Artificial intelligence touches every part of our lives. It powers our shopping and TV recommendations; it informs our medical diagnoses. Embracing this new world means mastering the core algorithms at the heart of AI.
Hi Rishal Hurbans,
What AI method actually used for TV recommendations?
Are the watching video app such as Youtube using AI method (Eg: Intelligence Search) too ?
Hi Randy. Regarding YouTube, Netflix, and similar services, AI algorithms are used for search and recommendations. These usually feed into each other. Notice that when you search for a movie on Netflix that isn't available, it will recommend movies with similar themes and often storylines. Content recommended to you is also powered by this engine. This learning is happening based on data from everyone's interactions. Apart from streaming services, some traditional AI algorithms like genetic algorithms have been employed in linear television advertising - that is pricing ads, and choosing the best time to show the ads based on the audience, content, and sometimes even world news. Finding the most optimal placement of ads can be seen as a search which many algorithms in the book are suitable for.
Few years ago when I was in University, I have implemented an Itinerary Planning System which incorporate with AI technique, that is Case-based Reasoning for my final year project.
Is this technique belongs to Grokking AI Algorithms or belongs to Machine Learning? I'm confused.
Life is but a BREATH
posted 3 weeks ago
Good question. I think it's best answered with these extracts from the book.
For the sake of our sanity, and to stick to the practical applications in this book, we will loosely define AI as a synthetic system that exhibits “intelligent” behavior. Instead of trying to define something as AI or not AI, let’s refer to the AI-likeness of it. Something might exhibit some aspects of intelligence because it helps us solve hard problems and provides value and utility. Usually, AI implementations that simulate vision, hearing, and other natural senses are seen to be AI-like. Solutions that are able to learn autonomously while adapting to new data and environments are also seen to be AI-likeness.
Here are some examples of things that exhibit AI-ness:
A system that succeeds at playing many types of complex games
A cancer tumor detection system
A system that generates artwork based on little input
A self-driving car
The bottom line is that AI is an ambiguous term that means different things to different people, industries, and disciplines. The algorithms in this book have been classified as AI algorithms in the past or present; whether they enable a specific definition of AI or not doesn’t really matter. What matters is that they are useful for solving hard problems.