Deep Learning – Mandate for Humans, Not Just Machines

Deep Learning terminology can be quite overwhelming to newcomers.. This blog post covers important aspect of deep learning which can be defined as set of techniques that uses neural networks to simulate human decision-making skills. #AILabPage

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Deep Learning terminology can be quite overwhelming to newcomers.. This blog post covers important aspect of deep learning which can be defined as set of techniques that uses neural networks to simulate human decision-making skills. #AILabPage

The post Deep Learning – Mandate for Humans, Not Just Machines appeared first on Vinod Sharma's Blog.

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Human Challenges Face Today’s AI Business Strategies

The hype surrounding artificial intelligence (AI) is intense despite that fact that as yet, artificial intelligence (AI) for most enterprises is still at an early, or planning, stage. While a lot has been done, there is a lot more to do before it becomes commonplace. However, that hasn’t stopped speculation about the impact on employment […]

The hype surrounding artificial intelligence (AI) is intense despite that fact that as yet, artificial intelligence (AI) for most enterprises is still at an early, or planning, stage. While a lot has been done, there is a lot more to do before it becomes commonplace. However, that hasn’t stopped speculation about the impact on employment and what it might mean for workers, especially those whose jobs are repetitive and considered low skilled.

In October last year,  a survey carried out by analytics giant Cary, N.C-based analytics giant SAS showed that the vast majority of organizations have begun to talk about artificial intelligence, and a few have even begun to implement suitable projects. There is much optimism about the potential of AI, although fewer were confident that their organization was ready to exploit that potential.

AI Human Challenges 

The reason for this is not because there is a lack of technologies on the market. What the research uncovered was that the challenges come from a shortage of data science skills to maximize value from emerging AI technology, and deeper organizational and societal obstacles to AI adoption. Some of the figures contained in the report show that:

  • 55 percent of survey respondents felt that the biggest challenge related to AI was the changing scope of human jobs in light of AI’s automation and autonomy.
  • 41 percent of respondents raised questions about whether robots and AI systems should have to work “for the good of humanity” rather than simply for a single company, and how to look after those who lost jobs to AI systems.

It also showed that several organizations had a senior-level sponsor for AI and advanced analytics. In some cases, this was a member of the C-suite, and in a few, the CEO. In others, it was a more junior director, usually one with an interest in the area. One respondent mentioned that the organization planned to appoint a Chief Data Officer within the next six months, who would take on responsibility for this area.

And it’s not the only research that has raised the issue of the impact AI will have on jobs. Recently, we were able to identify seven jobs that might be overtaken by the growth in the use of AI in the enterprise. That said there are ways that enterprises – and individuals – can meet the challenge.

Building a Talent Pipeline

AI is generating a demand for new skill sets in the workplace. However, there is a widespread shortage of talent that possess the knowledge and capabilities to properly build, fuel, and maintain these technologies within their organizations, according to Mohit Joshi president and head of banking, financial services and insurance, as well as, healthcare and life sciences at Bengalaru, India-based Infosys. The simple answer is up-skilling. “The lack of well-trained professionals who can build and direct a company’s AI and digital transformation journeys noticeably hinders progress and continues to be a major hurdle for businesses. But there is also opportunity here too and a way to redeploy workers who face redundancy because of AI,” he says.

To mitigate this, businesses should look inward and create on-the-job training and  to build these skills internally. With the proper staff powering AI, employees are able to focus on other critical activities and boost productivity creating a larger ROI. If an enterprise’s digital transformation goal is for AI to become a business accelerator, it needs to be an amplifier of its people. “It’s going to take work to give everyone access to the fundamental knowledge and skills in problem-finding and remove the elitism around advanced technology, but the boost to productivity and ROI will be worth it in the end,” says Joshi. Businesses that haven’t yet allocated budget for AI should start small by manually auditing the organization to streamline processes and free up employees’ bandwidth. This allows decision makers to clearly see which systems aren’t utilized effectively and which areas could benefit from technology down the road.

Shifting Roles

Anthony Macciola, Chief Innovation Officer and is responsible for AI initiatives at Moscow, Russia-based global giant ABBYY, a company that uses machine learning, robotic process automation and text analytics to improve business outcomes. He says that the introduction of AI into the general workplace will result in more tasks being addressed by system of record applications and shift knowledge workers’ roles from a control to an expertise standpoint.

