- Published on May 23, 2022
- In AI Features
Solving chain of thought problem of AI
Google introduced ‘chain of thought prompting’ to improve the reasoning abilities of language models.
Image by Analytics India Magazine
- By Avi Gopani
Two years back, NYU professors Gary Marcus and Ernest Davis published an article in MIT Technology Review on GPT-3. The authors asked GPT-3 a series of questions to expose its poor grasp of reality: "Yesterday I dropped my clothes off at the dry cleaner's, and I have yet to pick them up. Where are my clothes?" GPT-3 replied, "I have a lot of clothes."
Clearly, large language models like GPT-3 are not good at multi-step reasoning. "Fundamentally, language is about relating sentences that you hear, and systems like GPT-3 never do that. You give them all the data in the world, and they are still not deriving the notion that language is about semantics," said Gary Marcus. So the question is–how do we enable language models to perform reasoning tasks?
In a recent paper, "Chain of
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Avi Gopani
Avi Gopani is a technology journalist that seeks to analyse industry trends and developments from an interdisciplinary perspective at Analytics India Magazine. Her articles chronicle cultural, political and social stories that are curated with a focus on the evolving technologies of artificial intelligence and data analytics.
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