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| Section | Objectives |
|---|---|
| Applied Prompt Design | - Task-specific prompt construction - Domain-specific prompting scenarios |
| Evaluation and Ethics | - Bias, safety, and responsible AI use - Evaluating AI output quality |
| Foundations of Artificial Intelligence | - Basic AI concepts and terminology - Natural Language Processing overview |
| Prompt Engineering Principles | - Prompt refinement and iteration techniques - Prompt structure (instructions, context, persona, output format) |
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NEW QUESTION # 39
Which generative AI tool allows users to create engaging and dynamic content with templates and stock footage?
Answer: C
Explanation:
Invideois a generative AI platform specifically designed for video creation. It distinguishes itself from text-to- image or text-to-text models by providing a comprehensive suite of tools that combine AI-generated scripts with a library of stock footage, music, and templates. Users can provide a single text prompt describing a video concept, and the AI will generate a script, select relevant video clips, and even provide a voiceover.
This tool is a prime example of an "application-specific" generative medium. While ChatGPT can write the script and Midjourney can create the thumbnails, Invideo integrates these capabilities into a single workflow for content creators and marketers. The "prompting" in Invideo is often more about "Art Direction" than linguistic structure; users must specify the target platform (e.g., "YouTube Shorts"), the target audience, and the desired aesthetic. Evaluating this medium involves understanding how AI interacts with pre-existing assets (stock footage) versus creating entirely new ones from scratch. It represents the shift from "Generative AI" as a novelty to "Generative AI" as a functional production tool.
NEW QUESTION # 40
A person wants to use AI to digitize receipts for expense tracking. Which advanced AI tool should be used?
Answer: C
Explanation:
To digitize physical documents like receipts, the necessary technology isOptical Character Recognition (OCR). OCR is a specialized AI field that involves the conversion of images of typed, handwritten, or printed text into machine-encoded text. When you take a photo of a receipt, the AI analyzes the pixels to identify the shapes of letters and numbers, then translates those shapes into digital characters that can be stored in a database or an Excel spreadsheet.
In the context of expense tracking, advanced OCR does more than just "read" the text; it uses "intelligent character recognition" to understand the layout. It can identify which number is the "Total," which is the
"Tax," and which is the "Date" by looking at their positions on the page and the keywords nearby. This makes OCR an essential bridge between the physical and digital worlds. While a "Virtual personal assistant" (Option B) mightusean OCR tool to help you, the specific technology doing the work of digitization is OCR. It saves hours of manual data entry and reduces the human error associated with typing in long strings of financial data, making it a powerful "practical application" of AI in business and personal finance.
NEW QUESTION # 41
A person is using generative AI to create a social media post. Why is it important to write an effective prompt?
Answer: D
Explanation:
Writing an effective prompt is essential because it provides the logical framework the AI needs to process a request; primarily, the prompt prevents output that is nonsensical. Generative AI models are statistical engines that predict the next most likely word or character. Without a clear, well-structured prompt that includes instructions and context, the model can easily lose the "thread" of logic, leading to "hallucinations" or sequences of text that are grammatically correct but logically incoherent or irrelevant to the user's goal.
In the context of social media, where brevity and impact are key, an ineffective prompt might result in a post that uses the wrong hashtags, misses the brand voice, or includes bizarre metaphors that don't make sense to the audience. While no prompt can "ensure" a post will be well-received by humans (Option B) or guarantee absolute originality (Option D), a structured prompt guides the AI to stay within the bounds of human logic.
By providing specific constraints (e.g., "Write a 20-word caption about coffee in a joyful tone"), the user ensures the output is a sensible, usable piece of content rather than a random string of related words.
NEW QUESTION # 42
Which programming software task is well-suited for artificial intelligence?
Answer: B
Explanation:
Artificial Intelligence, particularly Large Language Models (LLMs) trained on vast repositories of public code, has become exceptionally proficient at suggesting code modifications. This task is well-suited for AI because code is inherently structured and follows strict logical and syntactical rules. AI can analyze a snippet of code, identify inefficiencies, detect potential bugs, and suggest more "pythonic" or optimized ways to achieve the same result. This is often referred to as "AI-assisted development" or "copiloting." While AI can certainly add comments to scripts, that is a relatively low-level task compared to the complex logic involved in code modification. Specifying project structure and performing user testing often require a high-level architectural understanding and human-centric feedback that AI currently lacks in a holistic sense.
Suggesting modifications involves the AI "understanding" the intent of the code and predicting the next logical sequence or identifying a better algorithm to solve a problem. This capability significantly accelerates the development lifecycle, allowing developers to focus on high-level logic while the AI handles boilerplate code and optimization suggestions. It bridges the gap between raw intent and functional implementation by leveraging the statistical likelihood of code patterns found in high-quality software libraries.
NEW QUESTION # 43
A bank uses an AI model to help evaluate loan applications. The model makes suggestions, but the bank employees have no knowledge of which criteria the model uses to evaluate applicants. What is the associated ethical concern described in the scenario?
Answer: A
Explanation:
The primary ethical concern in this scenario isTransparency, often referred to in the AI field as the "Black Box" problem. Transparency in AI means that the processes, logic, and data used by the system to reach a decision should be understandable and accessible to human stakeholders. When bank employees cannot explainwhya loan was denied, it violates the principle of "Explainability," which is a subset of transparency.
This lack of transparency is particularly problematic in high-stakes industries like finance, healthcare, and law. If a model is making biased or incorrect decisions, the lack of transparency makes it impossible to audit the system or correct the underlying error. Many modern regulations, such as the GDPR's "Right to Explanation," require that individuals affected by automated decisions have a right to know the logic behind them. Effective prompt engineering can help address this by using techniques like "Chain of Thought," where the AI is instructed to "show its work" or explain its reasoning process step-by-step, thereby transforming a black-box interaction into a more transparent, "white-box" process.
NEW QUESTION # 44
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