Artificial Intelligence
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Diffusion models work by gradually adding noise to an image in a controlled manner and then learning to reverse this process to generate new images. Thus, the correct option among the ones you provided is: **2. They gradually add noise into the original image.** In detail, diffusion models start with an original image and iteratively add Gaussian noise over several time steps. During training, the model learns to predict and remove this noise

The best option that relates to the integration of ChatGPT with other systems is **3. API Key**. ChatGPT can be integrated into various applications and systems using an API, which requires an API key for authentication. This allows developers to incorporate ChatGPT's capabilities into their own platforms, such as chatbots, customer support systems, and other applications, leveraging the language model's functionalities.

3. All of the listed options. Improving the content created in response to a prompt can be achieved through a combination of writing clear instructions, writing specific instructions, and allowing extra time for the model to think. Each of these strategies contributes to enhancing the quality and relevance of the generated content. Clear and specific instructions help guide the model effectively, and giving it more time can lead to more

A typical challenge of Generative AI is **2. Difficult to create high quality content**. While generative models can produce a wide range of outputs, ensuring that these outputs are not only coherent but also of high quality and relevant to a specific context can be quite challenging. The models may struggle with issues such as maintaining consistency, avoiding biases, and generating content that meets human standards of creativity and relevance.

The correct option that defines self-attention mechanism is: 4. Representation of a sentence is computed by relating different words in it. Self-attention allows a model to weigh the significance of different words in a sentence when generating a representation, enabling it to capture contextual relationships effectively.

Let's address each question one by one: ### Question 23 **Which one of the following is not a staple food crop?** - a. Bread - b. Maize - c. Rice - d. Yams **Answer:** **a. Bread** - Bread is a food product made from staple crops like wheat, but it is not a staple food crop itself. --- ### Question 24 **Which one of the following observations from the accompanying figure is true?** - a. Solar was the most energy-demanding renewable source

To evaluate the statements based on the unspecified figure on global primary energy consumption by source, we can analyze each statement considering historical trends and general knowledge of energy consumption: a. **Solar was the most energy-demanding renewable source in 1970.** - This statement is likely false, as solar energy consumption was negligible in 1970 compared to other renewable sources like hydropower. b. **The difference in

The correct option is: **3. Instruction-tuned LLMs are for more refined results.** Instruction-tuned LLMs are specifically trained to follow instructions and produce outputs that align more closely with user expectations, making them generally more refined in their responses compared to base LLMs. Base LLMs are typically more general and lack this specific tuning for following instructions.

The correct answer is: **b. refers to a mix of farmer-driven, ecologically based pest control practices that seek to reduce reliance on synthetic chemical pesticides.** Integrated Pest Management (IPM) is an approach to pest control that combines various strategies and practices to manage pest populations in an environmentally and economically sustainable manner, emphasizing the reduction of chemical pesticide use.

The most economically and environmentally sound option to focus water resource management on is: **c. increasing the efficiency of the way we use water.** Improving water efficiency helps to conserve existing water resources, reduces waste, and can often be achieved through relatively low-cost measures compared to large-scale infrastructure projects like desalination plants or cloud seeding. It also minimizes environmental impacts associated

The idea behind Generative Adversarial Networks (GANs) is primarily about **pitting 2 neural networks against each other**. In a GAN, there are two components: a generator and a discriminator. The generator creates fake data, while the discriminator evaluates the authenticity of the data (whether it is real or generated). The generator aims to improve its performance to fool the discriminator, while the discriminator strives to become better at

The software application published by Synopsys and Simpleware that includes a module/feature called ACTEL_BASE is **Simpleware ScanIP**. **ACTEL_BASE** generally refers to a specific feature or functionality within Simpleware software that focuses on managing and processing 3D imaging data, especially in applications related to biomedical imaging, engineering, and materials science. It allows users to extract, manipulate, and convert imaging

Food stability primarily relates to: **d. Access to food at all times with no risk of losing such access.** Food stability focuses on the consistent availability and accessibility of food, ensuring that individuals and communities can obtain sufficient food over time without facing disruptions or shortages.

The most accurate distinction is **2. New content creation**. Generative AI specifically focuses on creating new content, whether it's text, images, music, or other forms of media. This contrasts with traditional AI, which may primarily be concerned with tasks such as classification, analysis, or making predictions based on existing data. While generative AI uses similar underlying technologies, like neural networks, its primary purpose revolves