He cites an example of how this will work in the mortgage lending market. The dependency on a loan origination officer to drive the loan process will diminish over time due to the loan origination system being able to make intelligent decisions based on past funding behavior. This will leave only rules-based exceptions to require a loan processor’s attention. As a result, this will lighten the overall workload for loan officers, allowing them to be more responsive when an exception rises and should allow mortgage lenders to increase the productivity of their operations.

“As software gets smarter, dependency on the workforce shrinks and knowledge workers who have typically conducted manual input tasks or controlled processes in fintech, healthcare, transportation and logistics, and government customer/constituent engagement scenarios will become more narrowly focused from a role and responsibility standpoint,” he says.

Read the source article at CMSWire.com.

These 4 Apps Powered by AI Will Strengthen Your Business

Leaders know they need technology to advance their businesses and boost their teams — but many of them are scared to use it. They’re not alone; Americans as a whole fear technology more than death. Christopher Bader, a sociology professor at Chapman University and one of the authors of the study that found Americans find robots more terrifying […]

Leaders know they need technology to advance their businesses and boost their teams — but many of them are scared to use it. They’re not alone; Americans as a whole fear technology more than death.

Christopher Bader, a sociology professor at Chapman University and one of the authors of the study that found Americans find robots more terrifying than dying, said, “People tend to express the highest level of fear for things they’re dependent on but that they don’t have any control over, and that’s almost a perfect definition of technology.”

The great thing is that leaders don’t necessarily need to know how the technology works to benefit from it. Take these four platforms, which are powered by artificial intelligence but do the work for businesses:

1. Spiro.ai

Spiro.ai is an AI-powered CRM that empowers salespeople to nurture leads and close sales without the distraction of data entry. Spiro uses AI to proactively build a to-do list for sales reps and is the only CRM with a built-in email assistant. The email assistant provides sales reps and managers all the information they need, without requiring them to log in to their CRM.

The biggest selling point for the tech-averse may be that the CRM relies on an algorithm built by salespeople for salespeople, with the aim of creating a CRM people will actually use.

Because the CRM cuts down on the need to organize between calls, it fuels sales productivity and pushes salespeople to follow up in the quick timeline needed to close sales. And it offers another tech advantage in the form of reporting: Because Spiro self-populates with data, the reports it sends to managers are eight times richer with data than many competing platforms’ reports.

2. Pi

Pi is an AI-powered social marketing tool to help companies boost their social strategies by analyzing followers’ interactions. After connecting with a company’s Twitter or Facebook account, Pi evaluates followers’ profiles, posts, and comments (through natural language processing and sentiment analysis) to develop a list of relevant topics and tones. The app can recommend when to publish an associated post and use performance to continually assess and adjust its suggestions.

For those who don’t have the time to look at others’ accounts, the AI’s biggest benefit is that it can create a pool of links to consider posting, and it can predict how well a drafted post will perform once posted. It also offers a marketplace for sponsored posts.

3. Legal Robot

Legal issues are perhaps as terrifying for some as technology itself; enter Legal Robot, an AI-powered “legal advisor” that helps both lawyers and consumers build contracts. Built to overcome the difficulty of understanding legal language, the app uses deep learning and natural language processing to create models of contracts for various scenarios and uses. It can then translate the terminology into layman’s terms, compare documents to create a language benchmark for consistency, and ensure compliance.

The app aims to help businesses identify risks and pinpoint their specific blind spots in creating contracts, and its ability to learn and transform its understanding boosts its likelihood of doing that.

4. Learn Chinese

Microsoft’s Learn Chinese may specifically aim to teach users how to speak Chinese, but the AI-powered language app is a precursor of things to come. The app utilizes deep neural networks to use speech to help people learn to actually speak Chinese, not simply learn its grammar rules.

Learn Chinese uses speech clues to anticipate what a learner wants to say and then scores the speaker’s attempt compared to native speakers and synthesized examples. This allows users to practice language skills they may need to use on business trips or with visiting companies without face-to-face teacher availability.

