Microsoft Research](https://www.microsoft.com/en-us/research/publication/guidelines-for-human-ai-interaction/): a set of "18 generally applicable design guidelines for human-AI" interaction



## Papers Collection



* [Paper Digest - ChatGPT](https://www.paperdigest.org/2023/01/recent-papers-on-chatgpt/): Recent Papers on ChatGPT

* [dair-ai/ML-Papers-Explained](https://github.com/dair-ai/ML-Papers-Explained): Explanation to key concepts in ML

* [AI Reading List - Google Docs](https://docs.google.com/document/d/1bEQM1W-1fzSVWNbS4ne5PopB2b7j8zD4Jc3nm4rbK-U/edit): reading list organized by [Jack Soslow (@JackSoslow)](https://twitter.com/JackSoslow) 

* [Aman's AI Journal • Papers List](https://aman.ai/papers/): set of seminal AI/ML papers curated by Aman Chadha

* [Casual GAN Papers Reading Club](https://casualgan.notion.site/casualgan/Casual-GAN-Papers-Reading-Club-327c158518e44d5296a5def74486c7e8): Community knowledge base for Casual GAN Papers

* [Casual GAN Papers](https://www.casualganpapers.com/): Easy to read summaries of popular AI papers

* [The Illustrated VQGAN](https://ljvmiranda921.github.io/notebook/2021/08/08/clip-vqgan/): illustrated explanation on how VQGAN works

* [CLIP: Connecting Text and Images](https://openai.com/blog/clip/): OpenAI's explanation on how CLIP works

* [VQGAN+CLIP — How does it work?. The synthetic imagery (“GAN Art”) scene… | by Alexa Steinbrück | Medium](https://alexasteinbruck.medium.com/vqgan-clip-how-does-it-work-210a5dca5e52)

* [The Methods Corpus | Papers With Code](https://paperswithcode.com/methods)

* https://ieeexplore.ieee.org/abstract/document/9043519: A State-of-the-Art Review on Image Synthesis With Generative Adversarial Networks

* [Utilizando redes adversárias generativas (GANs) como agente de apoio à inspiração para artistas](https://www.cin.ufpe.br/~tg/2020-1/TG_CC/tg_cco2.pdf): Trabalho de Graduação de Cláudio Carvalho no Centro de Informática - UFPE

* [GAN Lab](https://poloclub.github.io/ganlab/): Play with Generative Adversarial Networks in Your Browser!

* [[PDF] Music2Video: Automatic Generation of Music Video with fusion of audio and text | Semantic Scholar](https://www.semanticscholar.org/paper/Music2Video%3A-Automatic-Generation-of-Music-Video-of-Jang-Shin/38e37c3a7dc22bb3356552e93e6685b99ca04264)

* [[PDF] Active Divergence with Generative Deep Learning - A Survey and Taxonomy | Semantic Scholar](https://www.semanticscholar.org/paper/Active-Divergence-with-Generative-Deep-Learning-A-Broad-Berns/091c4ea2efaba23cd9024d8a063609c9a313b5cb)

* [[PDF] Automating Generative Deep Learning for Artistic Purposes: Challenges and Opportunities | Semantic Scholar](https://www.semanticscholar.org/paper/Automating-Generative-Deep-Learning-for-Artistic-Berns-Broad/f3479740d4ec7f91b6d7a01167e9c875a72d386e)



## Online Tools and Applications



* [Lunroo](https://lunroo.com): 45+ Free AI Tools for Social Media Marketing. Save your time on routine tasks using AI.

* [COUNT](https://getcount.com): AI-powered accounting for small businesses

* [Competitor Research](https://www.competitoresearch.com): AI tool to help companies track their competitors

* [StartKit.AI](https://startkit.ai): Boilerplate for quickly building AI products

* [No-Code Scraper](https://www.nocodescraper.com/): Data Scraping without Code - Seamlessly extract data from any website with just a few simple inputs.

* [BacklinkGPT](https://www.backlinkgpt.com/): AI-powered link-building platform that helps you generate personalized outreach messages for faster link building.

* [VocalReplica](https://vocalreplica.com/): AI-Powered Vocal and Instrumental Isolation for Your Favorite Tracks

* [LangMagic](https://easytolearn.io): Learn languages from native content.

* [Persuva](https://persuva.ai): Persuva is the AI-driven platform to create persuasive, high-converting ad copy at scale.

* [Dittto.ai](https://dittto.ai): Fix your hero copy with an AI trained on top SaaS websites.

* [SEOByAI](https://seoby.ai): Rank Faster on Google with FREE AI SEO Tools

* [SinglebaseCloud](https://singlebase.cloud): AI-powered backend platform with Vector DB, DocumentDB, Auth, and more to speed up app development.

* [TrollyAI](https://trolly.ai/): Create professional SEO articles, 2x faster

* [WebscrapeAI](https://webscrapeai.com/): Scrape any website without code using AI

* [Architecture Helper](https://architecturehelper.com): Analyze any building architecture, and generate your own custom styles, in seconds.

* [AI-Flow](https://ai-flow.net/): Connect multiple AI models easily

* [Code to Flow](https://codetoflow.com): Visualize, Analyze, and Understand Your Code flow. Turn Code into Interactive Flowcharts with AI. Simplify Complex Logic Instantly.

* [Recast Studio](https://recast.studio): AI-powered podcast marketing assistant.

* [Clipwing](https://clipwing.pro/): A tool for cutting long videos into dozens of short clips.

* [Tailor](https://www.usetailor.com): Get a daily podcast and newsletter, created for you by an AI

* [ZZZ Code AI](https://zzzcode.ai/): AI-powered free website to get any programming question answered or code generated.

* [Scribble Diffusion](https://scribblediffusion.com/): turn your sketch into a refined image using AI

* [Paint by Text](https://paintbytext.chat/): Edit your photos using written instructions, with the help of an AI.

