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Amazon Exam AIF-C01 Topic 2 Question 15 Discussion

Actual exam question for Amazon's AIF-C01 exam
Question #: 15
Topic #: 2
[All AIF-C01 Questions]

A company wants to use a large language model (LLM) on Amazon Bedrock for sentiment analysis. The company wants to know how much information can fit into one prompt.

Which consideration will inform the company's decision?

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Suggested Answer: B

by Ruby at Nov 17, 2024, 09:13 PM

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Dominic
2 months ago
Temperature? What is this, a cooking exam? I'm pretty sure that's not gonna help with sentiment analysis on Amazon Bedrock. Maybe they should try the 'Preheat to 350°F' option instead.
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Linette
2 months ago
Model size, all the way! The bigger the model, the more it can fit into a single prompt. It's like trying to cram an entire library into a backpack - you need a bigger backpack!
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Rolf
2 months ago
Yes, the larger the model size, the more data it can handle in a single prompt.
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Stephaine
2 months ago
Model size is definitely important for fitting more information into one prompt.
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Jerry
3 months ago
Batch size? Really? I guess if they're running a whole bunch of prompts at once, it could be a factor. But come on, let's focus on the important stuff here - the model size and the context window.
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Willard
3 months ago
Context window, for sure! The company needs to know how much context the LLM can take in at once. It's like trying to read a book without the previous chapters - you just can't get the full story.
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Lenna
1 months ago
Agreed. The context window plays a crucial role in the effectiveness of sentiment analysis using the LLM on Amazon Bedrock.
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Franklyn
1 months ago
That's true. The company should consider the context window to ensure the LLM captures the necessary information.
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Nina
2 months ago
Exactly! The company should consider the context window size when deciding on using the LLM for sentiment analysis on Amazon Bedrock.
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Doug
2 months ago
So, the larger the context window, the more information the LLM can use to analyze sentiment accurately.
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Ilona
2 months ago
The context window is crucial for sentiment analysis. It determines the amount of text the model can consider at a time.
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Ashleigh
2 months ago
Context window, for sure! The company needs to know how much context the LLM can take in at once. It's like trying to read a book without the previous chapters - you just can't get the full story.
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Sunny
2 months ago
Exactly! If the context window is too small, the model might miss important information.
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Loreta
2 months ago
Context window, for sure! The company needs to know how much context the LLM can take in at once.
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Amalia
3 months ago
But what about the context window? Doesn't that also play a role in fitting information?
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Zana
3 months ago
I agree with Alica, the larger the model size, the more information can be included.
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Hui
3 months ago
Hmm, I'd say the model size is the key consideration here. The larger the model, the more information it can handle in a single prompt. But don't forget, you've got to have the compute power to back it up!
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Victor
2 months ago
C: So, it's a balance between model size and compute power for effective sentiment analysis.
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Allene
2 months ago
B: Definitely, but we also need to make sure we have the right compute power to support a large model.
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Victor
2 months ago
A: I agree, the model size is crucial for fitting more information into one prompt.
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Joesph
2 months ago
D: So, it's a balance between model size and compute power for effective sentiment analysis.
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Svetlana
2 months ago
C: But we also need to make sure we have enough compute power to support it.
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Veronika
2 months ago
B: Yeah, having a larger model can definitely handle more data at once.
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Lonny
3 months ago
A: I think the model size is crucial for fitting more information into one prompt.
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Alica
3 months ago
I think the model size is important for fitting information into one prompt.
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