Topic-1b. What Is AI? PDF

What is AI and Machine Learning? A Few Quotes AI & Machine Learning “A breakthrough in machine learning would be worth ten Microsofts” (Bill Gates, Chairman, Microsoft) “Machine learning is the next Internet” (Tony Tether, Director, DARPA) Machine learning is the hot new thing” (Joh...

What is AI and Machine Learning? A Few Quotes AI & Machine Learning “A breakthrough in machine learning would be worth ten Microsofts” (Bill Gates, Chairman, Microsoft) “Machine learning is the next Internet” (Tony Tether, Director, DARPA) Machine learning is the hot new thing” (John Hennessy, President, Stanford) “Web rankings today are mostly a matter of machine learning” (Prabhakar Raghavan, Dir. Research, Yahoo) “Machine learning is going to result in a real revolution” (Greg Papadopoulos, CTO, Sun) “Machine learning is today’s discontinuity” (Jerry Yang, CEO, Yahoo) What is Artificial Intelligence? Definition The science of training machines to perform human tasks Artificial intelligence (AI) makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks. Artificial intelligence is not here to replace us. It augments our abilities and makes us better at what we do. Because AI algorithms learn differently than humans, they look at things differently. They can see relationships and patterns that escape us. What is Artificial Intelligence? Human AI Partnership This human, AI partnership offers many opportunities. It can: Bring analytics to industries and domains where it’s currently underutilized. Improve the performance of existing analytic technologies, like computer vision and time series analysis. Break down economic barriers, including language and translation barriers. Augment existing abilities and make us better at what we do. Give us better vision, better understanding, better memory and much more. What is Artificial Intelligence? Video Why is AI Important? Advantages AI automates repetitive learning and discovery through data. AI adds intelligence to existing products. AI adapts through progressive learning algorithms AI analyzes more and deeper data AI achieves incredible accuracy AI gets the most out of data. Applications of AI AI Domains Health Care AI applications can provide personalized medicine and X-ray readings. Personal health care assistants can act as life coaches, reminding you to take your pills, exercise or eat healthier. Retail AI provides virtual shopping capabilities that offer personalized recommendations and discuss purchase options with the consumer. Stock management and site layout technologies will also be improved with AI. Manufacturing AI can analyze factory IoT data as it streams from connected equipment to forecast expected load and demand using recurrent networks, a specific type of deep learning network used with sequence data. Banking Artificial Intelligence enhances the speed, precision and effectiveness of human efforts. In financial institutions, AI techniques can be used to identify which transactions are likely to be fraudulent, adopt fast and accurate credit scoring, as well as automate manually intense data management tasks. So What is Machine Learning? Automating automation Getting computers to program themselves Writing software is the bottleneck Let the data do the work instead!  Data Computer Output Program Traditional Programming Data Computer Program Output Machine Learning Magic? No! More like gardening Seeds = Algorithms Nutrients = Data Gardener = You Plants = Programs What is Machine Learning Video ML in a Nutshell Tens of thousands of machine learning algorithms Hundreds new every year Every machine learning algorithm has three components: Representation Evaluation Optimization Machines Can & Cannot What do you expect in Machine Learning? Machines Can Forecast Memorize Reproduce Choose Best Item Machines Cannot Create Something New Get Smart Really Fast Go Beyond Their Task Components of Machine Learning Algorithm Decision trees KNN Representation Neural networks Machine Learning Algorithm Support vector machines Accuracy Precision and recall Evaluation Squared error Posterior probability Entropy Combinatorial optimization Optimization Convex optimization Constrained optimization Three Components of Machine Learning 1. Data: The more diverse the data, the better the result. 2. Features: Parameters or variables. These are the factors for a machine to look at. 3. Algorithms: Any problem can be solved differently. The method you choose affects the precision, performance, and size of the final model. If the data is bad, even the best algorithm won't help. Learning vs. Intelligence Artificial intelligence is the name of a whole knowledge field, similar to biology or chemistry. Machine Learning is a part of artificial intelligence. An important part, but not the only one. Neural Networks are one of machine learning types. A popular one, but there are other good guys in the class. Deep Learning is a modern method of building, training, and using neural networks. Basically, it's a new architecture. Nowadays in practice, no one separates deep learning from the "ordinary networks". We even use the same libraries for them.  Breakout Session How do you think AI is used in your area? Breakout Session (Applications of AI) Pick the right AI Class Activity Emoji Scavenger Hunt Class Activity https://emojiscavengerhunt.withgoogle.com/