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Published By: SAS     Published Date: Mar 06, 2018
This interview survey explores enterprise readiness for artificial intelligence (AI). Respondents came from across EMEA and from a number of industries and sectors. Their views on AI and their organisations’ levels of readiness were diverse. Download this whitepaper to learn more!
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SAS
Published By: SAS     Published Date: Mar 06, 2018
What management and leadership challenges will the next wave of analytic technology bring? This Insight Center on HBR.org went beyond the buzz of what artificial intelligence can do, to talk about how it will change companies and the way we manage them.
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SAS
Published By: SAS     Published Date: Mar 06, 2018
These emerging technologies and solutions certainly are not unique to financial services. But Stewart, a business director of security intelligence solutions within the SAS Security Intelligence Practice, sees particular interest and application in AML circles. "There remain a good number of manual processes within financial crimes departments in financial institutions, and AI can help automate some of those rote tasks such as document review or alert triage," he says. "Due to investments in technology, there is a lower barrier of entry for midsized institutions. "And finally, there's this anxiety over the unknown - those risks they are not able to detect, that may be hidden using traditional techniques - so they're hoping that more advanced, unsupervised learning techniques can be used to identify those edge cases or behaviors that are out of norm." In an interview about analytics and the AML paradigm shift, Stewart discusses: • The new industry intrigue with artificial intelligence a
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SAS
Published By: SAS     Published Date: Jun 06, 2018
A multitude of “things” generate floods of big data – cars, wearables, machines and appliances. Wouldn’t you like to sift through that noise and become an organization that relies on data to make fact-based decisions? Learn about the three foundations of becoming data-driven – data management, analytics and visualization – and how they can increase profitability, boost performance, raise market share and improve operations. Read about hurdles to becoming a data-driven organization and learn best practices from others. Then get a glimpse of what the future holds with the Internet of Things (IoT), edge analytics, artificial intelligence (AI) and other technology innovations.
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SAS
Published By: Group M_IBM Q2'19     Published Date: May 23, 2019
Defense and intelligence agencies want to leverage the data they collect so they can use artificial intelligence to enhance readiness – but most who run these programs don’t know how to get started and find it difficult to make the business case to their leadership. In this research report, created by GovLoop in partnership with IBM, which provides innovative technology solutions for national security and military intelligence, you’re going to learn where your peers stand—and some practical tips on how to get started—even if you think your data is “dirty” or not ready for advanced applications.
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Group M_IBM Q2'19
Published By: Group M_IBM Q3'19     Published Date: Aug 05, 2019
The possibilities for the machine-augmented future are endless — but while artificial intelligence has become ubiquitous in the commercial world, its adoption in government has been slow. This toolkit will help agencies identify the necessary steps to embark on an AI journey — and provide tips for government innovators to easily progress from crawling and walking to the running stage with the technology.
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Group M_IBM Q3'19
Published By: IBM     Published Date: Aug 01, 2018
Your customers aren't the only ones who can benefit from advancing artificial intelligence (AI) support — your employees can, too. Chatbots help employees who service customers, and you can build them with mature AI components. But success requires a focus on tasks rather than job replacement as well as a cyborg-like division between human and machine tasks. This report helps infrastructure and operations (I&O) pros determine which tasks are best executed by people and which are best left to machines, with use cases describing how that looks.
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IBM
Published By: IBM     Published Date: Aug 01, 2018
Inefficient contracting can cause firms to lose up to 40% of a deal’s value--but contracting doesn't have to be inefficient anymore. Watson can help your procurement teams dramatically cut the time they spend manually reading through, highlighting and comparing dense contracts--all while increasing the accuracy of their work. Join IBM Watson and client experts as they share how easy it is to start applying artificial intelligence to streamline contract reviews and improve accuracy. Get started today ... and in as little as six weeks, your contract governance teams can be implementing a transformative AI-solution.
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IBM
Published By: Group M_IBM Q418     Published Date: Sep 10, 2018
Businesses are struggling with numerous variables to determine what their stance should be regarding artificial intelligence (AI) applications that deliver new insights using deep learning. The business opportunities are exceptionally promising. Not acting could potentially be a business disaster as competitors gain a wealth of previously unavailable data to grow their customer base. Most organizations are aware of the challenge, and their lines of business (LOBs), IT staff, data scientists, and developers are working to define an AI strategy. IDC believes that this emerging environment is to date still highly undefined, even as businesses must make critical decisions. Should businesses develop in-house or use VARs, systems integrators, or consultants? Should they deploy on-premise, in the cloud, or in some hybrid form? Can they use existing infrastructure, or do AI applications and deep learning require new servers with new capabilities? We believe that many of these questions can be
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Group M_IBM Q418
Published By: Group M_IBM Q2'19     Published Date: Apr 01, 2019
Businesses are struggling with numerous variables to determine what their stance should be regarding artificial intelligence (AI) applications that deliver new insights using deep learning. The business opportunities are exceptionally promising. Not acting could potentially be a business disaster as competitors gain a wealth of previously unavailable data to grow their customer base. Most organizations are aware of the challenge, and their lines of business (LOBs), IT staff, data scientists, and developers are working to define an AI strategy.
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Group M_IBM Q2'19
Published By: Group M_IBM Q2'19     Published Date: Apr 01, 2019
IDC strongly believes that the days of homogenous compute, in which a single architecture dominates all compute in the datacenter, are over. This truth has become increasingly evident as more and more businesses have started to launch artificial intelligence (AI) initiatives. Many of them are in an experimental stage with AI and a few have reached production readiness, but all of them are cycling unusually fast through infrastructure options to run their newly developed AI applications and services on.
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Group M_IBM Q2'19
Published By: IBM     Published Date: Apr 07, 2017
Data science platforms are engines for creating machine-learning solutions. Innovation in this market focuses on cloud, Apache Spark, automation, collaboration and artificial-intelligence capabilities. We evaluate 16 vendors to help you make the best choice for your organization. This Magic Quadrant evaluates vendors of data science platforms. These are products that organizations use to build machine-learning solutions themselves, as opposed to outsourcing their creation or buying ready-made solutions.
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data analytics, product refinement, business exploration, advanced prototyping, analytics, data preparation, customer support, sales relations, market research, model management
    