The AI shines when users consider that people can learn either language featured– Chinese or English–through the app. Learn Chinese also identifies individual words needing more practice and offers audio samples of how the words should be pronounced for future reference, saving business leaders everywhere from the risk of dying of embarrassment.

Being dependent upon something without being comfortable with it is a scary prospect. Spending more time with AI-powered tools, however, can not only make leaders less scared of technology, but it can also improve their business–and the possibility of a stronger company should outweigh any fear.

Read the source article at Inc.com.

How Cognitive Ergonomics of AI Exciting FinTech

AI is Transforming the Digital Economy through FinTech. How its doing that we will answer below by taking help through “Cognitive Ergonomics”. May assuming AI more human then it is.

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AI is Transforming the Digital Economy through FinTech. How its doing that we will answer below by taking help through "Cognitive Ergonomics". May assuming AI more human then it is.

The post How Cognitive Ergonomics of AI Exciting FinTech appeared first on Vinod Sharma's Blog.

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How AI is Helping to Prevent Physician Burnout

So much of a physician’s workload includes repetitive, tedious tasks involved in researching diagnoses and analyzing patient data and imaging. On top of increasingly demanding administrative and regulatory burdens and electronic health records (EHR) hassles, it’s no wonder physicians are burning out in record numbers. Experts in artificial intelligence (AI)—a form of machine learning in […]

So much of a physician’s workload includes repetitive, tedious tasks involved in researching diagnoses and analyzing patient data and imaging. On top of increasingly demanding administrative and regulatory burdens and electronic health records (EHR) hassles, it’s no wonder physicians are burning out in record numbers.

Experts in artificial intelligence (AI)—a form of machine learning in which computers can be trained to recognize patterns in large swaths of data—are hopeful that AI will be a key part of reducing physicians burdens and saving them time and energy.

“We live in an age where a lot more data can be generated than a physician can really analyze,” says Mark Lambrecht, PhD, director of the global health and life sciences department at SAS, a North-Carolina based analytics company that offers solutions to healthcare providers and payers.

He believes that AI can step in to help. “Studies have shown that AI can help physicians reduce the time they have their hands on the keyboard,” Lambrecht says. “They do this by capturing the data automatically, making sense of it, providing content, and making sure the data is put in the right field.”

Lambrecht gives another example of how AI can help physicians who have patients with type one diabetes. “There are pens that can measure glucose values every minute. Lots of physicians are not able to interpret that data, so we have techniques in AI to help that interpretation, to see if a patient is stable or unstable.”

AI is already improving workflow for radiologists, according to Tarik Alkasab, MD, PhD, service chief for informatics, IT and operations at Massachusetts General Hospital in Boston. Before AI, in order for a radiologist to interpret an x-ray, they’d have to flip through a book full of hundreds of images and manually find the best match for their x-ray. Now, with AI, he says, Mass General is incorporating a system that automatically detects the best match, and then shows that to the radiologist along with some neighboring ones. “The tedious task of finding the book and flipping through it to find the right information is not something the radiologist has to do anymore.”

Alkasab feels that two of the reasons for physician burnout are related to “hunt and search” tasks and the documentation process, both of which can be improved upon by AI. “[Physicians] will do less of the searching, describing and measuring kinds of tasks, and more of the analyzing, synthesizing, evaluating and planning kinds of tasks. AI is going to be a lot more rewarding and less tedious.”

Read the source article in Medical Economics.

Here Are 10 Customer Experience Implementations Of AI

The future of customer experience is artificial intelligence. Artificial intelligence is popping up everywhere and changing how customers interact with brands. In fact, by 2025, an estimated 95% of customer interactions will be supported by AI technology. From chatbots to automation, artificial intelligence helps brands learn more about their customers to enhance personalization. Here are […]

The future of customer experience is artificial intelligence. Artificial intelligence is popping up everywhere and changing how customers interact with brands. In fact, by 2025, an estimated 95% of customer interactions will be supported by AI technology.

