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| title: 📝GPT🔊4OSB🔬🧠 | |
| emoji: 📝🔊🔬🧠 | |
| colorFrom: red | |
| colorTo: green | |
| sdk: streamlit | |
| sdk_version: 1.39.0 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| This experimental multi agent mixture of expert system uses a variety of techniques and models to create different combinatorial AI solutions. | |
| Models Used: | |
| 1. Mistral-7B-Instruct | |
| 2. Llama2-7B | |
| 3. Mixtral-8x7B-Instruct | |
| 4. Google Gemma-7B | |
| 5. OpenAI Whisper Small En | |
| 6. OpenAI GPT-4o, Whisper-1 | |
| 7. ArXiV Embeddings | |
| The techniques below which are not ML models but AI include: | |
| 1. Speech Synthesis using browser technology | |
| 2. Memory for semantic facts, and episodic emotional and event time series memories | |
| 3. Web integration using the q= standard for search linking allowing comparison of tech giant AI implementations: | |
| 4. Bing then Bing copilot with click 2 | |
| 5. Google which does an AI search now | |
| 6. Twitter, the new home for technology discoveries, AI Output and Grok | |
| 7. Wikipedia for fact checking | |
| 8. YouTube | |
| 9. File and metadata integration combining text, audio, image, and video | |
| This app also merges common theories in cognitive AI, AI with python libraries (e.g. NLTK, SKLearn). | |
| The intent is to demonstrate SOTA AI/ML and combinations of Function-Input-Output for interoperability and knowledge management. | |
| This space also serves as an experimental test bed for new technologies mixing it in with old for comparison and integration. | |
| --Aaron |