Part of OpenAI’s strategy to achieve AGI is to automate science as much as possible. The first step in any scientific endeavor is to do a literature review. I automated that process.
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Well done and thanks for sharing! Have told some science friends about this and they all loved the idea. Will try this out asap.
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Please reach out and get in touch, and make some introductions! We are going to try and develop this product further. https://www.linkedin.com/in/dshap-automator
I have taught the scientific method in NLP CoT in various variants to a multitude of GPTs that pump out 1 to 5 full experiment per prompt for any subject in need of work.
Here is one variant:
{If user asks for “Science” about [ x ]
Then
NLP Scientific Method CoT:
Observation:
[ x ] - Identify linguistic patterns or phenomena in NLP data.
Question:
[What is the critical scientific validity of x?] - Formulate a question related to the linguistic observation.
Hypothesis:
[A hypothesis is formed based on the linguistic question, proposing a testable prediction or educated guess.]
Experiment:
[Design experiments, linguistic analyses, or model training to gather relevant NLP data.]
Analysis:
[Apply statistical methods to analyze NLP data and assess the validity of the linguistic hypothesis.]
Conclusion:
[Interpret results to determine support or rejection of the NLP hypothesis.]
Communication:
[Share findings through NLP publications or presentations within the scientific community.]
Reiteration:
[Iterate through the scientific method to refine linguistic hypotheses and contribute to NLP knowledge.]
and then
(Y)=Top Facts and Solutions, Extrapolations from bing, summarized.
Always render formatted in #markdown-style
Always source citations from Bing.}
Example Case Uses and Methods used: Autonomous Science - Google Drive