Monthly Archives: April 2017

Forbes

Canada Is Prioritizing Artificial Intelligence Research For Good Reason Forbes You see, strong public support for research programs and world class expertise at Canadian universities has helped propel Canada to a position as leader in artificial intelligence and deep learning research and use. Canadian talent and ideas are in ...

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Canada Is Prioritizing Artificial Intelligence Research For Good Reason - Forbes

Forbes

Don't Fall For These Artificial Intelligence Mistakes Executives Commonly Make Forbes From banks to breweries and from customer service to marketing, the business case for Artificial Intelligence (A.I.) is now a foregone conclusion. The issue is not whether you need A.I., but how exactly you need to implement new technologies to yield ...

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Don't Fall For These Artificial Intelligence Mistakes Executives Commonly Make - Forbes

Artificial intelligence is not one technology but rather a group of related technologies including natural language processing, machine learning (computer programs that can learn when exposed to new data) and expert systems (software programmed to provide advice) that help machines sense, comprehend, and act in ways similar to the human brain. These technologies are behind innovations such as virtual agents (computer-generated, animated characters serving as online customer service representatives), identity analytics (solutions combining big data and advanced analytics to help manage user access and certification), and recommendation systems (algorithms helping match users and providers of goods and services) which have already transformed the ways in which companies look at the overall customer experience.

Artificial intelligence can help banks finance teams reimagine and restructure operating models and processes. Large banks must process huge volumes of data to generate financial reports and satisfy regulatory and compliance requirements. These processes are increasingly standardized and formulaic but still involve large numbers of people performing low-value-added tasks (often in reconciliation and consolidation). This makes them ideal candidates for robotic process automation (RPA). The software bots used in RPA can be coded to deal with rules and some exceptions, but its the added layer of machine learning across the more complex challenges and frequently changing tasks that make the combination of RPA and AI particularly powerful.

Over the next few years, AI will be used to transform the most central functions in finance such as intercompany reconciliations and the quarterly close and reporting of earnings, in addition to engaging in more strategic functions such as financial analysis, asset allocation, and forecasting. AI provides speed and accuracy the entire reporting and disclosure process, for example, can be undertaken in real (or nearly real) time. Rather than waiting until the end of the quarter, the finance team empowered by AI can identify issues and make adjustments much sooner than is possible today, increasing accuracy and eliminating period end efforts.

Financial institutions are well aware of the potential of AI. They have observed massive disruption in other industries, as digital startups and internet giants use AI to streamline operations and entice customers with more personal, relevant offerings and experiences developed upon new, technologically-enabled platforms. As a result, banks are investing heavily into new technologies and into recruiting and developing the talent needed to implement and work effectively with AI solutions.

Artificial intelligence provides banks, capital markets firms and insurers with an enormously powerful set of tools to transform and streamline some of their most fundamental financial processes. The challenge for many, however, is not only to identify and adopt the best AI technologies, but to also reshape and rethink their operating model and talent development to take advantage of AIs transformative capabilities.

Artificial intelligence can help banks dramatically improve operational efficiency and gain a much clearer understanding of where they are going, but it is still up to humans to make the big strategic decisions and set the course for AI and related technologies to help deliver profitable growth.

AI and machine learning can also help automate other investment categories, a growing trend in the past year. A recent published report by PwC noted that some financial institutions have been investing in AI for years, while other firms are now beginning to catch up thanks to advances in big data, open-source software, cloud computing, and faster processing speeds. Arthena is utilizing not only similar technological advancement but also acceptance of AI in investing to create the first automated art market investment platform, capable of returning over 15% y0y by generating calculated investment opportunities.

Visit Arthena.com to learn more.

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How Artificial Intelligence Will Change Everything - Huffington Post

Mashable

Artificial intelligence is now trying to make sense out of the mess that ... Mashable Governing is hard. Predicting what the, ahem, disjointed members of Congress are going to do on any given day is even harder. So why not give your noggin a ... and more »

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Artificial intelligence is now trying to make sense out of the mess that ... - Mashable

Most consumers don't really know what artificial intelligence (AI) does, and the basic misunderstanding has some fearful of the technology.

