Course: AI for Everyone
The course called "AI For Everyone," discussing the basic concepts of AI, its potential applications, and societal impact.
Week 1 focuses on AI concepts,
covering data interpretation, machine learning, corporate adoption of AI, limitations of AI, and examples of neural networks and deep learning.
covering data interpretation, machine learning, corporate adoption of AI, limitations of AI, and examples of neural networks and deep learning.
Week 2 delves into AI projects,
exploring developments in data science, machine learning, and neural networks. It emphasizes the complexity in decision-making capabilities of neural networks and the limitations of AI. The course also discusses the challenges for companies interested in developing AI strategies, emphasizing the need for expert evaluation of AI potential in projects, starting from material collection to creating feasible prototypes and the support required for such ventures. Only then should the formation of an AI team be considered.
exploring developments in data science, machine learning, and neural networks. It emphasizes the complexity in decision-making capabilities of neural networks and the limitations of AI. The course also discusses the challenges for companies interested in developing AI strategies, emphasizing the need for expert evaluation of AI potential in projects, starting from material collection to creating feasible prototypes and the support required for such ventures. Only then should the formation of an AI team be considered.
The translation of your text is as follows:
Week 3: AI and Industry
This week focuses on how industries can transform their knowledge into tasks manageable by AI for development. Examples of developed applications are provided, along with demonstrations of AI's limitations.
Week 4: AI and Society
People aware of technological advancements perceive AI as still immature. Despite excelling in specialized scenarios beyond human capabilities, AI's one-dimensional strength is limited in complex, multifaceted human life. Examples include AI navigation not always outperforming experienced taxi drivers, and AI customer service being inferior to human operators. A critical issue is humans unknowingly providing biased data to AI, only realizing it when AI makes biased decisions. Also, the unclear understanding of human learning processes makes it hard for AI to make comprehensive judgments on simple matters, like discerning emotions in customer service calls.
These insights reflect on the strong yet limited capabilities of AI in specific scenarios, highlighting the human aspiration to develop AI to support vulnerable aspects of our world.
AI is not new to me. Initially, I worked in the gaming industry, where I encountered AI as an opponent for players. After returning to school, I took courses like 'Natural Language,' studying how AI recognizes human language. There was also the popular Apple Siri. In various industries, basic professional AI tools have been developed. It was the emergence of ChatGPT, with its versatility, that transformed societal attitudes towards AI, fostering belief in its significant impact on human life. My interest in this field grew with the advent of generative AI."
Since I'm not very interested in specialized artificial intelligence, it might be like an encyclopedia, almost like a search engine. The versatility of generative AI has benefited me tremendously by providing me with more information outside of my own area of expertise, and has made me even more interested in the development of this technology. After all, my major is information engineering, and my level of expertise is probably at the level of: if I have any questions, I have to study technical documents or check their open source code. This is not something ChatGPT generally covers. (In order to confirm the correctness of this sentence, I asked ChatGPT again. It does provide a universal solution, but my environment is quite special and the universal solution cannot be implemented. This tool belongs to the HPC range in unpopular information. )
My interest in generative AI is more about how to build it than how to apply it. It is necessary to understand each stage of its development process and conduct practical experiments in order to provide effective suggestions for artificial intelligence transformation or assist in implementation for different research groups in the future. In addition, I have long-term interests and observations in the shortcomings of technological development, the limitations and shortcomings of artificial intelligence, and the relationship between technology and society. This course is a useful introductory course that provides beginners with a broad and useful introduction to artificial intelligence concepts, application suggestions and social impact.
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