AIF ACTUAL EXAM PAPER LATEST WITH

AIF ACTUAL EXAM PAPER LATEST WITH

TESTED QUESTIONS AND DETAILED VERIFIED

ANSWERS GRADED A+

◉Artificial Intelligence . Answer: A field of computer science dedicated

to solving cognitive problems commonly associated with human intelligence.

◉Conversational AI . Answer: A technology that makes software

capable of understanding and responding to voice-based or text-based human conversations.

◉Generative AI . Answer: A type of AI that can create new content and

ideas, including conversations, stories, images, videos, and music.

◉Embedding . Answer: A numerical representation of real-world objects

that machine learning (ML) and artificial intelligence (AI) systems use to understand complex knowledge domains like humans do.

◉Supervised learning . Answer: This is a prominent type of machine

learning due to its vast range of applications. It's termed supervised learning because there must be a supervisor. 1 / 3

◉Classification . Answer: A supervised learning technique that assigns

labels or categories to new, previously unseen data examples using a learned model.

◉Regression . Answer: A supervised learning technique that predicts

continuous or numerical values given one or more input variables.

◉Unsupervised learning . Answer: The algorithm tries to discover

hidden patterns or structures within the data without any prior information or guidance.

◉Clustering . Answer: This method divides data into clusters based on

similar traits or distances between data points in order to better understand the characteristics of a particular cluster.

◉Dimensionality reduction . Answer: An unsupervised learning strategy

that minimizes the number of features or dimensions in a dataset while retaining the most relevant information or patterns.

◉Reinforcement learning . Answer: One continuously improves their

model by analyzing feedback from prior versions. In reinforcement learning, an agent learns by trial and error as it interacts with its surroundings.

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◉Intelligent Document Processing (IDP) . Answer: A software tool that

extracts and categorizes information from unstructured or structured data, generates summaries, and delivers actionable insights.

◉Adaptability . Answer: It can adapt to a variety of activities and

domains by learning from data and producing material that is suited to specific situations or needs. Because of its flexibility, generative AI can be applied to a wide number of sectors.

◉Responsiveness . Answer: It can generate content in real time,

resulting in faster reaction times and more dynamic interactions. This is especially beneficial for chatbots, virtual assistants, and other interactive applications that demand instant feedback.

◉Simplicity . Answer: It can make hard tasks easier by automating

content generation processes. For example, AI language models may generate human-like text, reducing the time and effort necessary for content development.

◉Creativity and exploration . Answer: It can develop new ideas,

designs, or solutions by combining and recombining pieces in unusual ways. This can encourage creativity and the discovery of new possibilities.

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