Introduction:

This week’s lecture on Artificial Intelligence, opened our eyes to the incredible capabilities of machines that mimic human intelligence. We explored how AI isn’t just about performing calculations—it’s about learning, decision-making, and even perceiving the world in ways that were once the realm of science fiction. I personally enjoy AI and everything AI related.

Key Concepts Covered:

Defining AI, ML, and Deep Learning:

• Artificial Intelligence is the broader ability of machines to imitate human behavior, from visual perception and speech recognition to decision-making.
• Machine Learning is an approach that lets machines learn from data, improving their performance over time without explicit programming.
• Deep Learning is a subset of ML that uses neural networks (like Transformers) to analyze and generate complex patterns, such as natural language or images.

State Space Search and Intelligent Problem Solving:

We delved into state space search, a classic technique in “Good Old Fashioned AI” (GOFAI), which helps break down complex problems into manageable steps. This method is essential for tasks ranging from solving puzzles to navigating through a digital map.

Real World AI Applications:

The lecture also showcased how AI is being used today—from speech recognition and text analysis to image recognition and beyond—highlighting both the incredible progress and the challenges that remain.

Task Documentation:

Activity 1:

• Hands-On Experiment: Use the Teachable Machine to create a simple ML model that categorizes objects based on their visual features.