Monthly Archives: June 2017

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June 27, 2017, 7:01 PM EDT

Stop worrying that robots will steal your job. Artificial intelligence is actually set to boost to the British economy, according to PricewaterhouseCoopers LLP.

The majority of the U.K.s economic gains over the period to 2030 will come from increasing consumer demand thanks to AI driving a greater choice of products, increasing personalization and making them more affordable over time, PwC research published Wednesday shows.

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While we expect that the nature of jobs will change and that some will be susceptible to automation, our research shows that the boost to U.K. GDP that AI-driven products and services will bring will also generate significant offsetting job gains, PwC economist Jonathan Gillham said. Automating the more mundane and repetitive aspects of peoples jobs will also increase the U.K.s productivity and boost real wages.

While Britain could see a 10 percent increase in gross domestic product through 2030, the nations likely to see the biggest upswings are China and North America, which will be boosted 26 percent and 14.5 percent, PwC said. It sees the biggest gains in the retail, financial services, and health care sectors.

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Artificial Intelligence Could Add 10% to UK GDP, PwC Says - Bloomberg

Carnegie Mellon University is revamping the way it teaches artificial intelligence.

The universitys computer science department debuted Tuesday its CMU AI initiative intended to better prepare students for entering the workforce.

The goal is to train students to build complex software systems or powerful robots that utilize multiple different AI technologies, whether it be machine learning tech to help those systems learn from data or technology that helps robots see and perceive the world similar to humans.

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There is a real science to building these things, said CMU dean of computer science Andrew Moore.

While its common for students or faculty members to concentrate on one specific subset of AI, like machine learning, those subsets represent only one portion of a finalized product, like a robot or digital assistant like Apples ( aapl ) Siri.

However, there hasnt been a standardized way to develop these complex projects that require multiple AI technologies to function together. Similar to how building a skyscraper requires people with expertise in diverse fields like structural engineering and concrete mixing, building powerful software like Siri or robots requires people with expertise in many different areas of AI.

We have done a good job of covering all the component parts, Moore said of teaching different subsets of AI like machine learning and computer vision. We need to be thinking very seriously about the science of putting it all together.

Students who know how to piece together all the various AI components into functioning software will have better chances at landing high-caliber jobs. Moore said that when he worked at Google ( goog ) where he was once a vice president of engineering and a director in Google's Pittsburgh officehe learned how rare and how desperate it was to find people who have these skill sets.

Moore says he hopes the new AI initiative will better train students to fill the labor pipeline.

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Carnegie Mellon's AI Program Aims to Better Prepare Students for the Changing Workforce - Fortune

Before the internet arrived, I used to be an equity analyst. I'd spend my days finding and arranging metaphorical jigsaw pieces to come up with a complete picture and an investment recommendation, which the sales guys would disseminate by telephoning their favorite clients first, and the ones they didn't like so much a bit later.

Today, at asset management companies and other financial institutions, there are still large teams of analysts and portfolio managers, sifting through data, developing investment theses and making asset allocation decisions. The difference is that we are deluged in data. Not only is the amount of data available to us accelerating, the nature of it is changing, with new sources of information being seen as potentially relevant for analysis. For example, the location-based data that comes from your mobile phone shows whether you are in a mall. Scaled over the whole of the country, this could allow us to see what is happening to footfall, which would help with understanding retail sales in real time. The footage from closed-circuit television that shows what's happening in transportation is another example. Or social media analysis of events happening in real time from people on the ground. Or weather data. The list goes on.

The reality is that there is just too much data for humans to be able to use. Opportunities go wasted because a team of humans just cannot create a sophisticated response to all of this. Of course, funds have been using complex algorithmic-driven trading strategies for years, but this is largely confined to market data. Imagine if we could take all the data that's coming from the real economy and use that to discern price, predict performance, understand risk and make better investment decisions. The only feasible way to do this is to use computing power to ingest the data, understand correlation and causation, and deduce rapidly enough how to respond. Artificial intelligence has now advanced to the stage where this is possible. While this gives rise to some interesting opportunities to radically transform investment management and capital markets, it will be very disruptive for people who work in the industry.

Let's assume that you use very sophisticated AI-driven models to scan data from not just the market but a whole plethora of other sources to define, implement, monitor, refine and adjust your trading strategies. What kind of people do you now need to employ? Performance will come down to how well your combination of engineers, scientists and market people can define and improve those models. The kinds of people employed in the industry will change; we will need people who can model data, and others who can validate the models and the results. And we will not need so many people. Much of the dialogue around the types of jobs that will disappear because of artificial intelligence has centered on relatively unskilled jobs, but in financial services it will be expensive, highly educated Wall Street-types finding themselves out of work. An asset manager friend of mine agreed. He also said there's no way he'd go public about using this strategy; he'd prefer investors think how great his team was at stockpicking!