In a survey of 6,000 customers in six countries,the findings from Pegasystems study released this week found that consumers are hesitant to embrace AI devices and services. Some 36% are comfortable to engage with businesses using AI even if it results in a better customer experience. About 72% said they have some sort of fear about AI, with 24% worried about robots taking over the world.

Only 34% of survey respondents thought they had directly experienced AI, but when asked about the technologies in their lives, the survey found that 84% use at least one AI-powered service or device such as virtual home assistants, intelligent chatbots, or predictive product suggestions. When asked to identify AI-powered devices, only 41% knew that AI supports both Amazon Alexa and Google Home.

When asked to name the technology they have used in the past year that includes AI, 51% said email spam filters; 46%, predictive search; 36%, Siri virtual assistant; 31%, online virtual assistant; 28% Facebook recommended news; 28%, online shopping recommendations; 11% home virtual assistants; 9%, reverse image searching; and 16%, none of the above.

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About 72% believed they understood AI, but far fewer could correctly define what it is or what it can do. Only 37% knew that AI can interpret or understand speech, while 35% knew it could mimic humans; 50% knew it can solve problems; and 57% knew that it can learn.

Despite the misunderstanding, the data shows that consumers are significantly more comfortable with AI if they think. In general non AI-users -- at 25% -- said they feel at ease with businesses using AI to interact with them. This sentiment jumps to 55% for those who understand a bit more about the technology. Some 36% of non-AI users are uncomfortable, while 19% of AI users are comfortable, with AI.

Despite the misunderstandings, nearly 70% said they would like to experience more AI if it makes their lives easier.

The study also found that consumers still want human interaction when they need customer service. Only 10% said they are comfortable using AI for the government to provide better and more personalized customer service. That jumps to 15% for car dealerships and insurance, and 20% for banking and financial advice. Telecom at 15, healthcare at 27%, and online retail at 34% were the highest.

The report What Consumers Really Think About AI surveyed consumers across the US, Britain, France, Germany, the Netherlands, and Australia.

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Consumers Confused About Artificial Intelligence - MediaPost Communications

A near-miss during the Par-3 contest had Shane Lowry, Padraig Harrington and the crowd on the edge of some Augusta National magic.

Getty Images // Jamie Squire

Recall Sunday, April 10, 2016. Jordan Spieth had just teed off in the final group of a sure-to-be exciting day at Augusta National. Minutes later, across the course, Shane Lowry kickstarted the party.

The Irishman drew his ball to the center of the 16th green, where it curled left and toward the hole. It fell in the cup for an ace and created the first roar in what seemed like days. Lowry punched both fists high in the air, spanked Patrick Reed's open hand and gave his best Kirk Gibson impression, much to the delight of fans in the stands, Verne Lundquist in the CBS booth and, behind some glass doors hundreds of yards away, International Business Machines (better known as IBM).

One of the largest computer companies on Earth is a global sponsor of the Masters as well as its digital overseer. Since 1996, it has helped run the official Masters website. In 2007, that website began live streaming the competition. Two years later, IBM helped develop and launch the Masters iPhone app. Now, in 2017, IBM's Watson (the well-known artificial intelligence computer) is here to enhance the many platforms of consumer-facing content.

Watch @shanelowrygolf make the sixteenth hole-in-one at No. 16 in #themasters history. https://t.co/YClo2d7xmW Masters Tournament (@TheMasters) April 10, 2016

That's where Lowry's ace comes in. Watson's audio and visual recognition capabilities have helped study (and learn from) every shot during the 2016 event, and pinpoint specific things. Things like player reactions, where Watson knows the difference between a fist pump and a simple tip of the cap, crowd cheering where there's a clear difference between the common golf clap and the patented Augusta roar, and even commentary from broadcasters. Yes, if Peter Kostis declared an approach "phenomenal," Watson would know that it wasn't just good, it was indeed phenomenal.

