Forces Shaping Cognitive Computing

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Cognitive computing has the power to accelerate, enhance and scale human expertise.  According to IBM, these six factors – society, technology, perception, information, policy and skills – are shaping how the technology advances.  Below is a brief summary of each factor:

Society – consumers will continue to demand more intelligent machines and it is expected that mobile device use will continue to grow.  These two trends will allow society as a whole to gain more familiarity and comfort with cognitive systems.

Technology – leading experts agree that current architecture must advance to take full advantage of cognitive computing.  So far technology advances such as natural language processing and deep-learning coupled with more robust data from IoT devices has made strides in providing better input and output opportunities for cognitive systems.

Perception – continued education about the value of cognitive computing, grounded in reality, is necessary to keep interest and funding.

Information – With the explosion in digital data, it is getting harder and harder to keep pace with the volume and velocity without technology such as cognitive computing.  IDC predicts that the digital universe will reach 40 zettabytes by 2020 which will further drive the advancement of cognitive capabilities.

Policy – as more entities adopt the technology, policies around data sharing, data privacy, data security and decision making will also need to be revised and reapplied.

Skills – a skilled work-force is recognized as a top challenge by industry leaders.  Currently, the skills needed to advance the technology are limited.  The supply of skilled workers is low and more are needed to not only put cognitive systems in place but to also produce actionable results.

If you would like to read in more depth about the factors affecting cognitive computing growth, please check out this white paper by IBM: Your Cognitive Future, How Next-Gen Computing Changes the Way We Live and Work.

Adding Cognitive Computing to Your Business

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Many organizations are using cognitive computing, such as IBM Watson, to crunch data and produce insights to improve customer engagement, productivity and to grow their businesses.  But, for many of us adopting cognitive computing can seem daunting. IBM shares these best practices for adopting cognitive computing:

Start with a pilot project. Most businesses adopt cognitive computing by first testing the technology on a specific business issue.  From there these companies find success by embracing a test-and-learn mindset so that they are refining their model as they learn more.  Finally, your cognitive system and solution must be scalable, so you are ready when it is time to expand.

Data is everything. When approaching a cognitive project you must have a clear data strategy.  You must know what data sources you need, where the data is created and how it is managed. Your data set must also be big enough in order for your cognitive system to drive valid conclusions.

Build a team. Many early adopters of cognitive computing also agree that building a cross-disciplinary project team, whether the project is large or small, is important.  Allowing business to be involved helps make sure the insights derived from your cognitive system can be applied to the customer or company-specific challenge.  The team also looks for and relies on IT partners that bring to the table specific technology and industry expertise to augment critical skills.

At Evolving Solutions we can help you adopt cognitive computing through IBM Watson.  IBM Watson has the ability to:

  • Understand by analyzing and interpreting all of your data both structured and unstructured
  • Reason by providing personalized recommendations based on a user’s personality, tone and emotion
  • Learn by utilizing machine learning to grow expertise in a specific app or system
  • Interact by creating chat bots that can actually engage in dialogue with users

Our team works with you to first access your IT architecture, data and specific needs to determine which IBM Watson solution would best suit.  We then put together a recommendation on how to best implement the cognitive solution and work closely with IBM and your team to set it up.

Read more about what cognitive computing can do for your business.

How Artificial Intelligence is Boosting Productivity

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“Artificial intelligence (AI) is rapidly moving from nice-to-have into must-have territory for organizations. In fact, nearly six in ten AI early adopters think it will be a necessary element to remain competitive within the next few years. Two-thirds say AI is very important to their organization’s strategy and success”, reports Susan Hupfer for IBM. In fact, 62% of early adopters are reporting that their AI initiatives are exceeding their expectations.

