Definition
AI Research involves exploring new techniques to improve how machines learn, reason, and interact with the world. It is the engine behind the rapid advancements in Generative AI and autonomous systems.
Types of AI Research
1. Fundamental Research
Focuses on the core theory of intelligence, mathematical foundations of neural networks, and developing entirely new architectures (like the Transformer).
2. Applied Research
Focuses on using existing AI techniques to solve specific real-world problems.
- Biotechnology: Using AI for Protein Folding and drug discovery.
- Healthcare: Improving diagnostic accuracy using Computer Vision.
- Environment: Using AI to model climate change and optimize energy grids.
The Research Process
- Hypothesis: Proposing a new way to improve a model (e.g., "adding more layers will improve reasoning").
- Experimentation: Training models on massive datasets using GPU Computing.
- Benchmarking: Evaluating the model on standard datasets (like ImageNet or MMLU).
- Publication: Sharing results in papers (often via arXiv) and presenting at conferences like NeurIPS or ICML.
Open vs. Closed Research
- Open Research: Publishing full papers and open-sourcing model weights (e.g., Meta's Llama).
- Closed Research: Keeping techniques proprietary for competitive or safety reasons (e.g., OpenAI's later GPT models).