Turbotodd

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IBM Expands Watson Data Platform to Help Unleash AI

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 IBM today announced new offerings to its Watson Data Platform, including data cataloging and data refining, which is designed to make it easier for developers and data scientists to analyze and prepare enterprise data for AI applications, regardless of its structure or where it resides. By improving data visibility and helping to better enforce data security policies, users can now connect and share data across public and private cloud environments.

By 2018, nearly 75 percent of developers will build AI functionality into their apps, according to IDC. However, they also face the obstacle of making sense of increasingly complex data that lives in different places, and that must be securely and continually ingested to power these apps.

Addressing these challenges, IBM has expanded the functionality of its Watson Data Platform, an integrated set of tools, services and data on the IBM Cloud designed to enable data scientists, developers and business teams to gain intelligence from the data most important to their roles, as well as easily access services like machine learning, AI and analytics.

“We are always looking for new ways to gain a more holistic view of our clients’ campaign data, and design tailored approaches for each ad and marketing tactic,” said Michael Kaushansky, Chief Data Officer at Havas, a global advertising and marketing consultancy. “The Watson Data Platform is helping us do just that by quickly connecting offline and online marketing data. For example, we recently kicked off a test for one of our automotive clients, aiming to connect customer data, advertising information in existing systems, and online engagement metrics to better target the right audiences at the right time.”

Specifically, this expansion includes:

  • New Data Catalog and Data Refinery offerings, which bring together datasets that live in different formats on the cloud, in existing systems and in third party sources; as well as apply machine learning to process and cleanse this data so it can be ingested for AI applications;
  • The ability to use metadata, pulled from Data Catalog and Data Refinery, to tag and help enforce a client’s data governance policies. This gives teams a foundation to more easily identify risks when sharing sensitive data.
  • The general availability of Analytics Engine to separate the storage of data from the information it holds, allowing it to be analyzed and fed into apps at much greater speeds. As a result, developers and data scientists can more easily share and build with large datasets.

More details on the new offerings of the IBM Watson Data Platform may be found here.

To further help companies grasp control of all of their data no matter where it resides, IBM is also announcing a series of new features to its Unified Governance Platform. These bring greater visibility and management of clients’ global data, including new capabilities that help clients as they better prepare for impending data protection regulations such as GDPR.

Built on open source technologies and fueled by IBM Cloud, the Watson Data Platform brings together IBM’s cloud infrastructure, powerful data services and decades of experience helping clients across industries solve their data challenges. Linked closely with the most popular communities among data scientists and developers, including Python and Spark, the Watson Data Platform continues to evolve to build the most open and complete data operating system on the cloud.

For more information on the Watson Data Platform, visit: https://www.ibm.com/analytics/us/en/watson-data-platform/.

To try and explore the Watson Data Platform, visit the tutorial: www.ibm.biz/wdptutorial.

Written by turbotodd

November 2, 2017 at 9:52 am

IBM Watson To Generate Match Highlights At The U.S. Open

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IBM has announced it is launching IBM Watson Media, a new suite of AI-powered solutions on the IBM Cloud that analyze images, video, language, sentiment and tone, at the US Open.

By combining IBM Watson with IBM’s video capabilities, the United States Tennis Association (USTA) will be able to rapidly share highlight videos of more matches while engaging and informing fans more than ever before.

The US Open will use one of the first solutions available through IBM Watson Media called Cognitive Highlights. Developed at IBM Research with IBM iX, Cognitive Highlights can identify the match’s most important moments by analyzing the statistical tennis data, sounds from the crowd and the reactions of a player using both action and facial expression recognition.

The system then ranks the shots from seven US Open courts and auto-curates the highlights, which simplifies the video production process and ultimately positions the USTA team to scale and accelerate the creation of cognitive highlight packages.

The finished highlight videos will be available in four ways:

  • Each day, the USTA will post a Highlight of the Day, as ranked by Watson, on its Facebook page.
  • Fans that “favorite” players on the US Open apps will receive real-time push notification alerts about those players’ highlights. Fans on iOS 10 can play the highlights within the lock screen.
  • On the player bio page, video highlights will be available across all of the USTA’s digital platforms.
  • Onsite in the player’s lounge and in the fan-facing IBM Watson Experience on the plaza near Court 9.

