Artificial Intelligence (AI) refers to the ability of computers to perform tasks that typically require human intelligence — such as learning from data, recognizing patterns, and making complex decisions. Rather than being programmed with rigid rules, AI systems can infer rules from examples, improving their performance over time.
Key subfields of AI include:
- Machine Learning (ML): Algorithms that improve through experience.
- Deep Learning: Neural networks with multiple layers that model complex relationships.
- Natural Language Processing (NLP): Enabling machines to understand and generate human language.
Unlike traditional programming, where every step is explicitly written, AI-based systems learn from examples, making them adept at complex tasks like image recognition or language translation.
Everyday Touchpoints:
- Voice assistants (like Siri and Alexa) use NLP.
- Streaming platforms recommend content based on AI algorithms.
- Smartphones use AI for features like face recognition.
In research, AI is revolutionizing areas like medical image analysis and large-scale data mining, allowing researchers to uncover insights faster than ever.
Takeaway: Learning how AI functions under the hood equips researchers and editors to engage with it critically and creatively — a vital skill in today’s evolving landscape.