In turn, each of these things Watson recognized is given a value and mashed together via a special algorithm to determine that shot's 'Overall Excitement Level.' (In case you're wondering Lowry's ace earned a score of .87). The obvious question here is why? What's the value in assigning an excitement level to a golf shot, to every golf shot? Well, it helps Masters.com and the Augusta National editorial team push the event's greatest action to the fingertips of its biggest digital fans as quick as possible. It's humans and a computer, working together.

This interface displays Watson's assessment of specific shots in specific locations of Augusta National and their Overall Excitement Level.

Courtesy of IBM

"When you think about the golf that's going on with the number of golfers and number of cameras out there, it affords the Augusta National editorial team the ability to scale up," John Kent, the head of IBM's tech approach at the Masters, said. "I could do a highlight real for Shane Lowry, every shot of his, very easily. I could put a package together of your favorite players. I could create an experience for an individual coming to the site that is much more personal. I could have a recap video when you come on that is just Hey, here's what happened the last 15 minutes.' The possibilities are endless."

If it sounds over the top, maybe it is, but when has Augusta National ever approached anything uninspired? The idea is to bring the special action of Augusta National to those not lucky enough to be there.

Lets say Hideki Matsuyama's biggest fan in Tokyo wants to see the best shots from his first round, or Ernie Els's biggest fan in Johannesburg was stuck in a conference call as Big Easy played the back nine. Maybe the second-grade teacher of amateur Brad Dalke couldn't fork over the money to watch him compete in his first Masters. Scenarios like this are what the augmented intelligence of Watson and Masters.com are hoping to reach in the not-too-distant future.

Mark it down, for now, as the most recent step of a slow-to-act club working to show off its crown jewel like never before.

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Masters highlights getting artificial intelligence treatment via IBM's Watson computer - Golf.com

Storm season charged through North Texas resulting in home, vehicle, and public property damage. Within the past few weeks thousands of claims have been processed through Insurance companies.

From the last two hail storms we are just over 12,000 claims, said Carrie Bonney from Farmers Insurance. "When a large storm hits we begin mapping out where the claims are, then we send in our catastrophe team, she said.

Farmers insurance adjusters are now armed with a new tool to assess claims. A pilot program using drones and artificial intelligence was launched this storm season.

It is a really good way for us to quickly and easily get high definition photos of the roof so they can see the damage, said Bonney.

According to insurance companies, safety and efficiency are two of the main benefits to using aviation technology.

Some of the roofs are really steep. The adjuster would have to wear a rope and harness. It could take him up to three hours to inspect the roof. If we use a drone, it can be done in 20 minutes, she said.

The images are collected in three phases.

First, the drone takes pictures of the corner of the roof and a 3D rendering. The second, the camera takes a general overview of the roof. During the final phase, it drops down 15 to 20 feet near the roof to get a detail scan of the damage, said Bill Breedlove who both works for Farmers Insurance and operates the drone.

All three phases of imagery are put together to create a 3D-map of the home.

Its certainly much safer to capture these pictures with an aerial drone than climbing on a roof, said Breedlove.

The data used from this pilot program will help companies streamline additional drone use in the future.

Published at 5:20 AM CDT on Apr 5, 2017 | Updated 3 hours ago

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Drones, Artificial Intelligence Used to Survey Storm Damage - NBC 5 Dallas-Fort Worth

Global chip maker Intel on Tuesday announced a string of initiatives to boost the usage of Artificial Intelligence (AI) in diverse sectors by collaborating with partners and customers across the country.

"Our developer education programme will educate 15,000 scientists, developers, analysts and engineers on AI technologies, including Deep Learning and Machine Learning in India," said Intel South Asia Managing Director Praksh Mallya here.

AI is a software programme that makes computers and machines think intelligently and faster with more predictability than a human mind. AI is also the main workload in data centres which operate in line with the Moore's Law of computing power doubling every year.

By 2020, the industry expects more servers to process data analytics than other workloads and analytics predictors will be built into every application.