“The US Open is packed with so much action across so many courts that even the fastest video team is challenged to keep pace with what’s happening,” said Noah Syken, IBM VP of Sports & Entertainment Partnerships. “To meet that challenge, Watson is now watching the matches alongside the USTA to help bring fans closer to the best moments across the courts shortly after they happen. We’re seeing this technology come to life through tennis, but the entire IBM Watson Media portfolio has the potential to impact many industries.”

Written by turbotodd

August 31, 2017 at 8:54 am

Posted in 2017, cognitve computing, ibm watson, us open

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Codify Academy Users IBM Cloud, Watson to Design Cognitive Chatbot

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IBM recently announced that Codify Academy, a San Francisco-based developer education startup, tapped into IBM Cloud’s cognitive services to create an interactive cognitive chatbot, Bobbot, that is improving student experiences and increasing enrollment.

Using the IBM Watson Conversation Service, Bobbot fields questions from prospective and current students in natural language via the company’s website.

Since implementing the chatbot, Codify Academy has engaged thousands of potential leads through live conversation between the bot and site visitors, leading to a 10 percent increase in converting these visitors into students.

IBM Cloud with Watson provided Codify Academy with the speed and scale needed to immediately start building with cognitive intelligence. Bobbot can answer more than 200 common questions about enrollment, course and program details, tuition, and prerequisites, in turn enabling Codify Academy staff to focus on deeper, more meaningful exchanges.

For example, students can ask questions such as “What kind of job will I be able to find after I complete the program?” or “How do I apply, and what are tuition rates?”

“We saw a huge spike in interest from potential students in the early days of our company, which is a fortunate problem to have, but made us realize we needed to quickly build a solution to help us scale,” said Matt Brody at Codify Academy. “IBM Cloud gave us the infrastructure and access to cognitive services, including Watson, that we needed to quickly build and deploy an intelligent and intuitive bot – in turn helping us to field all inquiries and significantly increase enrollment.”

Codify Academy runs on the IBM Cloud platform, which has become one of the largest open, public cloud deployments in the world. It features more than 150 tools and services, spanning categories of cognitive intelligence, blockchain, security, Internet of Things, quantum computing and DevOps.

“We have designed our cloud platform to serve as the best possible engine for cognitive apps such as chatbots," said Adam Gunther, Director, IBM Cloud. "This enables companies to harness and fine tune incoming data quickly to create highly tailored user experiences.”

To learn more about Codify Academy, visit http://codifyacademy.com/.

Written by turbotodd

August 4, 2017 at 1:42 pm

IBM and University of Alberta Publish New Data on Machine Learning Algorithms to Help Predict Schizophrenia

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IBM scientists and the University of Alberta in Edmonton, Canada, have published new data in Nature’s partner journal, Schizophrenia1, demonstrating that AI and machine learning algorithms helped predict instances of schizophrenia with 74% accuracy.

This retrospective analysis also showed the technology predicted the severity of specific symptoms in schizophrenia patients with significant correlation, based on correlations between activity observed across different regions of the brain. This pioneering research could also help scientists identify more reliable objective neuroimaging biomarkers that could be used to predict schizophrenia and its severity.

Schizophrenia is a chronic and debilitating neurological disorder that affects 7 or 8 out of every 1,000 people. Those with schizophrenia can experience hallucinations, delusions or thought disorders, along with cognitive impairments, such as an inability to pay attention and physical impairments, such as movement disorders.

“This unique, innovative multidisciplinary approach opens new insights and advances our understanding of the neurobiology of schizophrenia, which may help to improve the treatment and management of the disease,” says Dr. Serdar Dursun, a Professor of Psychiatry & Neuroscience with the University of Alberta. “We’ve discovered a number of significant abnormal connections in the brain that can be explored in future studies, and AI-created models bring us one step closer to finding objective neuroimaging-based patterns that are diagnostic and prognostic markers of schizophrenia.”