IBM
Published By: Group M_IBM Q1'18     Published Date: Feb 27, 2018
Forrester survey: global IT leaders plan their transition to consolidated, cognitive smartphone, tablet, laptop, and IoT security by 2020.
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iot security, internet of things, mobility
    
Group M_IBM Q1'18
Published By: VMS     Published Date: Jul 31, 2009
If management has not already cut your budget, be prepared to “prove it or lose it” soon. This report will help you think through your measurement strategies, and either fine-tune an existing program, or get one started post haste.
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vms, economy, measurement strategies, budget, pr objective, objective, smart media, share, radio monitoring, proof of performance, realtime monitoring, artificial intelligence, human analysis, opportunities to see, ots, metrics, benchmark, proof of performance, business intelligence
    
VMS
Published By: VMS     Published Date: Jul 31, 2009
One of the big challenges with massive PR initiatives is the difficulty in measuring the outcomes as it pertains to your brand and business objectives set. Read this guide for a five step process that will help you determine the impact of your PR initiatives and compare it to the organizational goals they were aimed to accomplish.
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awareness, preferences, share, share of discussion, brand equity, cgm/wom, goals, economy, measurement strategies, budget, pr objective, objective, smart media, share, radio monitoring, proof of performance, realtime monitoring, artificial intelligence, human analysis, opportunities to see
    
VMS
Published By: VMS     Published Date: Jul 31, 2009
In the times of increased awareness and integrated communication across channels, it is crucial to understand correlation between the advertising spend and the PR that surrounds your brand. This report sheds new light on the impact of earned and paid media on the effectiveness of paid advertising.
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vms, economy, measurement strategies, budget, pr objective, objective, smart media, share, radio monitoring, proof of performance, realtime monitoring, artificial intelligence, human analysis, opportunities to see, ots, metrics, benchmark, proof of performance, communications, vantage
    
