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Applied AI - Creating machines with human know-how - Ayming UK

#artificialintelligence

Artificial intelligence (AI) is the branch of computer science that enables machines to perform activities that up to now have required human know-how, such as image or speech recognition. Virtual assistants are probably the most familiar everyday manifestations of AI, and the big players in the AI field have their own avatars: Siri (Apple), Alexa (Amazon), Google Assistant, and Cortana (Microsoft). However, the impact of applied AI is now being felt, particularly across sectors such as health sciences. Here, AI-driven solutions automate and improve the efficiency of complex processes for the early detection of certain cancers and reduce the risks to patients in treatment programmes for those conditions. Spending on cognitive and AI systems worldwide is expected to more than quadruple by 2021, according to International Data Corporation.


Creating machines that understand language is AI's next big challenge

#artificialintelligence

About halfway through a particularly tense game of Go held in Seoul, South Korea, between Lee Sedol, one of the best players of all time, and AlphaGo, an artificial intelligence created by Google, the AI program made a mysterious move that demonstrated an unnerving edge over its human opponent. On move 37, AlphaGo chose to put a black stone in what seemed, at first, like a ridiculous position. It looked certain to give up substantial territory--a rookie mistake in a game that is all about controlling the space on the board. Two television commentators wondered if they had misread the move or if the machine had malfunctioned somehow. In fact, contrary to any conventional wisdom, move 37 would enable AlphaGo to build a formidable foundation in the center of the board. The Google program had effectively won the game using a move that no human would've come up with. AlphaGo's victory is particularly impressive because the ancient game of Go is often looked at as a test of intuitive intelligence. The rules are quite simple. Two players take turns putting black or white stones at the intersection of horizontal and vertical lines on a board, trying to surround their opponent's pieces and remove them from play.


Creating machine learning models to analyze startup news

@machinelearnbot

This is the second part in a series where we analyze thousands of articles from tech news sites in order to get insights and trends about startups. Last time around we scraped all the articles ever published in TechCrunch, VentureBeat and Recode using Scrapy. We then filtered out all the articles that weren't about startups, so we now have only the publications relevant to our analysis. Finally, we'll combine these classifiers to be ready to analyze all of our data. For the first part of this analysis, it'd be great to know for each piece of startup news what "event" it is describing.


Creating machines that understand language is AI's next big challenge

#artificialintelligence

About halfway through a particularly tense game of Go held in Seoul, South Korea, between Lee Sedol, one of the best players of all time, and AlphaGo, an artificial intelligence created by Google, the AI program made a mysterious move that demonstrated an unnerving edge over its human opponent. On move 37, AlphaGo chose to put a black stone in what seemed, at first, like a ridiculous position. It looked certain to give up substantial territory--a rookie mistake in a game that is all about controlling the space on the board. Two television commentators wondered if they had misread the move or if the machine had malfunctioned somehow. In fact, contrary to any conventional wisdom, move 37 would enable AlphaGo to build a formidable foundation in the center of the board. The Google program had effectively won the game using a move that no human would've come up with. AlphaGo's victory is particularly impressive because the ancient game of Go is often looked at as a test of intuitive intelligence. The rules are quite simple. Two players take turns putting black or white stones at the intersection of horizontal and vertical lines on a board, trying to surround their opponent's pieces and remove them from play.


Creating machines that understand language is AI's next big challenge

#artificialintelligence

About halfway through a particularly tense game of Go held in Seoul, South Korea, between Lee Sedol, one of the best players of all time, and AlphaGo, an artificial intelligence created by Google, the AI program made a mysterious move that demonstrated an unnerving edge over its human opponent. On move 37, AlphaGo chose to put a black stone in what seemed, at first, like a ridiculous position. It looked certain to give up substantial territory--a rookie mistake in a game that is all about controlling the space on the board. Two television commentators wondered if they had misread the move or if the machine had malfunctioned somehow. In fact, contrary to any conventional wisdom, move 37 would enable AlphaGo to build a formidable foundation in the center of the board. The Google program had effectively won the game using a move that no human would've come up with. One reason that understanding language is so difficult for computers and AI systems is that words often have meanings based on context and even the appearance of the letters and words. In the images that accompany this story, several artists demonstrate the use of a variety of visual clues to convey meanings far beyond the actual letters.