Machine learning and deep learning fall under the topic of artificial intelligence. Machine learning describes a process of computers acquiring knowledge on their own. Deep learning has become the most common method of machine learning: This involves a computer acquiring its knowledge using an algorithm, which is used to analyze large volumes of data, and learning to draw conclusions based on this data. Here’s a simple example: Let’s say we want a system’s algorithm to learn how to identify stop signs. We show it one million pictures of stop signs; it accumulates experience as a result. On this basis, the system is subsequently able to identify a stop sign when it appears.
Analyzing images, evaluating data, identifying illnesses – when it comes to these tasks, artificial intelligence is in part already superior to the human brain. It also works without becoming fatigued and is able to respond within a fraction of a second. Thanks to these characteristics, AI is used in areas such as autonomous driving, driver assistance systems, and industrial applications. Collaborative robots, for example, can be trained in new tasks using sample data and machine learning. The limits of AI systems lie in direct interactions with people. Currently, they do not yet have any emotions, empathy, or social intelligence.
AI systems will drive us around in cars, manage our appointments as personal office assistants, and answer questions as service robots. When they’re integrated into smart homes, they will help save energy. AI systems in the form of nursing robots could even look after old and sick people. This wealth of possibilities does, however, need to be handled responsibly. How do we ensure that the algorithms behind artificial intelligence are transparent and controllable? Can AI be permitted to make life-or-death decisions, such as in combat drones? If companies and civil societies value the conscientious use of technology, they must find answers to these ethical questions.
AI systems are being developed by numerous companies, start-ups, and research institutions around the world. We’d like to mention two researchers from Germany as examples: Jürgen Schmidhuber is considered the father of modern artificial intelligence. The neural networks he developed with his team are found in three billion smartphones today, and are also used by Google, Apple, and Facebook. Meanwhile, Bernhard Schölkopf is head of the Max Planck Institute for Intelligent Systems in Tübingen, and numbers among the world’s leading scientists in the area of machine learning. Researcher and entrepreneur Oren Etzioni is also highly renowned in the field of AI. He’s the head of the Allen Institute for Artificial Intelligence in Seattle established by Microsoft co-founder Paul Allen.
Finding the best move in chess. Finding the best sequence of stock trades. Finding the best candidate for a job in less time. Analyzing post surgery patients to prevent relapse and re-hospitalization. Using continuous patient monitoring to gain baselines and early detection of problems. Analyzing CCTV video for anomalous behavior and security threat. IBM Watson can find insights quicker than humans. AI is being used to review and suggest corrections in contracts. AI is being used for 1000's of customer questions per month with 95% accuracy provided in seconds.
Google Duplex can make phone calls to make restaurant and hair appointments. Google Deep Mind won a global Starcraft game challenge against gaming pros. Amazon uses AI for book and product recommendations. Websites are using Chat-bots to answer basic customer queries. Airports are using image recognition for staff security. Rolls Royce is using AI for predictive maintenance and servicing of airplane engines. Informatica is using AI for compliance and data gathering and analysis purposes. Fintech is using AI to combine and analyse more diverse datasets. In Healthcare AI can help analyse more data for preventative medicine. Baidu in China is producing self driving buses for large cities.