* [Scenario AI](https://www.scenario.gg/): AI-generated game assets

* [AnimalAI](https://animalai.co/): custom AI-generated animal portraits (profits are directed to various wildlife conservation organizations)

* [starryai](https://www.starryai.com/): AI Art Generator App - AI Art Maker

* [ProsePainter](https://www.prosepainter.com/): an interactive tool to "paint with words." It incorporates guidable text-to-image generation into a traditional digital painting interface

* [ProsePainter: Image + Sketching Interface + CLIP! - YouTube](https://www.youtube.com/watch?v=mK4F32xNrdw&t=429s)

* [Cocreator AI](https://cocreator.ai/): creative computer agent (in wait list)

* [Runway ML](http://runwayml.com/): AI video creation suite

* [Hotpot.ai - Hotpot.ai](https://hotpot.ai/): set of AI Tools to post-process images

* [Toonify yourself by Justin Pinkney](https://www.justinpinkney.com/toonify-yourself/): turn a human face into a cartoon

* [deepart.io](https://deepart.io/): a online tool for applying style transfer

* [Artbreeder](https://www.artbreeder.com/): web-based tool to generate images by breeding existing images

* [Ostagram.ru](https://www.ostagram.me/): image style transfer plataform

* [cleanup.pictures](https://cleanup.pictures/): remove objects, people, text and defects from any picture for free

* [remove.bg](https://www.remove.bg/): remove background from images

* [Quick, Draw!](https://quickdraw.withgoogle.com/): can a neural network learn to recognize doodling? A game to help NL by adding users drawing

* [Nekton.ai](https://nekton.ai/): automate your workflows with AI

* [Documind.chat](https://documind.chat): Chat with PDF using AI. Documind is a powerful chat with pdf tool that lets you ask questions from your pdf documents.

* [Snowpixel](https://snowpixel.app): Generate Images/Videos/Animations/Audio/Music/3D Objects with Text and/or Image. Upload your own data to create custom models.

* [Chatpdf.so](https://chatpdf.so): Talk to PDF using GPT4 AI. Chatpdf.so is a chatpdf tool that lets you do question answering on your pdf documents.

* [Yona.ai](https://yona.ai): Create deeply personalized AI chatbots from your own conversations, your stories, your data. You can harness the power of your chat history to build an AI companion for a nostalgic trip down memory lane, whimsical fantasies, or any other unique purpose.

* [Voicesphere](https://www.voicesphere.co/): Chat with your documents to get intelligent, context specific answers.

* [Tune AI](https://chat.tune.app/): AI chat app powered by open source models

* [GPT Mobile](https://github.com/Taewan-P/gpt_mobile) GPT Mobile is an Android app that can chat with multiple LLMs at once! Currently supports ChatGPT, Anthropic Claude, and Google Gemini.

* [PageGen](https://pagegen.ai) - An AI Page Generator with Claude AI, React and Shadcn UI. Generate web pages from text, screenshot and templates with one click.

* [PerchanceStory](https://perchancestory.com/): PerchanceStory is an AI-based interactive story generator, which generates ever-changing story endings with endless possibilities based on simple user-provided input. 



# Code and Programming



## Vibe Coding



* [filipecalegario/awesome-vibe-coding](https://github.com/filipecalegario/awesome-vibe-coding): A curated list of vibe coding references, colaborating with AI to write code.

* [Andrej Karpathy on X](https://x.com/karpathy/status/1886192184808149383): "There's a new kind of coding I call "vibe coding", where you fully give in to the vibes, embrace exponentials, and forget that the code even exists."

* [Windsurf Editor by Codeium](https://codeium.com/windsurf): agentic IDE, "where the work of developers and AI truly flow together, allowing for a coding experience that feels like literal magic"

* [Bolt.new](https://bolt.new/): Prompt, run, edit, and deploy full-stack web and mobile apps.

* [Lovable](https://lovable.dev/): "Idea to app in seconds. Lovable is your superhuman full stack engineer."

* [v0 by Vercel](https://v0.dev/chat): assistant to build NextJS frontend

* [Cursor](https://www.cursor.com/): The AI Code Editor, "the best way to code with AI"

* [Replit](https://replit.com/): "Simply describe your idea above and let the Agent build it for you"



## AI-Powered Code Generation



* [batchai](https://github.com/qiangyt/batchai): A supplement to Copilot and Cursor - utilizes AI for batch processing of project codes

* [Archie](https://archie.8base.com/): AI-Driven Product Architect that Designs and Plans Software Applications

* [DhiWise](https://dhiwise.com): DhiWise is an app development platform that automates coding tasks, letting developers focus on core functionalities.

* [New study on coding behavior raises questions about impact of AI on software development – GeekWire](https://www.geekwire.com/2024/new-study-on-coding-behavior-raises-questions-about-impact-of-ai-on-software-development/) 

* [CostGPT: Software Development Cost Calculator](https://costgpt.ai/): "find the cost, time and the best tech stack for any kind of software, tools that you want to build using the power of AI"

* [codefuse-ai/Awesome-Code-LLM](https://github.com/codefuse-ai/Awesome-Code-LLM): a curated list of language modeling researches for code and related datasets.

* [tldraw/draw-a-ui](https://github.com/tldraw/draw-a-ui): draw a mockup and generate HTML for it

* [deepseek-ai/DeepSeek-Coder](https://github.com/deepseek-ai/DeepSeek-Coder): a tool that experiments the motto "let the code write itself"

* [Cody](https://about.sourcegraph.com/cody): AI coding assistant

* [Kombai](https://kombai.com/): generate UI code per component from Figma

* [geekan/MetaGPT](https://github.com/geekan/MetaGPT): the multi-agent framework that, give one line requirement, return PRD, design, tasks, repo

* [ZZZ Code AI](https://zzzcode.ai/): AI-powered free website to get any programming question answered or code generated.

* [Rapidpages](https://www.rapidpages.io/): create React & Tailwind landing pages using AI

* [Teaching Programming in the Age of ChatGPT – O’Reilly](https://www.oreilly.com/radar/teaching-programming-in-the-age-of-chatgpt/) 

* [GPT Web App Generator](https://magic-app-generator.wasp-lang.dev/): generates a webapp from a title, description, and other simple parameters

* [wolfia-app/gpt-code-search](https://github.com/wolfia-app/gpt-code-search/): search a codebase with natural language using AI

* [Dedicated File for Inbox for GenAI + Dev](https://github.com/filipecalegario/awesome-generative-ai/blob/main/inbox-gen-ai-dev.md): a list for further analysis and organization of GenAI + dev references 

* [e2b-dev/e2b](https://github.com/e2b-dev/e2b): "Open-source platform for building AI-powered virtual software developers"

* [Metabob](https://metabob.com/): Generative AI to improve and automate code reviews

* [gventuri/pandas-ai](https://github.com/gventuri/pandas-ai): Pandas AI is a Python library that integrates LLMs capabilities into Pandas, making dataframes conversational

* [A Systematic Evaluation of Large Language Models of Code](https://arxiv.org/abs/2202.13169): arxiv paper

* [pgosar/ChatGDB](https://github.com/pgosar/ChatGDB): "Harness the power of ChatGPT inside the GDB debugger"

* [The Impact of AI on Developer Productivity: Evidence from GitHub Copilot | arxiv](https://arxiv.org/abs/2302.06590) 

* [openai/openai-cookbook](https://github.com/openai/openai-cookbook): Examples and guides for using the OpenAI API

* [Reduce costs when prompting using GPT](https://www.codium.ai/blog/reduce-your-costs-by-30-when-using-gpt-3-for-python-code/)

* [Co-Developer GPT engine](https://github.com/stoerr/CoDeveloperGPTengine) - local r/w file access and execute actions from an OpenAI GPT

* [Potpie](https://potpie.ai) - Open Source AI Agents for your codebase in minutes. Use pre-built agents for Q&A, Testing, Debugging and System Design or create your own purpose-built agents.



