The AI landscape often glorifies the biggest language models like ChatGPT (175+ billion parameters), creating a notion that size determines a model's value.
However, our recent research collaboration with Chai demonstrates that effective chatbot development requires a different approach.
Contrary to popular belief, relying on massive, expensive LLMs is not necessary for chatbot success.
A strategic combination of smaller language models (over 100x smaller and more cost-efficient than ChatGPT) can outperform even the largest models.
Imagine each small language model as a specialist in a facet of language – grammar, style, domain knowledge.
This pool of experts working collaboratively results in a comprehensive and adaptable conversational AI system.
Our research with Chai, Led by Vyas Raina and Adian Liusie, introduces the groundbreaking 'Blending' approach. This innovative method efficiently combines the strengths of multiple smaller language models.
If you want to read in detail, the mechanics and the real-world impact of Blending, read our in-depth research paper: https://lnkd.in/emXePX5K
Chai incorporated the Blended approach into its chatbot platform, observing significant gains in user retention.
While 2023 celebrated ever-larger language models, 2024 marks the rise of specialized small language models working in tandem.
This shift offers exceptional conversational AI experiences at a fraction of the cost.
What benefits do you foresee with smaller, more specialized language models?
Ready to harness the power of 'Blending' and smaller expert models?
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