AI/ML Quiz

Generative AI: What's the main goal of Generative AI?

• A) Create chaos and confusion

• B) Generate realistic and original content

• C) Predict lottery numbers

• D) Write Shakespearean sonnets

Computer Vision: What do computers do with images in Computer Vision?

• A) Make memes

• B) See and interpret visual data

• C) Ignore them like your unread emails

• D) Paint them like a Picasso

Natural Language Processing:

What's a computer's favorite thing to do with words in NLP?

• A) Translate Shakespeare into emoji

• B) Write love letters to other computers

• C) Understand and analyze human language

• D) Turn words into tasty snacks

Computer Vision: What do computer vision algorithms dream about at night?

• A) Electric sheep

• B) Pixels dancing in binary

• C) Puppies playing fetch

• D) Solving the mysteries of the universe

LLMs with Different Domains: What is the focus of Large Language Models (LLMs) with different domains?

• A) Teaching computers to speak human languages

• B) Analyzing the language of dolphins

• C) Understanding specific fields like medicine or law

• D) Creating a universal language for robots

What is the primary task of Natural Language Processing (NLP)?

• A) Teaching computers to speak Klingon

• B) Helping computers understand and generate human language

• C) Translating cat meows into human language

• D) Deciphering ancient hieroglyphs

LLMs with Different Domains: What's the preferred bedtime story for a Legal BERT model?

• A) Harry Potter and the Order of the Legal Documents

• B) The Adventures of Legal Sherlock Holmes

• C) The Law and Order of the Rings

• D) Alice's Adventures in Legal Wonderland

AI Applications/Use Cases of AI: What does an AI-powered chatbot dream about?

• A) Conversations with humans

• B) Solving complex equations

• C) Becoming a real human

• D) Building a digital empire

AI Applications/Use Cases of AI: Which of the following is a practical application of AI in healthcare?

• A) Sending patients to the moon for treatment

• B) Predicting the outcome of sports events

• C) Diagnosing diseases from medical images

• D) Teaching doctors how to juggle