# Text



## Everything to Markdown to LLMs



* [LLMSTXT.NEW](https://www.llmstxt.new/): Generate consolidated text files from websites for LLM training and inference – Powered by Firecrawl

* [Mistral OCR / Mistral AI](https://mistral.ai/news/mistral-ocr): A document understanding API

* [opendatalab/MinerU](https://github.com/opendatalab/MinerU): A high-quality tool for convert PDF to Markdown and JSON

* [microsoft/markitdown](https://github.com/microsoft/markitdown): Python tool for converting files and office documents to Markdown.

* [docling-project/docling](https://github.com/docling-project/docling): get your documents ready for gen AI

* [Firecrawl](https://www.firecrawl.dev/): Turn websites into LLM-ready data

* [CatchTheTornado/text-extract-api](https://github.com/CatchTheTornado/text-extract-api): document (PDF, Word, PPTX ...) extraction and parse API using OCRs + Ollama supported models. Anonymize documents. Remove PII. Convert any document or picture to structured JSON or Markdown

* [R Jina](https://r.jina.ai/): convert websites into Markdown by placing the URL in the search bar

* [Gitingest](https://gitingest.com/): turn any Git repository into a simple text digest of its codebase.

* [uithub](https://uithub.com/): convert GitHub repositories into Markdown by placing the URL in the search bar



## Small Language Models



* [[2409.15790] Small Language Models: Survey, Measurements, and Insights](https://arxiv.org/abs/2409.15790) 

* [[2402.17764] The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits](https://arxiv.org/abs/2402.17764) 

* [mbzuai-oryx/MobiLlama](https://github.com/mbzuai-oryx/MobiLlama): Small Language Model tailored for edge devices



## Large Language Models (LLMs)



* [lunary-ai/abso](https://github.com/lunary-ai/abso): TypeScript SDK to easily call 100+ LLMs using OpenAI's format

* [oumi-ai/oumi](https://github.com/oumi-ai/oumi): open universal machine intelligence, open-source platform that streamlines the entire lifecycle of foundation models - from data preparation and training to evaluation and deployment

* [🔥] [Transformer Explainer](https://poloclub.github.io/transformer-explainer/): LLM Transformer Model Visually Explained [YouTube Video](https://www.youtube.com/watch?v=ECR4oAwocjs) 

* [comet-ml/opik](https://github.com/comet-ml/opik): Evaluate, test, and ship LLM applications with a suite of observability tools to calibrate language model outputs across your dev and production lifecycle.

* [mendableai/firecrawl](https://github.com/mendableai/firecrawl): Turn entire websites into LLM-ready markdown or structured data. Scrape, crawl and extract with a single API.

* [QuivrHQ/MegaParse](https://github.com/quivrhq/megaparse): File Parser optimised for LLM Ingestion with no loss. Parse PDFs, Docx, PPTx in a format that is ideal for LLMs.

* [LiteLLM](https://www.litellm.ai/): a proxy server to manage auth, loadbalancing, and spend tracking across 100+ LLMs, all in the OpenAI format

* [youssefHosni/Hands-On-LangChain-for-LLM-Applications-Development](https://github.com/youssefHosni/Hands-On-LangChain-for-LLM-Applications-Development): Practical LangChain tutorials for LLM applications development

* [unclecode/crawl4ai: Crawl4AI](https://github.com/unclecode/crawl4ai): Open-source LLM Friendly Web Crawler & Scrapper

* [microsoft/LMOps](https://github.com/microsoft/LMOps): General technology for enabling AI capabilities w/ LLMs and MLLMs

* [F*** You, Show Me The Prompt](https://hamel.dev/blog/posts/prompt/): quickly understand inscrutable LLM frameworks by intercepting API calls

* [danielmiessler/fabric](https://github.com/danielmiessler/fabric): fabric is an open-source framework for augmenting humans using AI. It provides a modular framework for solving specific problems using a crowdsourced set of AI prompts that can be used anywhere.

* [Langfuse](https://langfuse.com/): Open source LLM engineering platform: Observability, metrics, evals, prompt management, playground, datasets. Integrates with LlamaIndex, Langchain, OpenAI SDK, LiteLLM, and more. [#opensource](https://github.com/langfuse/langfuse)

* [naklecha/llama3-from-scratch](https://github.com/naklecha/llama3-from-scratch): llama3 implementation one matrix multiplication at a time

* [[2405.03825] Organizing a Society of Language Models: Structures and Mechanisms for Enhanced Collective Intelligence](https://arxiv.org/abs/2405.03825) 

* [Open challenges in LLM research](https://huyenchip.com/2023/08/16/llm-research-open-challenges.html) 

* [stanfordnlp/dspy](https://github.com/stanfordnlp/dspy): DSPy: The framework for programming — not prompting — foundation models

* [Groq](https://groq.com/): service focused on fast inference speed, providing API access to Llama 2 70B-4K and Mixtral 8x7B-32K 

* [🔥🔥🔥] [LLMLingua](https://llmlingua.com/): Designing a Language for LLMs via **Prompt Compression**

* [Floom](https://github.com/FloomAI/Floom) AI gateway and marketplace for developers, enables streamlined integration of AI features into products

* [rasbt/LLMs-from-scratch](https://github.com/rasbt/LLMs-from-scratch): Implementing a ChatGPT-like LLM from scratch, step by step

* [GoogleCloudPlatform/generative-ai](https://github.com/GoogleCloudPlatform/generative-ai): Sample code and notebooks for Generative AI on Google Cloud

* [LLM Visualization](https://bbycroft.net/llm)

* [Automatic Hallucination detection with SelfCheckGPT NLI](https://huggingface.co/blog/dhuynh95/automatic-hallucination-detection) 

* [StreamingLLM gives language models unlimited context](https://bdtechtalks.com/2023/11/27/streamingllm/): giving language models unlimited context

* [iusztinpaul/hands-on-llms](https://github.com/iusztinpaul/hands-on-llms): learn about LLMs, LLMOps, and vector DBs for free by designing, training, and deploying a real-time financial advisor LLM system ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 𝘷𝘪𝘥𝘦𝘰 & 𝘳𝘦𝘢𝘥𝘪𝘯𝘨 𝘮𝘢𝘵𝘦𝘳𝘪𝘢𝘭𝘴

* [Practical Tips for Finetuning LLMs Using LoRA (Low-Rank Adaptation)](https://magazine.sebastianraschka.com/p/practical-tips-for-finetuning-llms?) 