In the paper, researchers analyzed de-identified brain functional Magnetic Resonance Imaging (fMRI) data from the open data set, Function Biomedical Informatics Research Network (fBIRN) for patients with schizophrenia and schizoaffective disorders, as well as a healthy control group. fMRI measures brain activity through blood flow changes in particular areas of the brain.

Specifically, the fBIRN data set reflects research done on brain networks at different levels of resolution, from data gathered while study participants conducted a common auditory test. Examining scans from 95 participants, researchers used machine learning techniques to develop a model of schizophrenia that identifies the connections in the brain most associated with the illness.

The results of the IBM and University of Alberta research demonstrated that, even on more challenging neuroimaging data collected from multiple sites (different machines, across different groups of subjects etc.) the machine learning algorithm was able to discriminate between patients with schizophrenia and the control group with 74% accuracy using the correlations in activity across different areas of the brain. 

Additionally, the research showed that functional network connectivity could also help determine the severity of several symptoms after they have manifested in the patient, including inattentiveness, bizarre behavior and formal thought disorder, as well as alogia, (poverty of speech) and lack of motivation.

The prediction of symptom severity could lead to a more quantitative, measurement-based characterization of schizophrenia; viewing the disease on a spectrum, as opposed to a binary label of diagnosis or non-diagnosis. This objective, data-driven approach to severity analysis could eventually help clinicians identify treatment plans that are customized to the individual. 

“The ultimate goal of this research effort is to identify and develop objective, data-driven measures for characterizing mental states, and apply them to psychiatric and neurological disorders” said Ajay Royyuru, Vice President of Healthcare & Life Sciences, IBM Research. “We also hope to offer new insights into how AI and machine learning can be used to analyze psychiatric and neurological disorders to aid psychiatrists in their assessment and treatment of patients.”

The Research Domain Criteria (RDoC) initiative of NIMH emphasizes the importance of objective measurements in psychiatry. This field, often referred to as “computational psychiatry”, aims to use modern technology and data driven approaches to improve evidence-based medical decision making in psychiatry, a field that often relies upon subjective evaluation approaches.

As part of the ongoing partnership, researchers will continue to investigate areas and connections in the brain that hold significant links to schizophrenia. Work will continue on improving the algorithms by conducting machine learning analysis on larger datasets, and by exploring ways to extend these techniques to other psychiatric disorders such as depression or post-traumatic stress disorder.

You can learn more about IBM Watson Health solutions here.

Written by turbotodd

July 21, 2017 at 9:21 am

A Mammoth Customer Base

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IBM today announced that Mammoth Resorts, the leading four-season mountain resort operator in California, is using Watson Customer Engagement solutions on the IBM Cloud to create customized offers that are helping to drive record numbers of visitors to the resort every year.

One challenge facing year-round travel destinations such as Mammoth is attracting consumers who often visit multiple location web sites to research potential getaways only to hold off on making a firm decision until they’ve assessed all of their options.

For Mammoth, the question was how to bring prospective customers back to the Mammoth website to ultimately book a trip in advance of peak vacation periods.

With cloud-based Watson Marketing solutions, Mammoth is able to closely monitor customer activity on their website including where visitors are spending most of their time, what they were looking at, whether they left their shopping cart empty and more.

With these details, Mammoth is triggering responsive email campaigns that feature deals on the very items customers were viewing such as a free night’s stay on their next visit. The team can then track which promotions are most successful in sparking return visits to the site.

Since launching these campaigns, the results were almost instantaneous, with email click through rates climbing from 8 percent to 34 percent year-over-year, a growth of 325 percent.

In addition to attracting new guests, IBM Watson Customer Engagement is helping Mammoth build customer loyalty through timely, personalized campaigns that take into account each person’s preferences based on past stays. 

Mammoth Resorts then uses these details to proactively recommend trips, such as a return stay during the February winter break for summer guests that includes the same number of rooms and discounts on lift tickets.

Mammoth also automatically delivers guest alerts around birthdays, booking anniversaries and more, with each communication including special deals on both lodging and other items such as lift tickets as well as recommendations on, for example, off-season vacations options such as a summer mountain bike trip for the family.

