Date(s) - 04/04/2019
6:00 pm - 8:00 pm
Blockchain — You’ve heard the term, now understand the impact
Digital technologies let people who’ve never met do business across borders and continents in an instant. But how can they trust one another without relying on bureaucracy and middlemen? How can security, identity, and ownership be guaranteed while still operating at the speed of the Internet?
Blockchains, or distributed ledgers, may provide the answer.
Companies, researchers, and governments are exploring how blockchains can secure trust without the need for middlemen or third parties. Leaders in a wide range of industries around the world are seeking to understand how distributed ledgers can help them operate more efficiently.
Bitcoin, Ethereum has been luring some investors with potentially huge reward – and scaring others away with equally big risks. Should we put it on our investment shopping list?
Entrepreneurs are currently rushing into this surging field with blockchain products and have triggered a flood of ICO funding. As an emerging market with low barriers of entry, what should entrepreneurs consider and understand in order to make the best ones successful?
AI (Artificial Intelligence), as per Wikipedia
Artificial intelligence (AI, also machine intelligence, MI) is intelligence demonstrated by machines, in contrast to the natural intelligence (NI) displayed by humans and other animals. In computer science AI research is defined as the study of “intelligent agents”: any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Colloquially, the term “artificial intelligence” is applied when a machine mimics “cognitive” functions that humans associate with other human minds, such as “learning” and “problem solving”.
The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring “intelligence” are often removed from the definition, a phenomenon known as the AI effect, leading to the quip, “AI is whatever hasn’t been done yet.” For instance, optical character recognition is frequently excluded from “artificial intelligence”, having become a routine technology. Capabilities generally classified as AI as of 2017 include successfully understanding human speech, competing at the highest level in strategic game systems (such as chess and Go), autonomous cars, intelligent routing in content delivery network and military simulations.
Artificial intelligence was founded as an academic discipline in 1956, and in the years since has experienced several waves of optimism,followed by disappointment and the loss of funding (known as an “AI winter”),followed by new approaches, success and renewed funding. For most of its history, AI research has been divided into subfields that often fail to communicate with each other. These sub-fields are based on technical considerations, such as particular goals (e.g. “robotics” or “machine learning”),the use of particular tools (“logic” or “neural networks”), or deep philosophical differences. Subfields have also been based on social factors (particular institutions or the work of particular researchers).
The traditional problems (or goals) of AI research include reasoning, knowledge representation, planning, learning, natural language processing, perception and the ability to move and manipulate objects. General intelligence is among the field’s long-term goals. Approaches include statistical methods, computational intelligence, and traditional symbolic AI. Many tools are used in AI, including versions of search and mathematical optimization, neural networks and methods based on statistics, probability and economics. The AI field draws upon computer science, mathematics, psychology, linguistics, philosophy and many others.
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