Intel powers 97 per cent of data centre servers running AI workloads and offers flexible performance-optimised portfolio of solutions.

Through 60 programmes in a year, the initiatives will empower the community with the know-how for AI adoption with ready-to-deploy platforms and tools for solution development.

"As India undergoes digital transformation, the data centre and the intelligence behind the data collected will enable the government and industry to make quick decisions based on algorithms," said Mallya on the margins of Intel's 'AI Day 2017'.

The company's Indian subsidiary is collaborating with Hewlett Packard Enterprise, Wipro, Julia Computing and Calligo Technologies for using AI in the country.

"Our collaboration with the industry and the academia will help democratise AI, by reducing entry barriers for developers, data scientists and students," noted Mallya.

The subsidiary is targeting the BFSI (Banks, Financial Services and Insurance), telecom, and e-commerce sectors, across High Performance Computing (HPC), big data and Internet of Things, which are complementary to AI," added Mallya.

The onset of AI-based technology in India is evident in e-commerce and research, where entities using data analytics are looking to explore AI.

"Our research groups are working on implementation of evolutionary algorithms in parallel environments and using Intel platforms and software tools to deploy, parallelise and optimise systems," said IIT-Patna Director Pushpak Bhattacharya.

With its unified approach, Intel leads the AI computing era through hardware and software designed for building AI applications across industries.

Intel's collaboration with companies like Google and is acquisitions, including Saffron, Movidius, Nervana Systems and Mobileye, further its AI capabilities, giving it an edge at a time when embedded computer vision is becoming increasingly important the world over.

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Intel bets on India to boost artificial intelligence usage - PCMag India

Image: Microsoft

Microsoft has launched a new camera app called Sprinkles that uses the company's machine learning and artificial intelligence (AI) tools to analyze photos, and can detect faces, the age of photo subjects, and their celebrity look-a-like. The app can even offer captions based on what is happening in the photo, according to its iTunes App Store description.

Similar to Snapchat, Sprinkles' face detection technology can also place images such as hats and moustaches on subjects in a photo. It also offers different time- and location-based stickers and captions.

With Sprinkles, Microsoft seems to be targeting the teen audiences that typically flock to photo apps like Snapchat. As the description reads:

"Sprinkles is a camera with fun ideas. Snap a pic and automatically get new ideas for witty captions or add your own quip. Captions are unique to what's in the picture, so try different things such as coffee, food, pets, and selfies! Have fun with face-detecting Smart Stickers that fit your face perfectly. Choose from hundreds of Emojis and stickers and find even more with a quick web search. New captions and Smart Stickers are added frequently, because fresh fun is the best fun."

SEE: Machine learning as a service to hit nearly $20B by 2025, driven by healthcare and life sciences

The app allows users to swipe through the different photo options, including the caption ideas, accessories, and age suggestions. They can also decorate their own photos with emoji, stickers from the web, or text. The images can then be shared via messaging, Facebook, Twitter, or other platforms.

While the app is not targeted toward enterprise users, its technology could be useful for marketing professionals and social experts who could rely on the algorithms to help them make their social posts or picture-based ads more impactful. The photo recognition technology could also potentially be used in the future to help professionals analyze work-related photos, such as those from job sites or hazardous areas.

The release of Sprinkles and the technology it includes also points to a larger issue: With hardware commoditized, AI will likely be the next big battleground in mobile. Leveraging machine learning technology in sophisticated apps could be Microsoft's way of gaining ground in the mobile market.

The Sprinkles app is available for free in the iTunes App Store.

1. A new camera app from Microsoft called Sprinkles leverages the company's machine learning and artificial intelligence tools to recognize faces and create photo captions based on what is happening in a picture.

2. Though the company seems to be targeting a teen audience, the app could potentially be useful for marketing and social media professionals.

3. The app also demonstrates how the rise of AI will likely be the next big issue in mobile, and could help Microsoft gain a foothold.

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Microsoft's Snapchat-like Sprinkles app showcases the power of AI on mobile - TechRepublic