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Dell EMC Exam D-GAI-F-01 Topic 3 Question 2 Discussion

Actual exam question for Dell EMC's D-GAI-F-01 exam
Question #: 2
Topic #: 3
[All D-GAI-F-01 Questions]

In Transformer models, you have a mechanism that allows the model to weigh the importance of each element in the input sequence based on its context.

What is this mechanism called?

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Suggested Answer: B

In Transformer models, the mechanism that allows the model to weigh the importance of each element in the input sequence based on its context is called the Self-Attention Mechanism. This mechanism is a key innovation of Transformer models, enabling them to process sequences of data, such as natural language, by focusing on different parts of the sequence when making predictions1.

The Self-Attention Mechanism works by assigning a weight to each element in the input sequence, indicating how much focus the model should put on other parts of the sequence when predicting a particular element. This allows the model to consider the entire context of the sequence, which is particularly useful for tasks that require an understanding of the relationships and dependencies between words in a sentence or text sequence1.

Feedforward Neural Networks (Option OA) are a basic type of neural network where the connections between nodes do not form a cycle and do not have an attention mechanism. Latent Space (Option C) refers to the abstract representation space where input data is encoded. Random Seed (Option OD) is a number used to initialize a pseudorandom number generator and is not related to the attention mechanism in Transformer models. Therefore, the correct answer is B. Self-Attention Mechanism, as it is the mechanism that enables Transformer models to learn contextual relationships between elements in a sequence1.


by Blondell at Aug 04, 2024, 02:56 PM

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Julio
11 months ago
I believe it's B) Self-Attention Mechanism because it allows the model to focus on relevant parts of the input sequence.
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Louvenia
11 months ago
Latent Space? What is this, some kind of magical realm where the model hides its secrets?
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Candida
11 months ago
The mechanism that allows the model to weigh the importance of each element in the input sequence is called Self-Attention Mechanism.
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Kristine
11 months ago
No, latent space is not related to Transformer models.
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Tambra
12 months ago
Self-Attention Mechanism, of course! It's the secret sauce that makes Transformers so powerful.
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Ettie
11 months ago
That's right, it helps the model weigh the importance of each element based on context.
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Amira
11 months ago
I agree, it allows the model to focus on different parts of the input sequence.
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Tarra
11 months ago
Self-Attention Mechanism, definitely the key to Transformer models.
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Rebbecca
12 months ago
I'm not sure, but I think it's either A) Feedforward Neural Networks or B) Self-Attention Mechanism.
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Denny
1 years ago
I agree with Kati, Self-Attention Mechanism makes sense for weighing importance.
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Marshall
1 years ago
Haha, 'Random Seed'? Really? That's like mixing up a transformer with a slot machine!
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Dortha
11 months ago
Haha, 'Random Seed'? Really? That's like mixing up a transformer with a slot machine!
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Jina
11 months ago
B) Self-Attention Mechanism
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Lashandra
11 months ago
D) Random Seed
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Hyman
12 months ago
C) Latent Space
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Ivette
12 months ago
B) Self-Attention Mechanism
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Clorinda
1 years ago
A) Feedforward Neural Networks
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Kati
1 years ago
I think the mechanism is called Self-Attention Mechanism.
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