Oracle Exam 1Z0-1127-24 Topic 1 Question 3 Discussion

Actual exam question for Oracle's 1Z0-1127-24 exam

Question #: 3
Topic #: 1

[All 1Z0-1127-24 Questions]

Which is a key advantage of usingT-Few over Vanilla fine-tuning in the OCI Generative AI service?

AReduced model complexity

BEnhanced generalization to unseen data

CIncreased model interpretability

DFoster training time and lower cost

Show Suggested Answer

Suggested Answer: D

by Reuben at May 29, 2024, 10:25 PM

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Chauncey

10 months ago

I'm just happy I don't have to spell 'T-Few' during the exam. That's a tongue-twister if I ever saw one!

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Wayne

10 months ago

I'm going with B. Enhanced generalization to unseen data. Isn't that what we all strive for in the world of AI? Bring on the versatile models!

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Lino

9 months ago

Reduced model complexity is also important, but I think B is the top advantage.

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Odette

9 months ago

I agree, B is definitely a key advantage. Generalization is crucial in AI.

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Rosalind

11 months ago

A. Reduced model complexity is the winner here. Simpler is better when it comes to AI, especially for the OCI Generative AI service.

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Aileen

10 months ago

D) Foster training time and lower cost

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Barney

10 months ago

B) Enhanced generalization to unseen data

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Andra

10 months ago

A) Reduced model complexity

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Paris

11 months ago

C. Increased model interpretability is the key advantage in my opinion. Gotta love those transparent AI models!

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Karina

11 months ago

D. Foster training time and lower cost is the way to go! Who doesn't love saving time and money in the AI world, am I right?

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Sherell

10 months ago

D) Foster training time and lower cost

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Rebeca

10 months ago

B) Enhanced generalization to unseen data

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Cammy

11 months ago

A) Reduced model complexity

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Charlene

11 months ago

I agree with Chun, using T-Few can help simplify the model.

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Chun

11 months ago

I think the key advantage is reduced model complexity.

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Hollis

11 months ago

I think the correct answer is B. Enhanced generalization to unseen data. T-Few seems like a more powerful technique for handling diverse inputs.

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Tabetha

10 months ago

I think it also helps with reducing model complexity, so A) Reduced model complexity could be another advantage.

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Deonna

10 months ago

I agree, B) Enhanced generalization to unseen data is a key advantage of using T-Few.

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Emile

10 months ago

I think it's D) Foster training time and lower cost. That's a big advantage for businesses.

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Kimberlie

10 months ago

Foster training time and lower cost are definitely benefits of T-Few over Vanilla fine-tuning.

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Cyril

10 months ago

Reduced model complexity is also important, but I think B) is the best choice.

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Anabel

11 months ago

I agree, B) Enhanced generalization to unseen data is a key advantage of using T-Few.

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Keshia

11 months ago

I agree, B) Enhanced generalization to unseen data is a key advantage of using T-Few.

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