VMS
Published By: SAS     Published Date: Aug 28, 2018
Machine learning systems don’t just extract insights from the data they are fed, as traditional analytics do. They actually change the underlying algorithm based on what they learn from the data. So the “garbage in, garbage out” truism that applies to all analytic pursuits is truer than ever. Few companies are already using AI, but 72 percent of business leaders responding to a PWC survey say it will be fundamental in the future. Now is the time for executives, particularly the chief data officer, to decide on data management strategy, technology and best practices that will be essential for continued success.
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SAS
Published By: SAS     Published Date: Oct 03, 2018
Fraudsters are only becoming smarter. How is your organization keeping pace and staying ahead of fraud schemes and regulatory mandates to monitor for them? Technology is redefining what’s possible in fighting fraud and financial crimes, and SAS is at the forefront, offering solutions to: • Protect from reputational, regulatory and financial risks. • Reduce the cost of fraud and financial crimes prevention. • Gain a holistic view of risk across functions. • Include cyber events in regulatory report filings. In this e-book, learn the basics in how to prevent fraud, achieve compliance and preserve security. SAS fraud solutions use advanced analytics and artificial intelligence to help your organization better detect and prevent fraud. By applying analytics and powerful machine learning on a unifying platform, SAS helps organizations around the globe detect more financial offenses, reduce false positives and run more efficient investigations.
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SAS
Published By: SAS     Published Date: Jan 30, 2019
Machine learning systems don’t just extract insights from the data they are fed, as traditional analytics do. They actually change the underlying algorithm based on what they learn from the data. So the “garbage in, garbage out” truism that applies to all analytic pursuits is truer than ever. Few companies are already using AI, but 72 percent of business leaders responding to a PWC survey say it will be fundamental in the future. Now is the time for executives, particularly the chief data officer, to decide on data management strategy, technology and best practices that will be essential for continued success.
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SAS
Published By: BlackBerry Cylance     Published Date: Mar 12, 2019
Artificial intelligence (AI) has become a security industry buzzword so broadly applied as to become almost meaningless. When every product boasts AI capabilities, security decision makers may quickly become cynical, even in the face of the most exciting innovation shaping cybersecurity today.
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BlackBerry Cylance
Published By: BlackBerry Cylance     Published Date: Apr 15, 2019
Artificial intelligence (AI) leads the charge in the current wave of digital transformation underway at many global companies. Organizations large and small are actively expanding their AI footprints as executives try to comprehend more fully what AI is and how they can use it to capitalize on business opportunities by gaining insight to the data they collect that enables them to engage with customers and hone a competitive edge. But, while AI may indeed be the frontier of enterprise technology, there remain many misconceptions about it. Part of the confusion stems from the fact that AI is an umbrella term that covers a range of technologies — including machine learning, computer vision, natural language processing, deep learning, and more — that are in various stages of development and deployment. The use of AI for dynamic pricing and targeted marketing has been in use for a while, but actual AI computing where machines think like humans is still many years from becoming mainstream. T
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BlackBerry Cylance
Published By: BlackBerry Cylance     Published Date: Sep 18, 2019
There is now broad consensus among security professionals that artificial intelligence (AI) technologies can play an important role in reducing cyber risks. Exactly what that role is, however, and how it will evolve over time remains unclear for respondents to a new SANS Institute research study sponsored by BlackBerry Cylance. Opinions varied about the maturity of AI, its benefits and risks, and the baseline requirements for an AI-enabled security solution. Download the report today for the complete survey results and learn: 1) How perceptions of AI vary across industry sectors and organizational roles and responsibilities; 2) How AI technologies compare and contrast with human intelligence; 3) How machine learning is driving advances in the field; 4) What respondents believe to be the greatest risks and benefits of AI; and, 5) The most significant barriers to broader AI adoption.
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BlackBerry Cylance
Published By: BlackBerry Cylance     Published Date: Sep 18, 2019
“More than 70 percent of cyber attacks target small businesses," according to National Cyber Security Alliance estimates. That’s not surprising when you consider how many small and medium-sized businesses (SMBs) still rely on legacy AV tools despite their repeated failures to stop modern malware, ransomware, and zero-day attacks. Legacy AV is a lose-lose-lose proposition for SMBs. Attacks get through and cause damage. IT staff struggle to keep up with endless signature file updates from their AV vendors. End-users complain about sluggish system performance during scans and signature file updates. Fortunately, next-generation solutions are now available that protect endpoints with artificial intelligence (AI) rather than signatures. Ready to learn more? Then read the new eSecurity Planet executive brief sponsored by BlackBerry Cylance.
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BlackBerry Cylance
Published By: BlackBerry Cylance     Published Date: Sep 18, 2019
Artificial intelligence (AI) has become the buzzword du jour for endpoint protection platform (EPP) vendors struggling to remain relevant in a rapidly changing threat landscape. Why does one EPP prevent breaches while another only facilitates incident response? BlackBerry Cylance’s new eBook cuts through the noise with a concise analysis of AI’s role in cyber defense and the four key criteria for evaluating EPP investments. Read the BlackBerry Cylance eBook to learn more.
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BlackBerry Cylance
Published By: Bronto     Published Date: Feb 01, 2018
What you'll learn: • Why batch-and-blast email is losing its effectiveness and the email techniques to replace it. • How techniques like user-generated content and the mining of unstructured data can boost email effectiveness. • What artificial intelligence is offering today – and what it could offer years from now. • How omnichannel merchants can leverage physical locations as part of their online strategy.
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email, omnichannel, retail, ecommerce
    
Bronto
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