* [Poe](https://poe.com/): a platform that lets people ask questions, get instant answers, and have back-and-forth conversations with a wide variety of AI-powered bots

* [[2311.01555] Instruction Distillation Makes Large Language Models Efficient Zero-shot Rankers](https://arxiv.org/abs/2311.01555) 

* [🔥🔥] [State of LLM Apps 2023 · Streamlit](https://state-of-llm.streamlit.app/) 

* [The architecture of today's LLM applications - The GitHub Blog](https://github.blog/2023-10-30-the-architecture-of-todays-llm-applications/) 

* [Demystifying LLMs: How they can do things they weren't trained to do - The GitHub Blog](https://github.blog/2023-10-27-demystifying-llms-how-they-can-do-things-they-werent-trained-to-do/) 

* [How AI chatbots like ChatGPT or Bard work – visual explainer | The Guardian](https://www.theguardian.com/technology/ng-interactive/2023/nov/01/how-ai-chatbots-like-chatgpt-or-bard-work-visual-explainer)

* [cpacker/MemGPT](https://github.com/cpacker/MemGPT): teaching LLMs memory management for unbounded context [[demo page]](https://memgpt.ai/) [[arxiv]](https://arxiv.org/abs/2310.08560) 

* [[2307.10169] Challenges and Applications of Large Language Models](https://arxiv.org/abs/2307.10169): a systematic set of open problems and application successes of LLM area

* [Related resources from around the web | OpenAI Cookbook](https://cookbook.openai.com/articles/related_resources): tools and papers for improving outputs from GPT

* [🔥🔥🔥] [Patterns for Building LLM-based Systems & Products](https://eugeneyan.com/writing/llm-patterns/): "practical patterns for integrating large language models (LLMs) into systems & products" by Eugene Yan

* [Hannibal046/Awesome-LLM: Awesome-LLM](https://github.com/Hannibal046/Awesome-LLM): a curated list of Large Language Model

* [[2309.06794] Cognitive Mirage: A Review of Hallucinations in Large Language Models](https://arxiv.org/abs/2309.06794)

* [Generative AI for Strategy & Innovation](https://www.hbritalia.it/userUpload/ebook_Generative_AI_inglese.pdf): an experiment about management theories with ChatGPT by Harvard Business Review Italia

* [The TextFX project](https://textfx.withgoogle.com/): "AI-powered tools for rappers, writers and wordsmiths" (partnership between Lupe Fiasco and Google)

* [A jargon-free explanation of how AI large language models work | Ars Technica](https://arstechnica.com/science/2023/07/a-jargon-free-explanation-of-how-ai-large-language-models-work/) 

* [🔥🔥🔥] [What We Know About LLMs (Primer)](https://willthompson.name/what-we-know-about-llms-primer) 

* [A simple guide to fine-tuning Llama 2 | Brev docs](https://brev.dev/blog/fine-tuning-llama-2)

* [microsoft/semantic-kernel](https://github.com/microsoft/semantic-kernel): integrate cutting-edge LLM technology quickly and easily into your apps

* [CoPrompt](https://www.coprompt.io/login): platform for teams to use ChatGPT together

* [🔥🔥🔥] [Emerging Architectures for LLM Applications | Andreessen Horowitz](https://a16z.com/2023/06/20/emerging-architectures-for-llm-applications/): "a reference architecture for the emerging LLM app stack"

* [Advanced Guide to ChatGPT](https://aaditsh.notion.site/aaditsh/Advanced-Guide-to-ChatGPT-b8d5901b8bba44f580bb0c0835644567): guide by Neatprompts.com 

* [Falcon LLM - Home](https://falconllm.tii.ae/): a foundational large language model (LLM) with 40 billion parameters trained on one trillion tokens shared by Technology Innovation Institute from Abu Dhabi

* [🔥🔥🔥] [The Hugging Face Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard): "the 🤗 Open LLM Leaderboard aims to track, rank and evaluate LLMs and chatbots as they are released"

* [google/BIG-bench](https://github.com/google/BIG-bench): "a collaborative benchmark intended to probe large language models and extrapolate their future capabilities"

* [togethercomputer/OpenChatKit](https://github.com/togethercomputer/OpenChatKit): provides an open-source base to create both specialized and general purpose chatbots for various applications

* [Paper Digest - ChatGPT](https://www.paperdigest.org/2023/01/recent-papers-on-chatgpt/): Recent Papers on ChatGPT

* [Let Us Show You How GPT Works — Using Jane Austen - The New York Times](https://www.nytimes.com/interactive/2023/04/26/upshot/gpt-from-scratch.html)

* [Search-in-the-Chain: Towards Accurate, Credible and Traceable Large Language Models for Knowledge-intensive Tasks | arxiv](https://arxiv.org/abs/2304.14732): "a novel framework called Search-in-the-Chain (SearChain) to improve the accuracy, credibility and traceability of LLM-generated content for multi-hop question answering"

* [🔥🔥🔥] [Mooler0410/LLMsPracticalGuide](https://github.com/Mooler0410/LLMsPracticalGuide): list of practical guide resources of LLMs based on the paper [Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond](https://arxiv.org/abs/2304.13712)

* [hpcaitech/ColossalAI](https://github.com/hpcaitech/ColossalAI): Making large AI models cheaper, faster and more accessible

* [microsoft/LoRA](https://github.com/microsoft/LoRA): Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"s

* [kyrolabs/awesome-langchain](https://github.com/kyrolabs/awesome-langchain): 😎 Awesome list of tools and project with the awesome LangChain framework

* [Stability AI Launches the First of its StableLM Suite of Language Models — Stability AI](https://stability.ai/blog/stability-ai-launches-the-first-of-its-stablelm-suite-of-language-models) 