From chatbots to automation, artificial intelligence helps brands learn more about their customers to enhance personalization. Here are just a few of the ways brands are leveraging artificial intelligence and machine learning to make customer experiences better:

1-800 Flowers Leverages A Chatbot To Speed Up The Customer Experience

1-800-FLOWERS made ordering the perfect floral arrangement even easier by creating a Facebook Messenger chatbot to help customers order flowers. The bot is trained to pick up on conversational cues to suggest arrangements—if a customer mentions they need something quickly, the bot can briskly suggest the perfect flowers to win someone over. The bot shows pictures of each arrangement and makes it easy for customers to create their own message and set up the delivery

Retailer North Face Uses Watson To Create A Personalized Shopping Experience

Outdoor retailer North Face uses IBM’s AI supercomputer Watson to create a personalized online shopping experience. The site helps customers refine product selections based on their answers to a series of questions. If a customer says they like to hike in the winter, the program would ask questions about their location and preferences to recommend a jacket that will keep them warm and work with their preferred activities. Instead of sorting through hundreds of products to find the right one, the bot makes the choice much easier.

Dixons Carphone Recommends Insurance Through A Chatbot

UK-based Dixons Carphone – a multinational electrical and telecommunications retailer and services company – uses artificial intelligence in the form of a bot named Cami to connect online and in-store shopping experiences. Cami is a product expert who can recommend items, give advice, and anticipate customer’s needs and future purchases. If someone buys a new mobile device, Cami can automatically recommend cases or insurance. Cami can also easily check inventory, so in-store associates can stay with the customers. Employees can spend more time interacting with customers in the front of the store instead of sorting through inventory in the back of the store.

Ticketmaster Combats Fraud With Artificial Intelligence

Ticketmaster turned to artificial intelligence to combat ticket fraud, which was making the ticket buying experience negative for its customers. The company built a bigger bot to fight scalper bots that buy tickets and sell them for higher rates. Before tickets go on sale, customers must register on the site. The AI bot then analyzes every customer to make sure the people purchasing tickets are actually human. It seems to be working, as fewer tickets are ending up listed on third-party sites.

Read the source article at Forbes.

DATA – Blue Ocean Shift Strategy (Boss)

BOSS – Blue Ocean Shift Strategy can actually help and create vision to focus on areas such as AI, blockchain for education, health & agriculture, create ecosystems using BigData analytics and IoT. To capture a quick snapshot of this strategy, cer…

BOSS – Blue Ocean Shift Strategy can actually help and create vision to focus on areas such as AI, blockchain for education, health & agriculture, create ecosystems using BigData analytics and IoT. To capture a quick snapshot of this strategy, certainly, Big Data appears to be most effective and efficient driver for Blue Ocean Strategy. Based on a limited set....

2018 Year of Intelligence – Artificial & Augmentation

Year 2018 will be known as year of Artificial Intelligence and Intelligence Augmentation for sure.We used to think artificial intelligence was a silly sci-fi concept but when you really look into it, it seems like its been slowly encroaching into most …

Year 2018 will be known as year of Artificial Intelligence and Intelligence Augmentation for sure.We used to think artificial intelligence was a silly sci-fi concept but when you really look into it, it seems like its been slowly encroaching into most areas of everyday life! AI would become just a computer inside the robot or another software or a brain siting out of human body.

Demystifying AI, Machine Learning and Deep Learning

This was the first serious proposal in the philosophy of artificial intelligence, which can be explained as: a science developing technology to mimic humans to respond in a circumstance. In simple words AI involves machines that behave and think like h…

This was the first serious proposal in the philosophy of artificial intelligence, which can be explained as: a science developing technology to mimic humans to respond in a circumstance. In simple words AI involves machines that behave and think like humans i.e Algorithmic Thinking in general. Computers start simulating the brain’s sensation, action, interaction, perception and cognition abilities.

World Wide Data Wrestling

Big data presents a tremendous opportunity for enterprises across multiple industries especially in the tsunami like data flow industry of “Payments”. FinTech, InsureTech, MedTech are major data generating industries i.e massive group of factories. Acc…

Big data presents a tremendous opportunity for enterprises across multiple industries especially in the tsunami like data flow industry of “Payments”. FinTech, InsureTech, MedTech are major data generating industries i.e massive group of factories. According to some data from Google it shows technology based innovative insurance companies