Important Questions on Generative AI

In our previous blog of Generative AI questions and answers, we have discussed questions on Gen AI with explanations. Now, we take a deeper dive into the most critical questions surrounding this groundbreaking technology. From unraveling the basics of Gen AI  to exploring the latest advancements in AI models like GPT-4, Dall E 3, this blog post addresses the important questions that will shape the future of AI. Whether you're an AI researcher, a student, or simply curious about the future of technology, join us as we uncover the answers that will empower you to navigate the ever-evolving landscape of Generative AI. 

Part One of Gen AI questions and answers.

Part Three of Gen AI questions and answers.

Stay tuned for more.


1. What is the goal of using context in a prompt?

    a) To confuse the model
    b) To limit the model's response
    c) To improve the model's understanding and response quality 
    d) To ensure slowing down of the model's processing speed

Answer: c) To improve the model's understanding and response quality

Explanation: 

The aim of using context in a prompt is to give additional information. This helps an AI model to understand the request in a better manner and to generate more relevant and accurate response. In contextual prompts we can add instructions, background information, constraints which will help and AI model to generate accurate, relevant, creative and time efficient response in return.


2. Which of the following is a primary function of Generative AI?

    a) Analyzing and interpreting existing data. 
    b) Creating new content like text, images, or music.
    c) Translating languages with high accuracy.
    d) Predicting future trends based on past data.

Answer: b) Creating new content like text, images, or music.

Explanation: 

Generative AI models are designed to generate new fresh content based on patterns which they learn from training done with existing similar data. This includes variety of tasks like writing text (Essay's, Poems, stories), creating images, composing music.


3. What is the main goal of Generative Al?

    a) AI >> DL >> ML >> Gen Al
    b) AI >> ML >> DL >> Gen Al 
    c) DL >> AI >> ML >> Gen Al
    d) None of the above

Answer: b) AI >> ML >> DL >> Gen Al

Explanation: 

The correct answer is option b that is AI >> ML >> DL >> Gen Al. This sequence indicates the hierarchy based on each one category is a subset of the one before it. AI is he broadest category with techniques designed to impersonate human intelligence. Machine Learning is a subset of AI in which algorithms are designed to learn from data without being programmed every time. Machine Learning.  is a superset of Deep Learning. Gen AI is a application of AI which is often harnesses power of Deep Learning designed to create new content like text, images, or music.


4. What is a key feature of generative Al?

    a) Supervised learning
    b) Generating new data similar to training data 
    c) Rule-based processing
    d) High computational speed

Answer: b) Generating new data similar to training data

Explanation: 

Gen AI models are designed to generate new data based on training done with existing similar data. This includes variety of tasks like writing text (Essay's, Poems, stories), creating images, composing music based on neatly written contextual prompt.


5. Which of the following is an example of a Generative AI model that can create images from text descriptions?

    a) GPT-3
    b) BERT 
    c) DALL-E 
    d) AlphaGo

Answer: c) DALL-E

Explanation: 

DALL-E (it's latest version DALL-E 3) is a Gen AI model designed to generate detailed images from text prompts. GPT-3 is a text to text Gen AI model. BERT is a Deep Learning Model based on Transformer architecture. AlphaGo is AI system specifically designed for the ancient Chinese game GO.


6. When prompting an LLM for a text generation task, what is the benefit of providing context or background information in the prompt?

    a) It adds unnecessary complexity to the prompt giving more accurate response.
    b) It helps the LLM understand the context and generate more relevant content.
    c) It confuses the LLM and leads to incorrect response from LLM model.
    d) It has no to minimum impact on the LLM's performance.

Answer: b) It helps the LLM understand the context and generate more relevant content.

Explanation: 

The additional data as context and background information helps an AI model to understand the request. It helps Gen AI model to generate accurate and more relevant response. In contextual prompts we can add instructions, background information, constraints which will help and AI model to generate accurate, relevant, creative and time efficient response in return.


7. What does "one-shot" prompting refer to in the context of LLMs?

    a) Providing only one prompt or query to the LLM for generating responses.
    b) Using only one LLM model for multiple tasks simultaneously.
    c) Training the LLM using only one example of the desired task. 
    d) Prompting the LLM with a single word for generating complex responses

Answer: c) Training the LLM using only one example of the desired task. 

Explanation: 

When it comes to train a Large Language Models (LLMs), 'one-shot' prompting is a technique where the model is given a single example of a task to perform before asking it to complete a similar task. It is is a quick way to guide an LLM models behavior without providing a large number of examples.