* [Free Dolly | The Databricks Blog](https://www.databricks.com/blog/2023/04/12/dolly-first-open-commercially-viable-instruction-tuned-llm): open source, instruction-following LLM, fine-tuned on a human-generated instruction dataset licensed for research and commercial use

* [Summary of ChatGPT/GPT-4 Research and Perspective Towards the Future of Large Language Models](https://arxiv.org/abs/2304.01852): paper with "a comprehensive survey of ChatGPT and GPT-4 and their prospective applications across diverse domains"

* [lm-sys/FastChat](https://github.com/lm-sys/FastChat): The release repo for "Vicuna: An Open Chatbot Impressing GPT-4" [[demo](https://chat.lmsys.org/)]

* [🔥🔥🔥] [oobabooga/text-generation-webui](https://github.com/oobabooga/text-generation-webui): a gradio web UI for running Large Language Models like GPT-J 6B, OPT, GALACTICA, LLaMA, and Pygmalion

* [Why LLaMa Is A Big Deal | Hackaday](https://hackaday.com/2023/03/22/why-llama-is-a-big-deal/): post that discusses the impact of LLaMa and Alpaca in popularizing LLMs and even using them in small hardware devices

* [logspace-ai/langflow](https://github.com/logspace-ai/langflow): a UI for LangChain, designed with react-flow to provide an effortless way to experiment and prototype flows

* [More than you've asked for: A Comprehensive Analysis of Novel Prompt Injection Threats to Application-Integrated Large Language Models](https://arxiv.org/abs/2302.12173): paper on LLM Security

* [Cohere AI](https://docs.cohere.ai/): a way to integrate state-of-the-art language models to applications

* [Langchain for paper summarization](https://lancemartin.notion.site/lancemartin/Langchain-for-paper-summarization-d4ad122ea9a64c0eb1f981e743d6c419): using langchain to build a app for paper summarization

* [Red-Teaming Large Language Models | Hugging Faces](https://huggingface.co/blog/red-teaming): strategies for testing LLMs against jailbreaks and attacks

* [hwchase17/langchain](https://github.com/hwchase17/langchain/): "building applications with LLMs through composability"

* [Top Large Language Models (LLMs) in 2023 | MarkTechPost](https://www.marktechpost.com/2023/02/22/top-large-language-models-llms-in-2023-from-openai-google-ai-deepmind-anthropic-baidu-huawei-meta-ai-ai21-labs-lg-ai-research-and-nvidia/): list with large language models from diverse companies

* [Godly](https://godly.ai): Instant context for GPT3

* [GPTZero](https://gptzero.me/): "Detect AI Plagiarism. Accurately"

* [GPT-3 Apps](https://gpt-apps.com/): GPT-3 Powered Micro Products (ex: cat namer, poet pocket, summarize)

* [Inside language models (from GPT-3 to PaLM) – Dr Alan D. Thompson – Life Architect](https://lifearchitect.ai/models/)

* [Google AI Blog: Pathways Language Model (PaLM): Scaling to 540 Billion Parameters for Breakthrough Performance](https://ai.googleblog.com/2022/04/pathways-language-model-palm-scaling-to.html) 

* [DeepMind says its new language model can beat others 25 times its size | MIT Technology Review](https://www.technologyreview.com/2021/12/08/1041557/deepmind-language-model-beat-others-25-times-size-gpt-3-megatron/) 

* [Integrated AI: How to talk to AI for free using nine platforms (Megatron, GPT-3, GPT-J, Wudao, J1..) - YouTube](https://www.youtube.com/watch?v=yWM_8QwLyuY&list=LL&index=1&t=17s) by Dr Alan D. Thompson. The following references came from this video description

* [Haystack](https://github.com/deepset-ai/haystack): framework for building applications with LLMs and Transformers (e.g. agents, semantic search, question-answering)

* [SolidUI](https://github.com/CloudOrc/SolidUI): AI-generated visualization prototyping and editing platform, support 2D, 3D models, combined with LLM(Large Language Model) for quick editing.



### Model Context Protocol



* [Introducing the Model Context Protocol \ Anthropic](https://www.anthropic.com/news/model-context-protocol)

  * an open standard that enables developers to build secure, two-way connections between their data sources and AI-powered tools.

  * developers can either expose their data through MCP servers or build AI applications (MCP clients) that connect to these servers.

* [Model Context Protocol](https://github.com/modelcontextprotocol): Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools.

* [Introduction - Model Context Protocol](https://modelcontextprotocol.io/introduction)

  * Think of MCP like a USB-C port for AI applications.

  * MCP helps you build agents and complex workflows on top of LLMs.

* Examples

  * [Example Servers - Model Context Protocol](https://modelcontextprotocol.io/examples)

  * [abhiz123/todoist-mcp-server](https://github.com/abhiz123/todoist-mcp-server/tree/main): MCP server for Todoist integration enabling natural language task management with Claude

* List of Servers

  * [modelcontextprotocol/servers: Model Context Protocol Servers](https://github.com/modelcontextprotocol/servers)

  * [Awesome MCP Servers](https://mcpservers.org/)

  * [punkpeye/awesome-mcp-servers](https://github.com/punkpeye/awesome-mcp-servers): A collection of MCP servers.

  * [Composio MCP Server](https://mcp.composio.dev/): Connect Cursor, Windsurf, and Claude to 100+ fully managed MCP Servers with built-in auth

    * These servers are built by the community and are hosted by Composio

* [Example Clients - Model Context Protocol](https://modelcontextprotocol.io/clients)

* [Building MCP with LLMs - Model Context Protocol](https://modelcontextprotocol.io/tutorials/building-mcp-with-llms)

* [Add Supabase to Cursor via MCP](https://x.com/dshukertjr/status/1896531501514109056)

* [Building Agents with Model Context Protocol - Full Workshop with Mahesh Murag of Anthropic - YouTube](https://www.youtube.com/watch?v=kQmXtrmQ5Zg): AI Engineer Summit workshop

* [loopwork-ai/emcee](https://github.com/loopwork-ai/emcee): a tool that provides a Model Context Protocol (MCP) server for any web application with an OpenAPI specification.

