Forwarded from Chat GPT
What are Foundation Models? - 2nd $100 Contest
(1) Technical term for distinguishing measure: If you had to pick one quanitative measure with which to distinguish AI “foundation models” from traditional non-foundation models, what would that quantitative measure be? What, exactly is that measure measuring, in concrete techical terms?
(2) Technical term for threshold: What would be the threshold for that quantitative measure, beyond which crosses into “foundation model” territory?
(3) Technical term for what makes crossing the threshold even possible: What’s would be the technical words to describe what makes it possible to cross that quantitative threshold? What, conceptually, makes crossing that threshold even possible?
Looking for 3 technical terms.
First one has 2 possible technical terms AFAIK, but one seems clearly better. Looking for that best one in the first answer.
Bonus points if you can come up with prompts to get ChatGPT to solve these problems, without too many hints.
First to get all 3 technical terms, in one comment and without any wrong guesses, in this thread, without editing your comment - wins $100 in crypto.
Edit: Official Thread Link
(1) Technical term for distinguishing measure: If you had to pick one quanitative measure with which to distinguish AI “foundation models” from traditional non-foundation models, what would that quantitative measure be? What, exactly is that measure measuring, in concrete techical terms?
(2) Technical term for threshold: What would be the threshold for that quantitative measure, beyond which crosses into “foundation model” territory?
(3) Technical term for what makes crossing the threshold even possible: What’s would be the technical words to describe what makes it possible to cross that quantitative threshold? What, conceptually, makes crossing that threshold even possible?
Looking for 3 technical terms.
First one has 2 possible technical terms AFAIK, but one seems clearly better. Looking for that best one in the first answer.
Bonus points if you can come up with prompts to get ChatGPT to solve these problems, without too many hints.
First to get all 3 technical terms, in one comment and without any wrong guesses, in this thread, without editing your comment - wins $100 in crypto.
Edit: Official Thread Link
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“You don’t fully understand how it works, and yet you’ve turned it loose on society?”
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Chat GPT
What are Foundation Models? - 2nd $100 Contest (1) Technical term for distinguishing measure: If you had to pick one quanitative measure with which to distinguish AI “foundation models” from traditional non-foundation models, what would that quantitative…
What are foundation models? 2nd $100 Contest
Looking for 3 technical terms:
(1) Technical term for distinguishing measure: If you had to pick one quantitative measure with which to distinguish AI “foundation models” from traditional non-foundation models, what would that quantitative measure be? What, exactly is that measure measuring, in concrete techical terms?
(2) Technical term for threshold: What would be the threshold for that quantitative measure, beyond which crosses into “foundation model” territory?
(3) Technical term for what makes crossing the threshold even possible: What’s would be the technical words to describe what makes it possible to cross that quantitative threshold? What, conceptually, makes crossing that threshold even possible?
Entries in the Official Thread so far:
(A) breadth, high breadth, ?
(B) number of parameters , billions of parameters, distributed training techniques
(C) Accuracy, Zero Shot Reasoning Threshold, Algorithmic Optimization
(D) number of parameters, 1 billion parameters, self-supervised learning
(E) number of parameters, 1 billion parameters, scalability
Any other entries, before we run the poll to determine the winner?
If so, add your 3 terms to the Official Thread!
Looking for 3 technical terms:
(1) Technical term for distinguishing measure: If you had to pick one quantitative measure with which to distinguish AI “foundation models” from traditional non-foundation models, what would that quantitative measure be? What, exactly is that measure measuring, in concrete techical terms?
(2) Technical term for threshold: What would be the threshold for that quantitative measure, beyond which crosses into “foundation model” territory?
(3) Technical term for what makes crossing the threshold even possible: What’s would be the technical words to describe what makes it possible to cross that quantitative threshold? What, conceptually, makes crossing that threshold even possible?
Entries in the Official Thread so far:
(A) breadth, high breadth, ?
(B) number of parameters , billions of parameters, distributed training techniques
(C) Accuracy, Zero Shot Reasoning Threshold, Algorithmic Optimization
(D) number of parameters, 1 billion parameters, self-supervised learning
(E) number of parameters, 1 billion parameters, scalability
Any other entries, before we run the poll to determine the winner?
If so, add your 3 terms to the Official Thread!
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ChatGPT: How choose factors for dividing up concepts?
Task Utility, Objectivity, Stability, Parsimony, Completeness, Non-redundancy.
ChatGPT instantly pointing out many good reasons why most of the answers (to what should be the primary factor distinguishing traditional models from foundation models), including ChatGPT’s own initial answers, aren’t so great, and particular advice on directions to go next for improvement.
Now imagine an AI systematically going through all of these steps automatically. Going through millions of paths of thinking and backtracking, effortlessly.
Then imagine an AI being able to learn the intuition needed to skip going through the exhaustive steps, the next time it encounters similar problems.
Task Utility, Objectivity, Stability, Parsimony, Completeness, Non-redundancy.
ChatGPT instantly pointing out many good reasons why most of the answers (to what should be the primary factor distinguishing traditional models from foundation models), including ChatGPT’s own initial answers, aren’t so great, and particular advice on directions to go next for improvement.
Now imagine an AI systematically going through all of these steps automatically. Going through millions of paths of thinking and backtracking, effortlessly.
Then imagine an AI being able to learn the intuition needed to skip going through the exhaustive steps, the next time it encounters similar problems.
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