8. Which of the following statements is true about open source large language models?

    a) They cannot be modified by users of it.
    b) They are generally proprietary in nature and costs money.
    c) Their development is mostly controlled by one company.
    d) They allow for community contributions and improvements.

Answer: d) They allow for community contributions and improvements.

Explanation: 

Developers and researchers can collaborate for the enhancement of Open source LLMs, fostering innovation and improvement. People can leverage functionality of Open source LLMs without being restricted by licensing limitations.


9. What kind of learning method does Generative AI primarily rely on?

    a) Supervised learning
    b) Unsupervised learning
    c) Reinforcement learning 
    d) Transfer learning

Answer: b) Unsupervised learning

Explanation: 

Unsupervised learning involves training models mostly on unlabeled data, where the algorithm get's trained to understand relationships within the given input data and identify patterns. Generative AI models, like GPT, DALL E which are used to create images or text, are well trained on unsupervised learning. 


10. What is one way large language models can help in daily life?

    a) Improving writing style
    b) Helping in writing in blogs
    c) helping in understanding large PDFs
    d) All of the above 

Answer: d) All of the above

Explanation: 

The correct option among the given options is d, All of the above. LLM's can help in improving writing style by detecting grammar mistakes and spelling mistakes etc. LLM's can help in writing in blogs by generating new ideas, blog structures etc. based on the contextual prompts. LLM models can help in summarize the large content files like PDF's it can even help us find answers to the questions based on the data in PDF. 


11. Categorize ML Problem: Analyze a Traffic Light image to find the signal - Red or Green or Amber

    a) Regression
    b) Both
    c) Classification  
    d) None of the above

Answer: c) Classification  

Explanation: 

Classification is the categorizing of input data into predefined categories or classes in Machine Learning. In analysis of traffic light image, image is the input data and "Red," "Green," "Amber." are the predefined categories. The classification algorithm analyzes the image and determine to which category it belongs to.


12.  Which company developed Dall E 3 text to image Gen AI model?

    a) Google
    b) Microsoft 
    c) Both a & b 
    d) OpenAI 

Answer: d) OpenAI

Explanation: 

Dall E 3 (Latest version Dall E 3, previous versions Dall E, Dall E 2) is a text to image Generative AI model developed by OpenAI. It can help in generation of detailed images with the textual prompts.


13.  What are the types of Data?

    a) Unstructured
    b) Structured
    c) Both Structured & Unstructured 
    d) None of the above

Answer: c) Both Structured & Unstructured

Explanation: 

The data used to train Gen AI models are of Structured & Unstructured type. Structured data is organized in spreadsheet or database in a predefined format. Examples of structured data is spreadsheet containing data of employees monthly salary. Unstructured data do not have predefined structure is more free-flowing type. Examples of unstructured data is text files, PDF's etc.


14.  Why is controlling the output of generative Al systems important?

    a) To increase the efficiency of Al models in terms of output
    b) To reduce computational costs
    c) To ensure the accuracy of the output given by model
    d) To prevent the generation of harmful or offensive content 

Answer: d) To prevent the generation of harmful or offensive content 

Explanation: 

Preventing the generation of harmful, offensive content is essential because of Legal and Regulatory Compliance (Some content is not legal in some countries), Ethical Considerations (Misinformation like Deepfake video's, hatred speech causes social and political imbalance) Trust and Safety by user (Users will not adopt the new technology which is not safe). Accuracy, Computational costs and Efficiency are important but preventing harm is a higher priority.


15.  What is one major ethical concern in the use of generative Al?

    a) Efficient data storage
    b) Model interpretability
    c) Creation of biased content 
    d) Faster model training

Answer:  c) Creation of biased content 

Explanation: 

Gen AI models rely on available data to generate new data. If the existing available data is biased, the AI models can use and amplify those biases in their output with every iteration of content creation. In such a scenario it may generate content that is discriminatory and harmful to certain people, country or ethnicity. It may generate social and economic bias among countries or racial and gender bias between groups of people, so it is important control generation and iterative propagation of biased content.


We have a series of question answer articles in Gen AI listed below.

Part One of Gen AI questions and answers.
Part Three of Gen AI questions and answers.


Feeling curious about a specific Artificial Intelligence topic or Question? Don't hesitate to post your question in a comment below. Our team will be happy to assist you as soon as possible!

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