* [MCP Run](https://docs.mcp.run/): a registry of AI tools that can be developed by anyone and used inside any AI application

* [modelcontextprotocol/inspector](https://github.com/modelcontextprotocol/inspector): Visual testing tool for MCP servers



### Programming Frameworks for LLMs



* [DSPy: Not Your Average Prompt Engineering](https://jina.ai/news/dspy-not-your-average-prompt-engineering/): a post about the DSPy, a framework developed by the Stanford NLP group aimed at algorithmically optimizing language model prompts

* [🔥🔥🔥] [stanfordnlp/dspy](https://github.com/stanfordnlp/dspy): DSPy: The framework for programming — not prompting — foundation models



### Prompt Engineering



* [Narrow AI](https://www.getnarrow.ai/): Automated Prompt Engineering and Optimization Platform

* [Anthropic's Prompt Engineering Interactive Tutorial](https://github.com/anthropics/courses/tree/master/prompt_engineering_interactive_tutorial) 

* [ncwilson78/System-Prompt-Library](https://github.com/ncwilson78/System-Prompt-Library): A library of shared system prompts for creating customized educational GPT agents.

* [Promptstacks](https://www.promptstacks.com/): a prompt engineering community

* [Prompt engineering - OpenAI API](https://platform.openai.com/docs/guides/prompt-engineering): OpenAI's document with strategies and tactics for getting better results from large language models

* [[2310.04438] A Brief History of Prompt: Leveraging Language Models](https://arxiv.org/abs/2310.04438): the paper presents an exploration of the evolution of prompt engineering. The author, Golam Md Muktadir, extensively used ChatGPT for content generation

* [[2311.05661] Prompt Engineering a Prompt Engineer](https://arxiv.org/abs/2311.05661): this paper deals with the problem of "constructing a meta-prompt that more effectively guides LLMs to perform automatic prompt engineering"

* [[2311.04155] Black-Box Prompt Optimization: Aligning Large Language Models without Model Training](https://arxiv.org/abs/2311.04155) 

* [🔥🔥] [Prompt Engineering Roadmap - roadmap.sh](https://roadmap.sh/prompt-engineering) 

* [🔥🔥🔥] [Learn Prompting](https://learnprompting.org/): series of lessons of prompt engineering

* [🔥🔥🔥] [Prompt Engineering | Lil'Log](https://lilianweng.github.io/posts/2023-03-15-prompt-engineering/): prompt engineering learning notes by Lilian Weng

* [🔥🔥🔥] [ChatGPT Prompt Engineering for Developers - DeepLearning.AI](https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/): short course taught by Isa Fulford (OpenAI) and Andrew Ng (DeepLearning.AI) that provide best practices for prompt engineering

* [🔥🔥🔥] [Prompt Engineering Guide](https://www.promptingguide.ai/): a project by DAIR.AI that intends to educate researchers and practitioners about prompt engineering

* [the Book](https://fedhoneypot.notion.site/25fdbdb69e9e44c6877d79e18336fe05?v=1d2bf4143680451986fd2836a04afbf4): collection of prompts and hints of prompt engineering

* [dair-ai/Prompt-Engineering-Guide](https://github.com/dair-ai/Prompt-Engineering-Guide): Guide and resources for prompt engineering



#### Prompt Optimizers



* [zou-group/textgrad](https://github.com/zou-group/textgrad): Automatic "Differentiation" via Text, using large language models to backpropagate textual gradients.

* [🔥🔥🔥] [stanfordnlp/dspy](https://github.com/stanfordnlp/dspy): DSPy: The framework for programming — not prompting — foundation models

* [vaibkumr/prompt-optimizer](https://github.com/vaibkumr/prompt-optimizer): Minimize LLM token complexity to save API costs and model computations.

* [PromptPerfect](https://promptperfect.jina.ai/): "Optimize Your Prompts to Perfection"

* [🔥🔥🔥] [LLMLingua](https://llmlingua.com/): Designing a Language for LLMs via **Prompt Compression**



#### Prompt Engineering for Text-to-text



* [danielmiessler/fabric](https://github.com/danielmiessler/fabric): fabric is an open-source framework for augmenting humans using AI. It provides a modular framework for solving specific problems using a crowdsourced set of AI prompts that can be used anywhere.

* [ChatGPT for designers](https://tibidavid.gumroad.com/l/ChatGPT-Cheat-Sheet-V2?ref=filipecalegario-awesome-generative-ai): ChatGPT Cheat Sheet V2 to craft better prompts

* [🔥] [[2307.11760] Large Language Models Understand and Can be Enhanced by Emotional Stimuli](https://arxiv.org/abs/2307.11760) 

* [🔥] [[2305.13252] "According to ..." Prompting Language Models Improves Quoting from Pre-Training Data](https://arxiv.org/abs/2305.13252) 

* [🔥] [[2307.05300] Unleashing Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration](https://arxiv.org/abs/2307.05300)

* [timqian/openprompt.co](https://github.com/timqian/openprompt.co): Create. Use. Share. ChatGPT prompts

* [60 ChatGPT Prompts for Data Science (Tried, Tested, and Rated)](https://medium.datadriveninvestor.com/60-chatgpt-prompts-for-data-science-tried-tested-and-rated-4994c7e6adb2): post by Travis Tang from DataDrivenInvestor

* [f/awesome-chatgpt-prompts](https://github.com/f/awesome-chatgpt-prompts): this repo includes ChatGPT prompt curation to use ChatGPT better

* [brexhq/prompt-engineering](https://github.com/brexhq/prompt-engineering): "Tips and tricks for working with Large Language Models like OpenAI's GPT-4"

* [How to write an effective GPT-3 prompt | Zapier](https://zapier.com/blog/gpt-3-prompt/): a list of 6 GPT-3 tips for getting the desired output

* [The Art of ChatGPT Prompting: A Guide to Crafting Clear and Effective Prompts](https://fka.gumroad.com/l/art-of-chatgpt-prompting): e-book by Fatih Kadir Akın ([@fkadev](http://twitter.com/fkadev))



#### Prompt Engineering for Text-to-image



* [USP AI Prompt Book](https://app.usp.ai/static/Stable%20Diffusion%202.1%20Prompt%20Book%20by%20USP.ai.pdf): Stable Diffusion v2.1 Prompt Book

* [daspartho/prompt-extend](https://github.com/daspartho/prompt-extend): extending stable diffusion prompts with suitable style cues using text generation 

* [Prompt Box](https://www.promptbox.ai/): "organize and save your AI prompts"

* [Midjourney artist reference - Google Sheets](https://docs.google.com/spreadsheets/d/1e2MZ1K6WMTUuxlPAQ_2A0rz-H55NBykb66TY7DuerVg/edit#gid=2088669480) 

