Free NVIDIA Generative AI LLMs Practice Questions

A.  

RAPIDS enables on-GPU processing of computationally expensive calculations and minimizes CPU-GPU memory transfers.

B.  

RAPIDS is a Python library that provides functions to accelerate the PCIe bus throughput via word-doubling.

C.  

RAPIDS provides lossless compression of CPU-GPU memory transfers to speed up data analysis.

A.  

RAG is an architecture used to optimize the output of an LLM by retraining the model with domain-specific data.

B.  

RAG is a methodology that combines an information retrieval component with a response generator.

C.  

RAG is a method for manipulating and generating text-based data using Transformer-based LLMs.

D.  

RAG is a technique used to fine-tune pre-trained LLMs for improved performance.

A.  

RAG can enhance the security features of AI systems, ensuring confidential computing and encrypted traffic.

B.  

RAG can improve the energy efficiency of AI systems, reducing their environmental impact and cooling requirements.

C.  

RAG can align AI models with one another, improving the accuracy of AI systems through cross-checking.

D.  

RAG can generate responses that cite reference material from an external knowledge base, ensuring transparency and verifiability.

A.  

Sigmoid function

B.  

K-means clustering function

C.  

Mean Squared Error function

D.  

Diffusion function

A.  

ReLU is a linear function while sigmoid is non-linear.

B.  

ReLU is less computationally efficient than sigmoid, but it is more accurate than sigmoid.

C.  

ReLU and sigmoid both have a range of 0 to 1.

D.  

ReLU is more computationally efficient, but sigmoid is better for predicting probabilities.

A.  

NeMo focuses on the morphology of a language by studying its words, and how they are formed.

B.  

NeMo helps researchers to develop models that trade-off size with minimum loss impact.

C.  

NeMo facilitates the creation of models for speech recognition and natural language understanding.

D.  

NeMo helps researchers develop state-of-the-art models for computer vision based on convolutions.

A.  

To remove redundant information from the input sequence.

B.  

To encode the semantic meaning of each token in the input sequence.

C.  

To add information about the order of each token in the input sequence.

D.  

To encode the importance of each token in the input sequence.

A.  

ActionScript

B.  

Tableau dashboard

C.  

JSON parser

D.  

Regular expression filter

A.  

Achieving the highest possible level of prediction accuracy in AI models.

B.  

Implementing complex algorithms to enhance AI’s problem-solving capabilities.

C.  

Developing AI systems with autonomy from human decision-making.

D.  

Ensuring AI systems have explicable decision-making processes.

A.  

A branch of artificial intelligence that focuses on creating models that can generate new and original data.

B.  

A branch of artificial intelligence that focuses on auto generation of models for classification.

C.  

A branch of artificial intelligence that focuses on improving the efficiency of existing models.

D.  

A branch of artificial intelligence that focuses on analyzing and interpreting existing data.