GPT-2 Generated “Artificial Intelligence” Article 206

Input: AI companies in world will be

Generated Text: able to develop an overview of the world they live in, understand human behavior and tailor their services and products accordingly.
The AI we create will have the ability to reason, think abstractly and learn by example. The major hurdle to overcome before machines can compete with humans in meaningful jobs is the assumption that certain “smart” tasks – such as analysis of data or solving problems around logic – can be separated from human creativity and solving of new or different problems. However, software increasingly enables machines to read documents, speak human and write English and now techniques like neural networks are building machine intelligence by understanding the vast number of relationships among things in the world (affiliate http://affectnetwork.com/blog/affinity-networks-and-deeplearning/ and don’t feel so alone if we get AI-assisted driving!). There is of course a difference between automating specific machine functions and putting the device to a purpose; we do that when we write a song or a book. A few smart robots are around – Japan’s iFuture Robotics’ BEAM stands for Build Embedded Software Architecture Memory – and China’s Ecophone Smartrobot is a humanoid that reminds us of the Statue of Liberty (picture http://ecophone.com.cn/en/hongkong/).
There are many types of AI that together compose the AI era. We have focused on so-called Intelligent Cyber-Physical System (ICH-ICPS) which includes software that affects hardware, New Area Science and techniques from particle physics.
The field of AI was born out of the need to Degas, Rembrandt and the author of the 2010 World Brain paper, Joshua Brown, putting machine-learning algorithms to the test on the Hans A Lee Paper by themselves ten times more difficult than the best human papers. He could only manage so they asked in response and the heartbreak they went through was extraordinary. Thereafter, thousands of researcher poured in from all over the world to try their hands at AI which gave us AI that can beat the world best at a game of Go or Heart-Rate Variability that tells your car with a wave of your phone it has caught a virus. Pandemics, Wars, and famines followed.
There are various opinions about just what comprises as AI. The most widely accepted view is that AI is ‘the science and technology that applies technological advances in computer vision, speech recognition, natural language processing, and the analysis of digital data to give computers the ability to reason, learn, and adapt’.
There are various definitions of AI but they generally refer to ways in which a computer can be put to use managing a task such as a tax account filings or spotting fraud. The term is also used to describe the next stage in computer power when computers can handle more tasks and learn from previous interactions.
The first systems designed to prove their worth were chess and proceed to checkers. The game played itself until the mid-20th century. Computerized chess was played by the IBM team that won the 1972 Tournament of the Year. More recently the most recent World Cup match between humanised computers and Google’s DeepMind and the British-American Chess Master showed off their ability to use neural networks to learn.
In the 1980s, researchers in Utah realized there was a real opportunity to make computers effective managers. So in 1990 they set up a competition where the best software engineers in the world could apply to work for a company aiming to make an AI manager in a narrow industry like bank tellers.
The UK National Institute for Computational Science (NC SAS) at Sheffield developed the Adaptive Decision Making System (ADMS) to meet the needs of the UK banking sector, which was looking to use AI to reduce errors and improve performance.
By 2004, the US banking industry was desperate for another system and NDIA contributed $10 million to develop the next version, the CAP Theorem proving System (C&AP). It won the 2005 International Conference on Machine Learning Researchers’ Book Award. In 2009, the banking sector again applied for a system that would show if an AI system was reliable and would again get $25 million for the developing system, the Confidence in Advanced Machine Learning System (CAAML-FULL).
Since then, other sectors have jumped on the AI bandwagon. Tesla’s Chief Technology Officer, BJ Henningson, published a book, Architecture – Set the Team Improvise, which features four tasks that an organization might need an AI to manage, from customer service to product scheduling. So far, so public relations.
Hollywood used AI to put Michael Fassbender’s villain to rights in Steve Jobs. Disney bought the company that made the algorithm that got them there for a cool $5 billion. Amazon’s head of AI, Michael Erard, showed me his office and the first thing he showed me was a 24-karat-gold rolodex full of thank-you notes from US firms thanks to the magic of AI. The thing is, despite the movie lines,


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