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How AI is transforming the future of fintech

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WIRED Money takes place in Studio Spaces, London on May 18, 2017. For more details and to purchase your ticket visit wiredevent.co.uk "Breaking: Two Explosions in the White House and Barack Obama is injured." At the time of the tweet, AP's account had around two million followers. The post was favourited, retweeted, and spread. At 13:13, AP confirmed the tweet was fake.


5G to AR: Here are 7 technologies to watch in 2018

@machinelearnbot

USA TODAY's Ed Baig looks at the top Tech trends to watch for in 2018. Visitors walk past a 5G logo during the Mobile World Congress in Barcelona, on March 1, 2017. Blistering fast wireless networks, digital assistants that are, well, everywhere, and a coming out bash for augmented reality. These and other technologies mentioned here, some of which are already familiar but really just getting started, are worth keeping an eye on in 2018. You can bet we'll also learn about innovations in the months to come that are for now, completely under the radar.


Linguistic Knowledge and Empirical Methods in Speech Recognition

AI Magazine

Automatic speech recognition is one of the fastest growing and commercially most promising applications of natural language technology. The technology has achieved a point where carefully designed systems for suitably constrained applications are a reality. Commercial systems are available today for such tasks as large-vocabulary dictation and voice control of medical equipment. This article reviews how state-of-the-art speech-recognition systems combine statistical modeling, linguistic knowledge, and machine learning to achieve their performance and points out some of the research issues in the field. Speech is the most natural communicative medium for humans in many situations, including applications such as giving dictation; querying database or information-retrieval systems; or generally giving commands to a computer or other device, especially in environments where keyboard input is awkward or impossible (for example, because one's hands are required for other tasks).


Computational Sustainability and Artificial Intelligence in the Developing World

AI Magazine

Despite some difficult problems in such places, a period of enormous technologydriven change has created new opportunities to address poor management of resources and improve human wellbeing. As just one example of the possibilities, however, take road traffic in cities. The chaotic and spectacular road congestion that is characteristic of developing-world cities is a microcosm of opportunities for applying AI methods. The problems are mainly caused by inadequate infrastructure (for example, road layouts that have not changed significantly despite decades of economic growth, unsealed or pothole-strewn roads), and a lack of resources to monitor or control traffic (for example, scarce and possibly corrupt traffic police, rolling blackouts affecting traffic lights). Any such solution must take into account the unique nature of traffic in these places, where the assumptions made in developed-world intelligent transport systems -- for example, that drivers travel in the correct direction, and only on the road -- might not be valid.


2017 laid the foundation for faster, smarter AI in 2018

#artificialintelligence

This might be a helpful time to clarify that AI is often a catch-all term for an assortment of different technologies. There's artificial intelligence in our digital assistants like Siri, Alexa, Cortana and the Google Assistant. You'll find artificial intelligence in software like Facebook's Messenger chatbots and Gmail's auto-replies. It's defined as "intelligence displayed by machines" but also refers to situations when computers do things without human instructions. Then there's machine-learning, which is when computers teach themselves how to perform tasks that humans do.


2017 laid the foundation for faster, smarter AI in 2018

#artificialintelligence

This might be a helpful time to clarify that AI is often a catch-all term for an assortment of different technologies. There's artificial intelligence in our digital assistants like Siri, Alexa, Cortana and the Google Assistant. You'll find artificial intelligence in software like Facebook's Messenger chatbots and Gmail's auto-replies. It's defined as "intelligence displayed by machines" but also refers to situations when computers do things without human instructions. Then there's machine-learning, which is when computers teach themselves how to perform tasks that humans do.


What do made-for-AI processors really do?

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Last week, Qualcomm announced the Snapdragon 845, which sends AI tasks to the most suitable cores. There's not a lot of difference between the three company's approaches -- it ultimately boils down to the level of access each company offers to developers, and how much power each setup consumes. Before we get into that though, let's figure out if an AI chip is really all that much different from existing CPUs. A term you'll hear a lot in the industry with reference to AI lately is "heterogeneous computing." It refers to systems that use multiple types of processors, each with specialized functions, to gain performance or save energy.


stop-the-chitchat-bots-dont-need-to-sound-like-us

WIRED

Bert Brautigam is sick of having conversations with his devices. Like many of us, Brautigam, who works for the design firm Ziba, uses voice assistants like Google's phone AI or Amazon's Alexa. The theory is that voice commands make life more convenient. But these assistants are scripted to emulate every day conversation. And everyday conversation is filled with little pauses and filler words, the "phatic" spackle of social interactions.


Artificial Intelligence Is Putting Ultrasound on Your Phone

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If Jonathan Rothberg has a superpower, it's cramming million-dollar, mainframe-sized machines onto single semiconductor circuit boards. The entrepreneurial engineer got famous (and rich) inventing the world's first DNA sequencer on a chip. And he's spent the last eight years sinking that expertise (and sizeable startup capital) into a new venture: making your smartphone screen a window into the human body. Last month, Rothberg's startup Butterfly Network unveiled the iQ, a cheap, handheld ultrasound tool that plugs right into an iPhone's lightning jack. You don't have to be a technician to use one--its machine learning algorithms guide the user to find what they might be looking for.


Artificial Intelligence Is Putting Ultrasound on Your Phone

#artificialintelligence

If Jonathan Rothberg has a superpower, it's cramming million-dollar, mainframe-sized machines onto single semiconductor circuit boards. The entrepreneurial engineer got famous (and rich) inventing the world's first DNA sequencer on a chip. And he's spent the last eight years sinking that expertise (and sizeable startup capital) into a new venture: making your smartphone screen a window into the human body. Last month, Rothberg's startup Butterfly Network unveiled the iQ, a cheap, handheld ultrasound tool that plugs right into an iPhone's lightning jack. You don't have to be a technician to use one--its machine learning algorithms guide the user to find what they might be looking for.