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Reflections on course 'Generative AI for Everyone'

Course: Generative AI for Everyone

The course "Generative AI for Everyone" discusses the design principles, practical applications, and potential societal impacts of Generative AI (GAI). It shares a similar structure with the "AI for Everyone" course, highlighting the differences between GAI and traditional AI, as well as between general-purpose AI and Artificial General Intelligence (AGI).

Week 1: What is Generative AI?
Generative AI (GAI) is a type of AI that predicts the next step based on existing content and uses the results as a reference for future iterations. In the realm of imagery, it involves identifying and clarifying images from noise. A key characteristic of GAI is that smaller models have limited growth potential and don't improve significantly with more data, whereas larger models have greater potential for development. In terms of accuracy, GAI is not as effective as Web Search. GAI is better suited for simple interactions, summarizing long articles, and inspirational conversations.

Week 2: Applications and Evolution of Generative AI
Currently, AI is effectively used for deriving actions, deducing context, and providing reference opinions. Different AI architectures excel in various task types. Evolving AI models currently include Retrieval Augmented Generation (RAG) and Fine-tuning. The course explores how to obtain answers aligned with objectives from existing models, focusing on methods like Instruction tuning and Reinforcement Learning from Human Feedback (RLHF).

Week 3: The Impact of Generative AI on Society
This week's focus is on the impact of Generative AI (GAI) on society. It covers how, while many tasks are still beyond current AI capabilities, AI can assist workers in areas where it excels, improving and even automating tasks. The introduction of AI in businesses might not always be cost-saving, but it offers an opportunity for companies to reevaluate and possibly enhance their processes, including customer interactions. Current Large Language Models (LLMs) can respond to general-purpose queries, while the emerging topic of Artificial General Intelligence (AGI) looks at machines performing tasks at a level comparable to a high school student. This session also discusses the influence of GAI and LLMs on higher-paid jobs, contrasting with past automation technologies that mainly impacted lower-wage jobs. The development of responsible AI is emphasized, focusing on fairness, transparency, privacy, security, and ethical use.

After completing two of Andrew Ng's courses, one can truly sense his passion for AI. I too believed, even before taking AI courses, that humans won't be replaced by AI, but by those who know how to use it. Just like in the primitive era, civilizations that mastered fire advanced to the next stage. However, it's foreseeable that, regardless of AI's widespread application, the demand for AI engineers might remain limited, similar to Unreal Engine engineers in today's society. Yet, enterprises might start considering 'AI proficiency' as an additional requirement for tech positions.

In modern times, where fraudsters and aggressors have also entered the online world, Europe has established GDPR (EU General Data Protection Regulation) to protect its citizens. This regulation, while essential, somewhat hinders AI development. I favor the development of open-source models, which can prevent misuse, as experts across related fields can work to counteract any crisis created using these models. GDPR might push AI models towards privatization, complicating the clarification of misinformation for well-intentioned companies and obscuring the principles behind malicious activities by nefarious corporations. Industries, especially academia, aiming to build upon the work of others, need to make more detailed distinctions in their operations, which might conflict with service providers, like subscription services that inherently include identity recognition features. Subscription services have effectively curtailed the piracy that has plagued the software industry for decades.

This course is highly recommended for beginners in Generative AI.

 

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