Change is already underway. One of the most high-profile companies in this space is Kensho, which is backed by Google, Goldman Sachs and S&P Global. Kensho uses AI to scan vast data sets much more quickly and accurately than analysts, and sells the information to banks and other financial institutions.

One competitor is Sentifi, which takes in data from thousands of sources, then filters it for accuracy. The founder got the idea after the nuclear disaster at Fukushima, when an investment manager friend griped that it would take three weeks of sifting through seemingly unconnected data to work out the implications of this event on his portfolio.

One hedge fund taking artificial intelligence to the next level is Numerai - which doesn't even employ the AI talent! This San Francisco fund encrypts its trading data and then crowdsources AI-based algorithms from anyone who wants to have a go. Contributors who develop algorithms that successfully improve performance get paid in bitcoin.

It's a long way from when I used to analyze company reports, scan articles in actual newspapers and use old-fashioned methods like the telephone and company visits to develop my investment ideas.

Hazel Moore is the chairman and co-founder of the London investment bank FirstCapital.

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BankThink Is artificial intelligence the future of capital markets? - American Banker (subscription)

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Carnegie Mellon University announced Tuesday an initiative to bring together its research and education related to artificial intelligence.

CMU AI will coordinate faculty, students and staff working on AI in robotics, engineering, language, human-computer interaction, machine learning and more.

Having grown large, we've also grown a little further apart, and in the context of AI, we are bringing it back to together, said Jaime Carbonell, director of CMU's Language Technologies Institute. And we expect to grow more

CMU AI will create one of the largest and most experienced artificial intelligence research groups in the world, the university said. Carbonell said researchers classified their work based on the sub-field of artificial intelligence in which they worked, such as robotics, machine translation or machine learning, not under the umbrella of AI. Now those disciplines will be under CMU AI, underscoring the university's commitment to the research and potentially upping the university's public profile and funding.

It certainly helps the messaging, Carbonell said. But more than messaging, it helps the substance.

Carbonell said projects like analyzing social networks for nefarious activity and designing robots to care for the elderly will benefit from harnessing the university's entire AI hive mind.

Artificial Intelligence was essentially created at CMU. In 1956, professors Allen Newell and Herbert A. Simon helped write Logic Theorist, considered the first artificial intelligence computer program.

Since, the university's advancements in artificial intelligence have worked their way into everything from self-driving cars to poker bots that can defeat the best players in the world. CMU AI projects help computers recognize faces and images and power robot soccer players and IBM's Jeopardy-playing Watson. They've improved instant replay in sports and algorithms that match kidney donors with recipients. Two teams of CMU students are working with Amazon to improve Alexa , its home assistant. Another team is using machine learning to develop a reading and math tutor for kids in countries facing teacher shortages. The RoboTutor project is a semifinalist in the $15 million Global Learning XPRIZE.

AI technologies developed at CMU have been acquired by Facebook, Amazon, Google and more.

AI is not something that a lone genius invents in the garage, Andrew Moore, the dean of CMU's School of Computer Science, said in a statement. It requires a team of people, each of whom brings a special expertise or perspective. CMU researchers have always excelled at collaboration across disciplines, but CMU AI will require all of us to work together in unprecedented ways.

RELATED: K&L Gates gives $10M to CMU to study ethics of AI

The initiative will bring together more than 100 professors and researchers working on artificial intelligence in CMU's School of Computer Science's seven departments. Moore will direct the initiative. Carbonell will lead the initiative along with Martial Hebert, the head of the Robotics Institute; Tuomas Sandholm, the computer science professor behind Libratus, the poker bot, and Manuela Veloso, the head of the Machine Learning Department.

The initiative will focus on two things. It will work to educate a new breed of AI scientists. About 1,000 students, more than half of the School of Computer Science, are working on AI-related projects. Moore said these are the people who will improve life through technology and shape the rest of the century.

Exposing these hugely talented human beings to the best AI resources and researchers is imperative for creating the technologies that will make our lives healthier and safer in the future, Moore said.

