Few-shot learning is changing the AI game. On this episode of Before AGI, we discuss how AI models learn from small datasets, its distinction from zero-shot learning, and its real-world applications in fields like medical imaging, chatbots, and robotics.
🔍 Highlights:
Few-shot vs. Zero-shot learning explained
Applications in various industries
Key advancements: SetFit framework and Natural Language Inference techniques
Challenges like domain shift, bias, and hubness
Ethical considerations and the future of AI
🎧 Tune in to explore how few-shot learning is transforming the AI landscape!
More from Ian Ochieng:
🌐 Website: ianochiengai.substack.com
📺 YouTube: Ian Ochieng AI
🐦 Twitter: @IanOchiengAI
📸 Instagram: @IanOchiengAI
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