You can learn more about IBM Watson Customer Engagement solutions here.

Written by turbotodd

July 20, 2017 at 11:08 am

LivePerson, IBM Watson Offer Combined Platform For AI, Bots To Advance Customer Care

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LivePerson, Inc., a leading provider of cloud mobile and online business messaging solutions, and IBM have announced LiveEngage with Watson, the first global, enterprise-scale, out-of-the-box integration of Watson-powered bots with human agents.

The new offering combines IBM’s Watson Virtual Agent technology with LivePerson’s LiveEngage platform, allowing brands to rapidly and easily deploy conversational bots that get smarter with each interaction, and lets consumers message those brands from their smartphone — via the brand’s app, SMS, Facebook Messenger, or even the brand’s mobile site — instead of having to call an 800 number.

The customer care sector has lagged behind consumers in terms of technology adoption, still requiring most interactions to be conducted by analog voice call. In fact, customers make more than 270 billion phone calls to customer support lines each year.

This legacy approach has not kept pace with the consumer move to smartphones and messaging apps, now the dominant way consumers communicate digitally. Forrester’s 2017 Customer Service Trends report revealed that “Customers of all ages are moving away from using the phone to using self-service — web and mobile self-service, communities, virtual agents, automated chat dialogs, or chatbots — as a first point of contact with a company” and, according to Dimension Data, while there has been a 12 percent decline in phone volume, there has been growth in every digital channel.

LiveEngage with Watson helps meet that demand – allowing consumers to message large brands from their smartphones and instantly get answers from AI-powered bots, with human care representatives brought in seamlessly, in real-time, if a bot is not able to resolve an issue satisfactorily.

The move will help enable millions of consumers to avoid the frustrating experience of legacy, voice-based customer support, which requires them to dial an 800 number, wait on hold, then talk to an agent, and often multiple agents over multiple phone calls.

LiveEngage with Watson gives brands the ability to customize bots based on their own unique corpuses of data — from product manuals to customer service guidelines — creating a personalized interaction that can be up and running as quickly as in a few days. These bots can be informational, personalized, and transactional — quickly addressing the most commonly raised customer service issues such as taking bill payments and finding contact information — while bringing in human expertise when necessary to drive effective customer engagement.

“Providing customer care over 800 numbers is not just extremely costly — it is a poor and antiquated experience for consumers,” says Robert LoCascio, founder and CEO of LivePerson. “Nobody likes waiting on hold. This partnership between IBM and LivePerson marries the technology and services to solve the problem at scale. We’re working with top brands in the telecoms and banking space right now to get this done, moving customer care away from costly, analog voice calls with frustrating hold times and toward consumer-friendly mobile messaging. We’re thrilled to form this partnership. No other company but IBM brings this sophistication of cognitive technology and breadth of supporting consulting and implementation services.”

As business decisions continue to be made with the help of AI, customer care will be no different. IBM Global Business Services, the company’s consulting unit, is providing a set of strategy and implementation services to help companies integrate LiveEngage with Watson as part of their broader business transformation.

By building experiences that learn, and adapt, into core processes, companies can deliver better engagement with customers. Together with LivePerson, IBM plans to operate a Cognitive Care Center of Excellence to help enable brands to drive this change at scale. 

You can learn more about IBM Watson here.

Written by turbotodd

June 15, 2017 at 3:31 pm

IBM Launches Cognitive Era of RegTech With New Watson Financial Services

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IBM has launched the first suite of cognitive solutions to help financial institution professionals manage their regulatory and fiduciary responsibilities.

The Watson-powered software, which can be deployed on the IBM Cloud, is designed to help financial professionals in three areas: understanding regulatory requirements, delivering increased insight into potential financial crimes, and managing financial risk with a new architectural approach for data.

Managing risk and compliance currently consumes 10 to 15 percent of operational spending budgets among major banks, with annual spending estimated at $270 billion per year for financial services organizations.

This burden is expected to only grow in the coming years. By 2020, the global financial services industry will contend with an estimated 300 million pages of regulations, with thousands of new pages added each year after that.

