Interests in 2023

Apart from high school, this is what I’ve been upto in 2023. There are multiple notable changes in my interests. I will go over what they are, and what they signify.

# Artificial Intelligence

In 2023, I have developed a strong interest for artificial intelligence. Since November of 2022, I’ve been hands-on with ChatGPT, and through sheer curiosity and interest, have been following with the highly mercurial and protean world of AI development.

1. LLM & GPT: The world was shocked to see the impressive amount of intelligence that OpenAI was able to create using a Language Model. GPT models that work as token-predictors, essentially ‘a smart autocomplete’ have created a massive ripple in the world of technology. OpenAI has shown monumental advancement in AI capabilities over just 3-5 years ago through GPT 3 & 4. 3-5 years ago, AI chatbots were useless. I’m following the latest research and advancements in this field and am developing an appreciation for the potential impact of these technologies on society.
2. Machine Learning: These fields are closely related to AI, and can provide a practical understanding of how algorithms learn from data and made decisions. One needs to gain a strong fundamental understanding of how deep learning works because without them, AI seems like a black-box. I have to ‘cross the bridge’ of information-encapsulation to ‘grok’ AI and become an expert.
3. AGI: Artificial Generative Intelligence, or essentially an Advanced AI capable of any general intellectual task. The goal of today’s efforts in AI are to converge, to create AGI. It is all quite interesting. I’m following the latest research and advancements in this field and am developing an appreciation for the potential impact of these technologies on society.
4. AI Tools: Today’s AI tools are still tools. Learning to use them, push them to the edge, deeply understanding how they work and how companies are innovating is very important to anyone in this field. Imagine the 1980s, where being able to use a computer was one of the highest paid skill per hour. AI is a new tide, and one must embrace it to avert job displacement.
5. Ethical Debates: Three major areas of ethical concern for society related to AI are: privacy and surveillance, bias and discrimination, and the role of human judgment. There are debates around privacy safeguards and how to overcome bias in algorithmic decision-making, which can be influenced by conscious and unconscious prejudices of program developers and those built into datasets used to train the software. The question of whether smart machines can outthink humans, or if certain elements of human judgment are indispensable in deciding some of the most important things in life, is another area of ethical debate. The potential for AI to replicate human biases and confer on these biases a kind of scientific credibility is also a concern.

# Rationality and Metaphysics

Researching Bing AI let me to discover Lesswrong.com, a website that has enriched my understanding of AI beyond what I found on any other source. Its online discussions and debates provide a unique pleasure and appeal to a part of my brain that other platforms don’t. Lesswrong offers a common ground for discussing Rationality, AI, Metaphysics, and other fascinating topics. Rational thinking is essential to human cognition, playing a crucial role in decision-making, problem-solving, and critical thinking. Through Lesswrong, one can gain a deeper understanding of logical and rational thinking, becoming a more effective thinker and making better-informed decisions.

1. Rationality: has both normative and descriptive dimensions. Normative rationality refers to how an agent ought to reason to attain a goal, while descriptive rationality focuses on how humans actually reason in practice. Rationality involves making decisions and forming beliefs based on reason, knowledge, and evidence while taking into account one’s values, emotions, and personal experiences. Learning about rationality and trying to incorporate it in my life makes me push myself, but I believe it’s worth it.
2. Neuroscience and Cognitive Science: These disciplines explore the mysteries of the human brain and its processes, which are the source of our intelligence and consciousness. We can gain a deeper understanding of consciousness and intelligence through the study of artificial intelligence systems. As we strive to create machines that can match or surpass human intelligence, we are forced to confront questions about what makes us unique as a species, our limitations, and our potential for growth and development.
3. Metaphysics: Lesswrong is a great platform for exploring metaphysical topics that can enhance our understanding of AI and human thinking. By delving into the nature of intelligence, the structure of human and artificial thinking, and the fundamental aspects of reality, you can satisfy your profound curiosity and gain insights into the nature of consciousness, the relationship between the mental and the physical, and the existence of abstract entities like mathematical objects. These insights can potentially lead to the development of more robust and efficient AI systems and a deeper understanding of human cognition.

# Computer Science

1. Rust and TypeScript: Rust is a systems programming language that offers high performance, memory safety, and concurrency without sacrificing expressiveness or productivity. As good as Python may be, every great developer needs to know some low-level languages, and the C++ of yesteryear is the Rust of today. TypeScript is a superset of JavaScript that adds optional static typing, class-based object-oriented programming, and other features that make JavaScript more scalable and maintainable. Both languages have large and active communities, rich ecosystems of libraries and tools, and support for multiple platforms and paradigms. I need not elaborate on the usefulness of knowing JavaScript.
2. Complex Systems and Network Theory: These areas focus on the study of complex systems and the relationships between their components, which could be relevant to understanding the dynamics of large-scale AI systems and their interactions with other systems. I admit this is a novel interest, but my interest in Computer Science will eventually lead me into studying about this, and I look forward to it.
3. Game Theory and Decision-Making: Game theory studies strategic decision-making in competitive situations and could be useful for understanding the behavior of AI agents in various scenarios, as well as informing the development of rational decision-making processes. This seems incredibly interesting and something I already somewhat do in my life - making academic systems fun by gamification.