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Summary of the Sam Altman roundtable held at UCL

Haebom
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OpenAI is currently limited by GPU resources, which is leading to bottlenecks in some features like the fine-tuning API and longer context windows.
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OpenAI is working to improve its models so they can use GPU resources more efficiently and support context windows ranging from 100,000 up to 1 million tokens in the future.
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There are plans to improve and address the bottlenecks in the fine-tuning API and to introduce more efficient methods for fine-tuning.
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OpenAI's future roadmap includes developing a more affordable and faster GPT-4, longer context windows, fine-tuning APIs, stateful APIs, and multi-modality.
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The plugin hasn't achieved product-market fit (PMF); while some users need it, others may not.
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OpenAI considers its developer community a major asset, rather than focusing on releasing competing products, and will keep supporting developers through APIs so they can build new products and enhance the platform.
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OpenAI acknowledges the need for regulation, highlights the importance of open source, and has raised concerns that there may be limits to hosting very large-scale models.
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The scaling law for AI models is still valid, and it's explained that increasing the size of the internal data can continue to improve performance.
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