Synthetic data from scratch - Clip from livestream 7/May/2024 - Claude 3 Opus, phi-1, phi-3, ChatGPT

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Dr Alan D. Thompson

Dr Alan D. Thompson

Ай бұрын

The Memo: lifearchitect.ai/memo/
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Read the paper: arxiv.org/abs/2306.11644
See the steps: huggingface.co/blog/cosmopedia
Read the shared document: docs.google.com/document/d/1d...
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Read more: lifearchitect.ai/
Dr Alan D. Thompson is a world expert in artificial intelligence (AI), specialising in the augmentation of human intelligence, and advancing the evolution of ‘integrated AI’. Alan’s applied AI research and visualisations are featured across major international media, including citations in the University of Oxford’s debate on AI Ethics in December 2021.
lifearchitect.ai/
Music:
Under licence.
Liborio Conti - Looking Forward (The Memo outro)
no-copyright-music.com/

Пікірлер: 9
@knaz7468
@knaz7468 15 күн бұрын
Why are comments turned off on your latest video? It was super interesting and i was hoping to moment.
@damienhughes4559
@damienhughes4559 Ай бұрын
Did anyone notice that there's currently a Golden Gate Claude version available for a limited time? If you go to Claude and look in the upper right, there's a Golden Gate Bridge icon. If you click on it, you can talk to the altered state version referenced in Claude's tinkering with the model research paper. It's crazy!
@I-Dophler
@I-Dophler Ай бұрын
Interesting insights into the process of generating synthetic data and the potential implications for research and development. Thanks for sharing!
@siceastwood2714
@siceastwood2714 Ай бұрын
7:29 wow, did he knew about the release of GPT-4o or was that a prediction for the logical next step of AI development?
@midnightmoves7976
@midnightmoves7976 Ай бұрын
It is possible to use an Open Source model to generate synthetic data. for instance you can set a system prompt asking the llm to create question and answer pairs for a specific document. this creates a synthetic question answering detaset for your own documents/data. Thanks again for an exelent update Alan.
@I-Dophler
@I-Dophler Ай бұрын
🎯 Key Takeaways for quick navigation: Synthetic data generation replicates existing datasets for various age groups and professions. Models like Claude 3 Opus use prompts to generate synthetic data on specific topics, like French cooking. Synthetic data advantages include new, open, and copyright-free data, but may lose resolution over time. Synthetic data sets can be tailored for different audiences, such as children, teenagers, and researchers. Challenges with synthetic data include potential breakdowns and truthfulness measurement. Synthetic data sets may lack imagination but remain truthful representations. Automated processes are being developed to create large-scale synthetic data sets for AI training. Synthetic data generation could aid AI reasoning by providing diverse and high-quality texts for analysis. Made with HARPA AI
@seb_gibbs
@seb_gibbs Ай бұрын
I dont think AI should be generating new information just because of lack of original imputed information, thats a bad idea After training, AI model has a very large amount of knowledge/information in its 'brain'; and is able to recall a number of true facts, but many known facts conflict with each other. For AI to advance further, it should analyse what it knows and attempt to draw new information from it. All new information its drawn should be tagged for questioning with real people, people who have expert understanding within the subject matter. I can imaging this would be quite engaging communication with AI. Here's a possible prompt for AI: "With the information you know, there must be a number of facts that conflict with each other. Please ask me questions about any of these conflicts that might puzzle you. To start, please ask a single question that puzzles you the most in the subject of ... "
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