Artificial Intelligence #178

Hey, in this issue: the economic potential of generative AI; LLM-powered autonomous agents; Meta's response to Google's MusicLM for text-to-music; we can’t predict how AI will affect the workforce; five methods to detect drift in ML embeddings; gpt-engineer; and more.

This issue is sponsored by?Gretel and True Positive.

• [McKinsey]?The economic potential of generative AI: the next productivity frontier
• LLM-powered autonomous agents
• [Model] Otter:?a multi-modal model with in-context instruction tuning?(video)
• [Project] simpleaichat:?a Python package for easily interfacing with chat apps, with robust features and minimal code complexity
• [Sponsored]?Accelerate Data Access in Healthcare

Join leading researchers and scientists?from Roche, University of Cambridge, and Gretel for a conversation on how synthetic data can unlock challenges to data access across the healthcare, life sciences and pharmaceutical industries. Registration is free.?Wed, July 19th, 2023 | 8am PDT / 11am EDT / 4pm BST

• MusicGen:?Meta's response to Google's MusicLM for text-to-music
• [IEEE] “Model collapse” looms?when AI trains on the output of other models
• [Sponsored] To start in AI, read The Hundred-Page Machine Learning Book followed by the Machine Learning Engineering book
• [Tutorial] Five?methods to detect drift in ML embeddings
• [Project] gpt-engineer:?specify what you want it to build, the AI asks for clarification, and then builds it

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