Promontory Financial Group
, an IBM subsidiary that specializes in risk management and regulatory compliance, has trained Watson initially on 60,000 regulatory citations.

Watson has also started to review transactions and cases related to potential financial crimes. The result is a suite of cognitive solutions that are designed to offer professionals assistance in making better-informed risk and compliance decisions with greater speed.

Over time, additional data sets will be added, which will allow the machine learning and analytics embedded in Watson Financial Services to further expand and help improve the insights provided to professionals.

Gene Ludwig, founder and chief executive officer of Promontory Financial Group , added, “The speed and volume of information that financial institutions must manage is already daunting and yet still growing rapidly. The answer to this problem is cognitive technology taught by industry experts, like those at Promontory. Essentially, we’re embedding our deep regulatory experience into Watson so that a broader group of professionals can benefit from this knowledge and help their organizations operate more effectively and efficiently.”

The solutions are available to financial services industry clients, many of whom have worked with IBM and Promontory to address their risk and compliance needs.  

The specific products launched by Watson Financial Services today include:

Watson Regulatory Compliance
Watson Regulatory Compliance will help financial institutions better understand and address the constantly changing regulatory requirements. Watson’s natural language processing capabilities are being used to train and understand the language of regulation, and IBM has started the process of feeding regulations from 200 different sources into the system in order to identify and tag potential obligations. This will help simplify the daily, manual activities of compliance professionals by providing a company-specific view of regulatory requirements. 

Compliance professionals using Watson Regulatory Compliance will have access to a customized and searchable library of regulatory requirements, with the ability to identify the obligations and controls applicable to their business, which can be easily filtered by geography, line of business, product, process and compliance area.

They will also be able to more easily track changes, with the ability to subscribe to only the specific parts of the regulation that are directly relevant to them.

IBM Financial Crimes Insight with Watson
Each year, financial institutions spend $18 to $21 billion on anti-money laundering (AML) activities, $16 to $19 billion on know-your-customer (KYC) requirements, and $11 to $15 billion on conduct surveillance. These activities are extremely manual in nature, often requiring significant time to collect information from various sources. The final decision is often subjective and dependent on the experience of individual analysts.

IBM Financial Crimes Insight with Watson applies cognitive computing, intelligent robotic process automation, identity resolution, network analysis, machine learning, and other advanced analytics capabilities to accelerate due diligence activities and help organizations more effectively understand and manage the plethora of AML alerts generated by today’s transaction monitoring systems.

Combined with Promontory’s expertise, financial institutions can increase the speed and accuracy of customer verification and adverse news collection for KYC requirements, help reduce false positives and speed up case investigations for AML alert reviews.

In addition, IBM’s solution for conduct surveillance is being expanded to address broader conduct risks such as sales practices, client suitability and fiduciary responsibilities. This solution goes beyond traditional rules-based and lexicon approaches and generates increased insight by identifying the various activities and behavior associated with misconduct.

It will also advance complaint management in ways that can further assist professionals responsible for identifying misconduct.

IBM Algo One Big Data Foundation
For many financial institutions, it is a challenge to scale their existing systems, and yet, scaling is necessary to meet the dramatic increase in requirements for Fundamental Review of the Trading Book (FRTB) regulations, Valuation Adjustments (XVA) measures, and liquidity analysis.

IBM Algo One Big Data Foundation is a new architectural approach to help clients achieve the performance that is required to address regulatory compliance.

The solution integrates big data technology with the core risk data management applications of Algo One. This enables financial firms to examine risk in a shorter amount of time with an intuitive user interface. By utilizing structured and unstructured data to its fullest potential, the solution is designed to encourage decision makers to ask more complex questions and get better answers faster when developing new business strategies.

This moves the use of big data from an experimental or niche use at a bank to that of daily production to help satisfy banks’ regulatory and financial planning. The first solutions available as part of the new architectural approach focus on liquidity, application lifecycle management, and market risk.

All of the new Watson Financial Services solutions are available today on the IBM Cloud. For more information about IBM Watson Financial Services, visit https://www.ibm.com/watson/financial-services/.

Written by turbotodd

June 14, 2017 at 9:15 am

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