What does it mean to think? Learn about having a machine sense, reason, and act.
- In the very beginning, artificial intelligence…used something called the symbolic systems approach.…This approach allowed machines to act in a way…that seemed intelligent,…but in reality it was just complex pattern matching.…The symbolic systems approach allowed early programmers…to create expert systems.…These machines could do things…that were normally left to experts.…They could diagnose illnesses, give you a credit score,…and even help you with your taxes.…
The problem with these systems is that they…created long lists of matching patterns.…They also required experts to create these patterns.…You needed someone who knew Chinese…to match every possible phrase.…Maybe you'd need a doctor who would…come up with an answer…to every one of a patient's questions.…You had to create these long lists of matching patterns.…Sometimes this is called combinatorial explosion.…This type of effort made it extremely difficult…to create robust expert systems.…
There was also the very real possibility…that you wouldn't find a match.…
This course will introduce you to some of the key concepts behind artificial intelligence, including the differences between "strong" and "weak" AI. You'll see how AI has created questions around what it means to be intelligent and how much trust we should put in machines. Instructor Doug Rose explains the different approaches to AI, including machine learning and deep learning, and the practical uses for new AI-enhanced technologies. Plus, learn how to integrate AI with other technology, such as big data, and avoid some common pitfalls associated with programming AI.
- The history of AI
- Machine learning
- Technical approaches to AI
- AI in robotics
- Integrating AI with big data
- Avoiding pitfalls