* [Stable Diffusion Prompt Book — Stability.Ai](https://stability.ai/sdv2-prompt-book): prompt book for Stable Diffusion v2.0 and v2.1 released by Stability.AI

* [The Ultimate Stable Diffusion Prompt Guide by PromptHero](https://prompthero.com/stable-diffusion-prompt-guide) 

* [CLIP Interrogator - a Hugging Face Space by pharma](https://huggingface.co/spaces/pharma/CLIP-Interrogator): image-to-text tool to figure out what a good prompt might be to create new images like an existing one

* [🔥🔥🔥] [Prompt book for data lovers II - Google Slides](https://docs.google.com/presentation/d/1V8d6TIlKqB1j5xPFH7cCmgKOV_fMs4Cb4dwgjD5GIsg/edit#slide=id.g1834b964b0f_3_4): An open source exploration on text-to-image and data visualization

* [some9000/StylePile](https://github.com/some9000/StylePile): A helper script for AUTOMATIC1111/stable-diffusion-webui. Basically a mix and match to quickly get different results without wasting a lot of time writing prompts.

* [Artists To Study | All images generated with Google Colab TPUs + CompVis/stable-diffusion-v1-4 + Huggingface Diffusers](https://artiststostudy.pages.dev/): a systematic study of artists' styles made by [@camenduru](https://twitter.com/camenduru)

* [CLIP retrieval for laion5B](https://rom1504.github.io/clip-retrieval/?back=https%3A%2F%2Fknn5.laion.ai&index=laion5B&useMclip=false): CLIP retrieval using Laion5B. "It works by converting the text query to a CLIP embedding , then using that embedding to query a knn index of clip image embedddings".

* [rom1504/clip-retrieval](https://github.com/rom1504/clip-retrieval): Easily compute CLIP embeddings and build a CLIP retrieval system with them

* [PromptDesign | Reddit](https://www.reddit.com/r/PromptDesign/): Reddit community for "the art of communicating with natural language models"

* [Prompt Engineering and Zero-Shot/Few-Shot Learning [Guide] - inovex GmbH](https://www.inovex.de/de/blog/prompt-engineering-guide/): prompt engineering for text generation

* [clip-interrogator.ipynb - Colaboratory](https://colab.research.google.com/github/pharmapsychotic/clip-interrogator/blob/main/clip_interrogator.ipynb#scrollTo=rbDEMDGJrJEo): a tool for image-to-prompt

* [Useful Prompt Engineering tools and resources | Reddit](https://www.reddit.com/r/StableDiffusion/comments/xcrm4d/useful_prompt_engineering_tools_and_resources/) 

* [PromptHero](https://prompthero.com/): Search the best prompts for Stable Diffusion, DALL-E and Midjourney

* [promptoMANIA](https://promptomania.com/): AI art community with prompt generator

* [Lexica](https://lexica.art/): search over 10M+ Stable Diffusion images and prompts

* [list of artists for SD v1.4 A-C / D-I / J-N / O-Z](https://rentry.org/artists_sd-v1-4) 

* [succinctly/text2image-prompt-generator · Hugging Face](https://huggingface.co/succinctly/text2image-prompt-generator): a GPT-2 model fine-tuned on the succinctly/midjourney-prompts dataset, which contains 250k text prompts that users issued to the Midjourney text-to-image service over a month period

* [The Prompter | vicc | Substack](https://theprompter.substack.com/): a newsletter about news, tips and thoughts around prompt engineering

* [(19) Nikhil Agrawal 📌 on Twitter](https://twitter.com/HeyNikhila/status/1570005481896255490): 11 AI Images Prompt websites to level up the image quality

* [Phraser](https://phraser.tech/): a tool that support prompt creation

* [PromptBase | Prompt Marketplace](https://promptbase.com/): PromptBase is a marketplace for DALL·E, Midjourney & GPT-3 prompts, where people can sell prompts and make money from their prompt crafting skills.

* [Professional AI whisperers have launched a marketplace for DALL-E prompts - The Verge](https://www.theverge.com/2022/9/2/23326868/dalle-midjourney-ai-promptbase-prompt-market-sales-artist-interview)

* [Visual Prompt Builder](https://tools.saxifrage.xyz/prompt): simple deck of illustrated card to combine modifiers for prompt building

* [Prompt Engineering Template - Google Sheets](https://docs.google.com/spreadsheets/d/1-snKDn38-KypoYCk9XLPg799bHcNFSBAVu2HVvFEAkA/edit#gid=0): spreadsheet with lists of modifiers for prompt building and a lot of interesting links for reference

* [Prompt Engineering: From Words to Art - Saxifrage Blog](https://www.saxifrage.xyz/post/prompt-engineering)

* [DALL·Ery GALL·Ery Resources](https://dallery.gallery/prompt-resources-tools-ai-art/): DALL·E 2 and AI art prompt resources & tools to inspire beautiful images

* [[2204.13988] A Taxonomy of Prompt Modifiers for Text-To-Image Generation](https://arxiv.org/abs/2204.13988) 

* [List of Aesthetics | Aesthetics Wiki | Fandom](https://aesthetics.fandom.com/wiki/List_of_Aesthetics) 

* [Artist Directory (Volcano Comparison) | AI Art Creation Wiki | Fandom](https://aiartcreation.fandom.com/wiki/Artist_Directory_(Volcano_Comparison)) 

* [The DALL·E 2 Prompt Book – DALL·Ery GALL·Ery](https://dallery.gallery/the-dalle-2-prompt-book/)

* [DALL·Ery GALL·Ery](https://dallery.gallery/): A guide to OpenAI's DALL·E – prompts, projects, examples, and tips

* [(2) MASSIVE 💥 DALL-E 2 ANIME ⚡︎ KEYWORDS + MODIFIERS LIST ★ : haaaaven](https://www.reddit.com/user/haaaaven/comments/w05f56/massive_dalle_2_anime_keywords_modifiers_list/): image prompt modifier collection by haaaaven

* [DrawBench](https://docs.google.com/spreadsheets/d/1y7nAbmR4FREi6npB1u-Bo3GFdwdOPYJc617rBOxIRHY/edit#gid=0): a list of prompts the Google Imagen is organizing as a benchmark

* [CLIP Prompt Engineering for Generative Art - matthewmcateer.me](https://matthewmcateer.me/blog/clip-prompt-engineering/): list of styles tested with Quick CLIP Guided Diffusion

* [Adobe should make a boring app for prompt engineers (Interconnected)](https://interconnected.org/home/2022/06/02/dalle)

* [[2206.00169] Discovering the Hidden Vocabulary of DALLE-2](https://arxiv.org/abs/2206.00169)

* [When SD just doesn't understand the prompt no matter how hard I try | Reddit](https://www.reddit.com/r/StableDiffusion/comments/xgwcab/when_sd_just_doesnt_understand_the_prompt_no/) 

* [It's very interesting how some prompts have very defined output but other specific ones are not | Reddit](https://www.reddit.com/r/StableDiffusion/comments/xgplii/its_very_interesting_how_some_prompts_have_very/)



### Mamba



* [[2312.00752] Mamba: Linear-Time Sequence Modeling with Selective State Spaces](https://arxiv.org/abs/2312.00752): alternative to Transformer architecture.

