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https://github.com/yaohaizhou/awesome-agi

πŸ€– A list of latest AGI-related repos, resources and courses including LLMs and AI Agents.
https://github.com/yaohaizhou/awesome-agi

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πŸ€– A list of latest AGI-related repos, resources and courses including LLMs and AI Agents.

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# Awesome AGI with LLMs and AI Agents
πŸ€– A list of latest AGI-related repos, resources and courses including LLMs and AI Agents.

## LLMs

### Tutorial / Article

1. [Let's build the GPT Tokenizer](https://www.youtube.com/watch?v=zduSFxRajkE)
2. [LLM Engineering: Steering language models](https://www.wandb.courses/courses/steering-language-models)
3. [Gemini 1.5 pro tech report](https://storage.googleapis.com/deepmind-media/gemini/gemini_v1_5_report.pdf) πŸ”₯πŸ”₯πŸ”₯
4. [DLite V2: Lightweight, Open, Easily Customizable LLMs](https://medium.com/ai-squared/dlite-v2-lightweight-open-llms-that-can-run-anywhere-3ab59b3a7feb)
5. [Can you really run LLMs locally on your laptop?](https://jpreagan.com/blog/can-you-really-run-llms-locally-on-your-laptop/)
6. [Anthropic (@AnthropicAI) on X](https://twitter.com/AnthropicAI/status/1764653830468428150)
7. [Stanford CS229 I Machine Learning I Building Large Language Models (LLMs)](https://www.youtube.com/watch?v=9vM4p9NN0Ts&t=64s) πŸ”₯πŸ”₯πŸ”₯
8. [OpenAI’s 5 Levels Of β€˜Super AI’](https://www.forbes.com/sites/jodiecook/2024/07/16/openais-5-levels-of-super-ai-agi-to-outperform-human-capability/)

### Repos

1. [google/gemma.cpp](https://github.com/google/gemma.cpp)
2. [llama index](https://github.com/run-llama/llama_index)
3. [gpt4all: run open-source LLMs anywhere](https://github.com/nomic-ai/gpt4all)

## AI Agents

### Landscape (2024.2.29)

drawing

### Tutorial

1. [The Future of Generative AI Agents with Joon Sung Park](https://youtu.be/vVb366mGtXo?si=redp1VfHF9fWYSQd)
2. [Google – AI Assistants for Data Tasks with Gemma](https://www.kaggle.com/competitions/data-assistants-with-gemma/?utm_medium=social&utm_source=linkedin&utm_campaign=comp-gemma1)
3. [Retrieval Augmented Generation - MindsDB](https://docs.mindsdb.com/integrations/ai-engines/rag#simple-example)
4. [Tutorial Proposal: Retrieval-based Language Models and Applications](https://aclanthology.org/2023.acl-tutorials.6.pdf)
5. [Building Production-Ready RAG Applications: Jerry Liu](https://www.youtube.com/watch?v=TRjq7t2Ms5I&ab_channel=AIEngineer)
6. [WALKING DOWN THE MEMORY MAZE: BEYOND CONTEXT LIMIT THROUGH INTERACTIVE READING](https://arxiv.org/pdf/2310.05029.pdf)
7. [AutoGen Studio 2.0 Tutorial - Skills, Multi-Agent Teams, and REAL WORLD Use Cases (NO CODE)](https://www.youtube.com/watch?v=4ZqJSfV4818) πŸ”₯πŸ”₯πŸ”₯

### Repos / Community

1. [MicroSoft AutoGen](https://github.com/microsoft/autogen)
2. [MicroSoft Power Virtual Agents](https://learn.microsoft.com/en-us/power-platform/release-plan/2023wave1/power-virtual-agents/)
3. [Microsoft Copilot Studio: Make your own Copilot with no code](https://www.youtube.com/watch?v=sJUJbYEoqSo&ab_channel=MicrosoftReactor)
4. [Google Dialogflow CX](https://cloud.google.com/dialogflow/cx/docs/basics)
5. [Shanghai Lanma Technology AskXBOT](https://www.askxbot.com/community/)

## Video

1. [EMO: Emote Portrait Alive - Generating Expressive Portrait Videos with Audio2Video Diffusion Model under Weak Conditions](https://humanaigc.github.io/emote-portrait-alive/)
2. [Revisiting Feature Prediction for Learning Visual Representations from Video | Research - AI at Meta](https://ai.meta.com/research/publications/revisiting-feature-prediction-for-learning-visual-representations-from-video/)
3. [Video generation models as world simulators](https://openai.com/research/video-generation-models-as-world-simulators) πŸ”₯πŸ”₯πŸ”₯

## Articles / Papers

1. [Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security (Jan 10, 2024)](https://arxiv.org/abs/2401.05459)