
5G Academy - AI/ML - English
Authored by Maurizio Pinto
Professional Development
Professional Development
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8 questions
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1.
MULTIPLE CHOICE QUESTION
45 sec • 1 pt
What is one of the main goals of artificial intelligence?
Emulate human thinking
Completely replace human intelligence
Completely automate every human process
Optimize efficiency in specific tasks
2.
MULTIPLE CHOICE QUESTION
45 sec • 1 pt
What does the term "machine learning" represent in the field of artificial intelligence?
The ability of a system to learn from experience without being explicitly programmed
The creation of machines that can think autonomously like humans
The use of robots to automate manual tasks
The simulation of biological processes in the computer
3.
MULTIPLE CHOICE QUESTION
45 sec • 1 pt
What does the cost function measure during the training of a machine learning model?
The accuracy of the model on the training data
The complexity of the model
The time required to train the model
The distance between the model's prediction and the true value
4.
MULTIPLE CHOICE QUESTION
45 sec • 1 pt
What is one of the main aspects that make GPUs (Graphic Processing Units) crucial for training machine learning models?
Their ability to process large amounts of data in parallel
Their ability to withstand extreme temperatures
Their ability to connect to the internet via Wi-Fi
Their flexibility in executing complex logical operations
5.
MULTIPLE CHOICE QUESTION
45 sec • 1 pt
What is one of the most well-known architectures of Large Language Models?
Long Short-Term Memory (LSTM)
Generative Pre-trained Transformer (GPT)
Bidirectional Encoder Representations from Transformers (BERT)
Embeddings from Language Models (ELMO)
6.
MULTIPLE CHOICE QUESTION
45 sec • 1 pt
What is the goal of the encoder in generative AI?
Generate new data from an input distribution
Encode input data into a latent representation space
Decode input data to generate coherent output
Classify input data into predetermined categories
7.
MULTIPLE CHOICE QUESTION
45 sec • 1 pt
What is meant by "fine-tuning" in a Large Language Model?
Optimizing parameters during training
Adding new layers to the neural network
Adapting the model to a specific task through training on additional data
Reducing the complexity of the neural network
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