artificial intelligence

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Why Cylance Beats the Competition When It Comes to Endpoint Protection

Published By: BlackBerry Cylance     Published Date: Jul 02, 2018
The 21st century marks the rise of artificial intelligence (AI) and machine learning capabilities for mass consumption. A staggering surge of machine learning has been applied for myriad of uses — from self-driving cars to curing cancer. AI and machine learning have only recently entered the world of cybersecurity, but it’s occurring just in time. According to Gartner Research, the total market for all security will surpass $100B in 2019. Companies are looking to spend on innovation to secure against cyberthreats. As a result, more tech startups today tout AI to secure funding; and more established vendors now claim to embed machine learning in their products. Yet, the hype around AI and machine learning — what they are and how they work — has created confusion in the marketplace. How do you make sense of the claims? Can you test for yourself to know the truth? Cylance leads the cybersecurity world of AI. The company spearheaded an innovation revolution by replacing legacy antivirus software with predictive, preventative solutions and services that protect the endpoint — and the organization. Cylance stops zero-day threats and the most sophisticated known and unknown attacks. Read more in this analytical white paper.
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cylance, endpoint, protection, cyber, security
    
BlackBerry Cylance

Providing a Frontline Defense Against Fileless Malware

Published By: BlackBerry Cylance     Published Date: Jul 02, 2018
Fileless attacks surged in 2017, largely due to their ability to bypass traditional antivirus solutions. Last year was host to several fileless malware victories. OceanLotus Group infiltrated Asian corporations during Operation Cobalt Kitty, and conducted nearly six months of fileless operations before detection. Ransomware hall-of-famers Petya and WannaCry both implemented fileless techniques in their kill chains. Every major player in information security agrees that fileless attacks are difficult to stop, and the threats are growing worse. Abandoning files is a logical and tactical response to traditional AV solutions which have overcommitted to file-intensive and signature-based blacklists. What can security solutions offer when there are no infected files to detect? How will a blacklist stop an aggressor that only uses legitimate system resources? The security landscape is changing and the divide between traditional AV products and next-generation security solutions is growing wider by the day. Cylance® has built a reputation on security driven by artificial intelligence and provides a frontline defense against fileless malware. This document details how Cylance protects organizations.
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malware, predictive, test, response
    
BlackBerry Cylance

5 Categories of Questions for Evaluating AI Driven Security Solutions

Published By: BlackBerry Cylance     Published Date: Aug 22, 2018
Artificial intelligence (AI) is a security industry term that is now so broadly and loosely applied, it's become almost meaningless. Now that every product boasts AI capabilities, security decision makers are becoming cynical, even in the face of the most exciting innovation shaping cybersecurity today.
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security, solutions, industry, artificial, intelligence
    
BlackBerry Cylance

Security Gets Smart with AI

Published By: BlackBerry Cylance     Published Date: Apr 26, 2019
The concept of artificial intelligence (AI) has been with us since the term was coined for the Dartmouth Summer Research Project on Artificial Intelligence in 1956. Today, while general AI strives for full cognitive abilities, there is a narrower scope—this better-defined AI is the domain of machine learning (ML) and other algorithm-driven solutions where cybersecurity has embraced AI. SANS recently conducted a survey of professionals working or active in cybersecurity, and involved with or interested in the use of AI for improving the security posture of their organization. Read their report to learn their survey findings, conclusions, and recommended considerations.
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BlackBerry Cylance

Artificial Intelligence for Executives: Integrating AI into your analytical strategy

Published By: SAS     Published Date: Mar 06, 2018
Information on artificial intelligence (AI) is flooding the market, media and social channels. Without doubt, it’s certainly a topic worth the attention. But, it can be difficult to sift through market hype and grandiose promises to understand exactly how AI can be applied in practical and reliable solutions. Like most technological advances, incorporating new technology into business processes requires significant leadership and effective direction that all stakeholders can easily understand.
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SAS

Making Sense of AI

Published By: SAS     Published Date: Mar 06, 2018
Today's artifical intelligence (AI) solutions are not sentient in the manner popularized in science fiction by scores of self-aware and typically nefarious androids. Even so, the ability to arm such systems with the ability to directly sense and respond to their in situ environment is critical. Why? In the future, our experiences will be smart, intuitive and informed by analytics that are not seen but felt via new business, personal and operational engagement models. Enabling this interaction requires AI applications that can sense, analyze and respond to their environment in an intelligent and interactive manner. Without requiring the end user to write, understand or interpret code. “Sensitive” artificial intelligence enables: • More productive use of expanded (big, often unstructured) information sources • Intuitive man-machine interactions (no code-speak here!) • Adaptive, immersive experiences and environments As frequently touted on the nightly news, AI’s popularity is clear. Ho
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SAS

TDWI Best Practices Report Q3 2017: Advanced Analytics: Moving Toward AI, Machine Learning and Natur

Published By: SAS     Published Date: Mar 06, 2018
There is a lot of excitement in the market about artificial intelligence (AI), machine learning (ML), and natural language processing (NLP). Although many of these technologies have been available for decades, new advancements in compute power along with new algorithmic developments are making these technologies more attractive to early adopter companies. These organizations are embracing advanced analytics technologies for a number of reasons including improving operational efficiencies, better understanding behaviors, and gaining competitive advantage.
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SAS

The Enterprise AI Promise: Path to Value

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

The Next Analytics Age: Artificial Intelligence (A Harvard Business Review Insight Center Report)

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

ISMG: Analytics and the AML Paradigm Shift eBook

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

Becoming a Data-Driven Organization: The what, why and how

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

Data & Defense: How to Boost Readiness

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

The Government AI Toolkit

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

AI Is Ready For Employees, Not Just Customers

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

Disrupting Procurement with AI

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

Hitting the Wall with Server Infrastructure for Artificial Intelligence

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

Hitting the Wall with Server Infrastructure for Artificial Intelligence Whitepaper

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

Rethinking infrastructure for AI WP

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

Magic Quadrant For Data Science Platforms

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

Mobile Vision 2020: The Impact of Mobility, The Internet Of Things, And Artificial Intelligence On T

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

8 Great Tips for Smart Media Measurement in today's economy

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
    
VMS

Mixing PR Goals with Measures - a Measurement Matrix

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

Newfound impact of PR on advertising

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

Data Management for Artificial Intelligence

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

Fight Fraud and Financial Crimes with Analytics and AI

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
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