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Unlocking the Potential of AI - April Edwards & Henk Boelman - NDC Porto 2023
AI has evolved from proof-of-concept to generating next tokens, predicting contexts, and practical applications.
- AI has come a long way, from being limited to proving up on existing data to now learning from it.
- Generative AI can predict the next likely token, given the context.
- Custom models can be built with Azure OpenAI, allowing for more control over the response.
- Error handling is important, and safety mechanisms can be implemented to prevent undesired behavior.
- AI models can be used for search applications, and Azure cognitive search can combine multiple sources.
- Vectors and factors can be used to search for similar documents and contexts.
- The future of AI models is flexible, usable, and adaptable to different problem spaces.
- The potential of AI is vast, but it is important to consider the impact of AI on individuals and society.
- Collaboration between humans and AI is key to harnessing the potential of AI.
- GitHub Copilot chat can be used to explain code and add comments, and can even generate unit tests.
- The indexing process can be managed through Azure OpenAI, allowing for efficient storage and retrieval of data.
- Factoring and vectorization can be used to improve the speed and accuracy of search results.
- Microsoft is building custom models for Office, demonstrating the potential of AI in practical applications.