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Diffusion models are one of the most influential generative modeling techniques for image generation and, across many benchmarks, they outperform state-of-the-

Q1# Discssuion

Diffusion models are one of the most influential generative modeling techniques for image generation and, across many benchmarks, they outperform state-of-the-art GANs. 

Explain your opinion on the reasons for the popularity of diffusion models.
What is the real difference between diffusion models and GANs? 

Q2# Test 1: ChatGPT Training

ChatGPT is a tool that allows users to interact with their suite of large language models through a conversational interface. Describe the training process for ChatGPT and suggest which tool/network would you use for each part of the training process and justify your suggestion: 

Supervised fine-tuning / training tool / explanation
Reward modeling / training tool / explanation
Reinforcement learning / training tool / explanation 

Need by Monday evening

Discussion 3: diffusion models (500 to 600 words)

Diffusion models are one of the most influential generative modeling techniques for image generation and, across many benchmarks, they outperform state-of-the-art GANs. 

1. Explain your opinion on the reasons for the popularity of diffusion models.

2. What is the real difference between diffusion models and GANs? 

Test 1: ChatGPT Training

 

ChatGPT is a tool that allows users to interact with their suite of large language models through a conversational interface. Describe the training process for ChatGPT and suggest which tool/network would you use for each part of the training process and justify your suggestion: 

1. Supervised fine-tuning / training tool / explanation

2. Reward modeling / training tool / explanation

3. Reinforcement learning / training tool / explanation 

The post Diffusion models are one of the most influential generative modeling techniques for image generation and, across many benchmarks, they outperform state-of-the- first appeared on Writeden.

Diffusion models are one of the most influential generative modeling techniques for image generation and, across many benchmarks, they outperform state-of-the-
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