* [Mamba: A shallow dive into a new architecture for LLMs | by Geronimo (@geronimo7) | Dec, 2023 | Medium](https://medium.com/@geronimo7/mamba-a-shallow-dive-into-a-new-architecture-for-llms-54c70ade5957)

* [Mamba-Chat](https://github.com/havenhq/mamba-chat): A chat LLM based on the state-space model architecture



### Running LLMs Locally



* [llama.cpp guide](https://steelph0enix.github.io/posts/llama-cpp-guide/): Running LLMs locally, on any hardware, from scratch

* [PowerInfer](https://github.com/SJTU-IPADS/PowerInfer): a high-speed inference engine for deploying LLMs locally 

* [🔥🔥] [Ollama](https://ollama.ai/): run Llama 2, Code Llama, and other models locally

* [GPT4All](https://gpt4all.io/index.html): A free-to-use, locally running, privacy-aware chatbot. No GPU or internet is required.

* [LM Studio](https://lmstudio.ai/): Discover, download, and run local LLMs

* [ggerganov/llama.cpp](https://github.com/ggerganov/llama.cpp): Port of Facebook's LLaMA model in C/C++



### Function Calling



* [Nexusflow/NexusRaven-V2-13B · Hugging Face](https://huggingface.co/Nexusflow/NexusRaven-V2-13B): "surpassing GPT-4 for Zero-shot Function Calling"



### GPTs and Assistant API



* [Featured GPTs](https://www.featuredgpts.com/):  curated custom GPTs list for daily tasks

* [AllGPTs](https://allgpts.co/): a directory to find GPTs



### Retrieval-Augmented Generation (RAG)



* [Benchmarking Hallucination Detection Methods in RAG | Towards Data Science](https://towardsdatascience.com/benchmarking-hallucination-detection-methods-in-rag-6a03c555f063/)

* [bRAGAI/bRAG-langchain](https://github.com/bRAGAI/bRAG-langchain): Everything you need to know to build your own RAG application

* [ragapp/ragapp](https://github.com/ragapp/ragapp): an alternative to use Agentic RAG in enterprises

* [LlamaParse](https://www.llamaindex.ai/blog/launching-the-first-genai-native-document-parsing-platform): GenAI-native document parsing platform by LlamaIndex

* [Retrieval-Augmented Generation for Large Language Models: A Survey](https://arxiv.org/abs/2312.10997) 

* [weaviate/Verba](https://github.com/weaviate/Verba): Retrieval Augmented Generation (RAG) chatbot powered by Weaviate

* [imartinez/privateGPT](https://github.com/imartinez/privateGPT): "Interact with your documents using the power of GPT, 100% privately, no data leaks"

* [pinecone-io/canopy](https://github.com/pinecone-io/canopy): Retrieval Augmented Generation (RAG) framework and context engine powered by Pinecone

* [Forget RAG, the Future is RAG-Fusion](https://towardsdatascience.com/forget-rag-the-future-is-rag-fusion-1147298d8ad1): post by Adrian H. Raudaschl in Towards Data Science

* [Rerankers and Two-Stage Retrieval | Pinecone](https://www.pinecone.io/learn/series/rag/rerankers/)

* [Retrieval Augmented Generation | Pinecone](https://www.pinecone.io/learn/series/rag/)

* [dssjon/biblos: biblos.app](https://github.com/dssjon/biblos): example of RAG architecture using semantic search and summarization for retrieving Bible passages



### Embeddings and Semantic Search



* [🪆 Introduction to Matryoshka Embedding Models](https://huggingface.co/blog/matryoshka) 

* [Getting creative with embeddings by Amelia Wattenberger](https://wattenberger.com/thoughts/yay-embeddings-math) 

* [The Hidden Life of Embeddings: Linus Lee - YouTube](https://www.youtube.com/watch?v=YvobVu1l7GI) 

* [neuml/txtai](https://github.com/neuml/txtai): semantic search and workflows powered by language models

* [facebookresearch/faiss](https://github.com/facebookresearch/faiss): A library for efficient similarity search and clustering of dense vectors 

* [Optimize Your Chatbot’s Conversational Intelligence Using GPT-3 | by Amogh Agastya | Better Programming](https://betterprogramming.pub/how-to-give-your-chatbot-the-power-of-neural-search-with-openai-ebcff5194170): tutorial presenting semantic search concepts

* [🔥] [whitead/paper-qa](https://github.com/whitead/paper-qa): "LLM Chain for answering questions from documents with citations", [demo](https://twitter.com/andrewwhite01/status/1629346569756483584?s=20)

* [What is Semantic Search?](https://txt.cohere.ai/what-is-semantic-search/)

* [Learning Center | Pinecone](https://www.pinecone.io/learn/): Pinecone's guides to vector embeddings

* [BLIP+CLIP | CLIP Interrogator | Kaggle](https://www.kaggle.com/code/leonidkulyk/lb-0-45836-blip-clip-clip-interrogator): a Kaggle notebook for image description and captioning (imate-to-text)

* [jerryjliu/gpt_index: GPT Index (LlamaIndex)](https://github.com/jerryjliu/gpt_index): a project to make it easier to use large external knowledge bases with LLMs

* [Llama Hub](https://llamahub.ai/): a repository of data loaders for LlamaIndex (GPT Index) and LangChain

* [Chroma](https://www.trychroma.com/): an open-source AI-native database that makes it easy to use embeddings



### Autonomous LLM Agents



* [🔥] [Building effective agents by Anthropic](https://www.anthropic.com/research/building-effective-agents): this article introduces basic concepts related to agents and didactically presents agent architectures.

* [Complete Guide to LLM Agents (2025)](https://botpress.com/blog/llm-agents): summarization of terms related to LLM agents

* [pydantic/pydantic-