What can AI systems do? AI technologies augment human intelligence to help improve decision making by crunching large amounts of data quickly and being able to generate predictions, relations and recommendations.  This helps managers make more informed decisions faster. Here are some examples of how AI is helping companies boost their productivity:

  • Search. For many companies offering an intelligent search option for employees and customers across fragmented systems and data sources is difficult.  AI search platforms have enabled companies to improve search offerings for both structured and unstructured data
  • Customer care. AI systems are working in a number of ways for customer care departments. In some case, AI evaluates natural language questions submitted via text, web chats or instant messaging platforms. In other cases, AI  allows customer care employees to find faster the right answers to customer questions
  • Workflows. Some companies are also using AI systems to compile “organizational wisdom” to cut down on the bottlenecks that can happen when the same subject matter experts are repeatedly sought out for information
  • Operations.  Equipment and operational based businesses are using the predictive powers of AI systems to identify potential risks for downtime and to better plan for equipment maintenance. These businesses can also use these predictive elements to better manage inventory and supply chains to save money

According to IBM, half of early adopters are already reporting workplace productivity and efficiency.  Think about how AI technology could combine with your business  strengths to improve operations, employee performance and ultimately customer satisfaction.

Early Adopters Report Cognitive Benefits

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IBM explains cognitive computing as follows, “cognitive technology augments human expertise to unlock new intelligence from vast quantities of data and to develop deep, predictive insights at scale.”  Cognitive computing is opening up more real-time opportunities  for many businesses across many industries. In fact, analysts expect investment in cognitive technology to grow from $2.5 billion in 2014 to $12.5 billion in 2019. IBM recently surveyed over 600 decision makers who are early adopters and asked about the benefits they are experiencing.

First, who are the early adopters?  Below is a great graphic from IBM outlining where these early adopters fall within their cognitive uses:

The cognitive early adopters

Here are also some of the reasons why they are investing in cognitive:

  • 65% of early adopters view cognitive technology as very important to their organization’s strategy
  • 58% feel that cognitive is essential for digital transformation
  • 58% reported that they feel strongly that cognitive will become a “must have” in just a few short years

62% of cognitive users are already reporting that their projects have exceeded expectations.  For the most part these early adopters are finding success in three categories: customer engagement, productivity and efficiency and business growth. Here is a break down from the survey:

  • 49% report more personalized customer/user experiences
  • 42% said they have been enabled to respond faster to customer/market demands
  • 46% have seen improved decision making and planning
  • 46% report improved security and compliance
  • 41% have used cognitive to expand the company into new markets
  • 45% report a reduction in costs due to productivity and efficiency gains

Business growth - IBM Cognitive Graphic

The road to adoption isn’t always easy. Many of the decision makers surveyed sited data management and an employee skills gap as challenges. Turning to outside expertise has been key to helping them overcome both challenges.

Cognitive computing is helping many early adopters unlock new opportunities. As more practical use cases develop, we can expect more companies to put cognitive technology to work for them.

Cognitive Computing: Improving X-Rays

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“What if your X-ray could predict a potential disease months in advance,” writes Laura Lorenzetti for Fortune. This past summer IBM Watson Health created a new partnership with leading medical providers and imaging tech companies to see if cognitive computing can take medical imaging one step further to actually predict the chance of diseases like cancer and heart failure.

Ms. Lorenzetti’s article points out that much of the data gathered from an x-ray or MRI is “unstructured.” It can be difficult for computers to connect the information to patient records in a meaningful way. IBM Watson Health is trying to change that and utilizing its power to connect unstructured data with its massive databases of patient medical history.  Ms. Lorenzetti writes, “the goal is to provide new offerings across various medical environments (a hospital ER or an everyday physician’s office) that can connect systems (medical records, picture archiving, lab results) and deliver cognitive insights to doctors on the spot for better diagnoses.”

One example from the article is the use of mammograms. Not only could Watson connect the image results to the patient’s medical history but it could also “cross-reference against the similar patients within the Watson database.”  These connections could improve a doctor’s  ability to identify early warning signs or risks.

Another example is the use of cognitive computing to help doctors predict which patients are more likely to have a heart attack after reporting chest pain.  Ms. Lorenzetti reports that 2% of patients who visit an ER with chest pain have the early signs of a heart attack missed. By connecting the data dots IBM Watson Health could help doctors identify these signs better.

IBM Watson Health’s shear power to process unstructured data such as medical imaging while also consuming vast amounts of patient data allows for it to draw cognitive insights that will one day improve patient diagnoses and treatments.