The initiative will also focus on creating new capabilities for AI. It will bring together work in machine learning, the study of how software can make decisions and learn through experience; machine translation, using computers to understand and translate languages; human-computer interaction, how people and machines can work together, and robotics, which is renowned for its computer vision group studying how computers understand images.

Students who study AI at CMU have an opportunity to work on projects that unite multiple disciplines, Veloso said. CMU students at all levels have a big impact on what AI can do for society.

Aaron Aupperlee is a Tribune-Review staff writer. Reach him at aaupperlee@tribweb.com, 412-336-8448 or via Twitter @tinynotebook.

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CMU to harness power of collaboration to advance artificial ... - Tribune-Review

Acquistions of AI startups are rapidly increasing while the health AI market is set to register an explosive CAGR of 40 percent through 2021.

Artificial Intelligence can help drive the Triple Aim in healthcare, reducing cost, improving qualityand expanding access, according toArtificial Intelligence: Healthcares New Nervous System from Accenture.

Acquisitions of AI developers in health will be fast-paced, growing at a compound annual growth rate of 40 percent explosive in the word of Accenture moving from $600 million in 2014 to $6.6 billion in 2021.

What these AI startups will do is to enable machines to sense, comprehend, act and learn, Accenture foresees, to augment administrative and clinical tasks which could free up healthcare labor (doctors, other clinicians, and accountants) to work at their highest-and-best-use.

The most impactful AI-driven application would be robot-assisted surgery, generating $40 billion of value, annually, by 2026. Next in AI-health value-creation include virtual nursing assistants (valued at $20 billion annually), administrative workflow support ($18 billion), fraud detection ($17 billion), and medication error reduction ($16 billion).

Artificial Intelligence, AI, can help drive the Triple Aim in healthcare, reducing cost, improving quality, and expanding access, according toArtificial Intelligence: Healthcares New Nervous System from Accenture.

Acquisitions of AI developers in health will be fast-paced, growing at a compound annual growth rate of 40 percent explosive in the word of Accenture moving from $600 million in 2014 to $6.6 billion in 2021.

What these AI startups will do is enable machines to sense, comprehend, act and learn, Accenture foresees, to augment administrative and clinical tasks, which could free up healthcare labor (, doctors, other clinicians, and accountants) to work at their highest-and-best-use.

The most impactful AI-driven application would be robot-assisted surgery, generating $40 billion of value, annually, by 2026. Next in AI-health value-creation include virtual nursing assistants (valued at $20 billion annually), administrative workflow support ($18 billion), fraud detection ($17 billion), and medication error reduction ($16 billion).

Acquistions of AI startups are rapidly increasing while the health AI market is set to registr an explosive CAGR of 40 percent through 2021.

Artificial Intelligence can help drive the Triple Aim in healthcare, reducing cost, improving quality, and expanding access, according toArtificial Intelligence: Healthcares New Nervous System from Accenture.

Acquisitions of AI developers in health will be fast-paced, growing at a compound annual growth rate of 40 percent explosive in the word of Accenture moving from $600 million in 2014 to $6.6 billion in 2021.

What these AI startups will do is to enable machines to sense, comprehend, act and learn, Accenture foresees, to augment administrative and clinical tasks which could free up healthcare labor (doctors, other clinicians, and accountants) to work at their highest-and-best-use.

The most impactful AI-driven application would be robot-assisted surgery, generating $40 billion of value, annually, by 2026. Next in AI-health value-creation include virtual nursing assistants (valued at $20 billion annually), administrative workflow support ($18 billion), fraud detection ($17 billion), and medication error reduction ($16 billion).

Artificial Intelligence, AI, can help drive the Triple Aim in healthcare, reducing cost, improving quality, and expanding access, according toArtificial Intelligence: Healthcares New Nervous System from Accenture.

Acquisitions of AI developers in health will be fast-paced, growing at a compound annual growth rate of 40 percent explosive in the word of Accenture moving from $600 million in 2014 to $6.6 billion in 2021.

What these AI startups will do is enable machines to sense, comprehend, act and learn, Accenture foresees, to augment administrative and clinical tasks, which could free up healthcare labor (, doctors, other clinicians, and accountants) to work at their highest-and-best-use.

The most impactful AI-driven application would be robot-assisted surgery, generating $40 billion of value, annually, by 2026. Next in AI-health value-creation include virtual nursing assistants (valued at $20 billion annually), administrative workflow support ($18 billion), fraud detection ($17 billion), and medication error reduction ($16 billion).

This blog was first published on Health Populi.

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Artificial Intelligence is becoming the new operating system in health - Healthcare IT News (blog)