"Cloud-based predictive analytics platforms are a relatively new phenomenon, and they go far beyond
the remote monitoring systems of a prior generation. Three key features differentiate cloud-based
predictive analytics — data sharing, scope of monitoring, and use of artificial intelligence/machine
learning (AI/ML) to drive autonomous operations. To help familiarize the uninitiated with specifically
what types of value these systems can drive, IDC discusses them at some length in this white paper."
Download this white paper to find out how you could augment your fraud management with Decision Manager machine learning insights from more than 68 billion annually processed Visa and CyberSource transactions – matched with flexible rules-based fraud strategies.
• Detect fraud more accurately with robust data and insights on ever-changing fraud patterns
• Protect your bottom line by reducing fraud and chargebacks
• Increase acceptance rates with the only fraud solution that uses machine learning to generate and test new rules-based strategies from your historic data
The Future of Work: 10 Essentials for Winning Employee Development
Your go-to guide for thriving in the changing face of work
Employee development looks a lot different today than it did just a few years ago. This ebook details 10 trends that are crucial for keeping up with the ever-changing future of work.
The modern workforce is a place where baby boomers, Gen X, millennials and now Gen Z all share the same Nespresso machine. That’s four distinct generations with different views, expectations and priorities. Companies will have to adopt new methods for just about everything—from recruitment and benefits to employee development and career planning.
While there are several key differences between each generation in the modern workforce, how companies should treat them can be summarised in one word: individually.
This ebook is designed to help HR and L&D professionals who want to turn their organisation into a learning environment well-equipped for the workplace of tomorrow, do ex
At Bridge, we know that a big problem facing sales leaders is not being able to onboard or train reps quickly enough to reach targets. In fact, it takes 50% of new reps 6 to 10 months to contribute to quotas. This guide is for sales leaders looking to elevate their teams and realise faster, more effective onboarding from 'Day One'. It helps at every step in the onboarding process, from hiring to providing reps with continuous learning.
NICE has made a significant investment into AI and ML techniques that are embedded into its core workforce management solution, NICE WFM. Recent advancements include learning models that find hidden patterns in the historical data used to generate forecasts for volume and work time. NICE WFM also has an AI tool that determines, from a series of more than 40 models, which single model will produce the best results for each work type being forecasted. NICE has also included machine learning in its scheduling processes which are discussed at length in the white paper.
There’s never been a more urgent need for comprehensive security and surveillance solutions. GeoVision Inc. has built its business on helping meet this need, providing digital and networked video surveillance solutions to customers in 110 countries. To succeed in its highly competitive and fast-changing industry, GeoVision must always be on the lookout for ways to give its customers leading-edge performance. Find out how GeoVision is working closely with Intel to maximize the performance of the hardware using the tools in Intel® System Studio, a comprehensive development tool suite to optimize the computer vision and deep learning workloads.
o The growing video surveillance market is driving demand for advanced video analysis technologies. Businesses and organizations from all vertical sectors are looking to leverage the benefits of enhanced detection accuracy and flexibility provided by deep learning to solve their security, safety, and operations challenges. Discover how Agent Vi’s innoVi* leverages cutting-edge deep learning technology to transform the hundreds, or even thousands, of cameras deployed across a city into smart video devices, contributing to the city’s ability to improve security, safety, and incident response citywide.
Have you ever wished for an army of clones to do all your thankless
tasks and chores? Well, that fantasy is becoming a reality—at least
on the Internet. And while they may not be actual clones, bots have
begun doing lots of digital dirty work.
Managing your relationship with bots—good and bad—has become an inherent part of doing business in a
connected world. With more than half of online traffic initiated by autonomous programs, it’s clear that bots
are a driving force of technological change, and they’re here to stay.
As bot technology, machine learning, and AI continue to evolve, so will the threats they pose. And while
some bots are good, many are malicious—and the cybercriminals behind them are targeting your apps.
Preparing your organization to deal with the impact of bots on your business is essential to developing a
sustainable strategy that will enable you to grow as you adapt to the new bot-enabled world.
AI will transform the workplace in ways we’re still trying to imagine. What skills and capabilities will your organisation need to survive? Read this report to find out ¬– with contributions from government, academics and the Big Innovation Centre.
Download the report to discover:
• how AI will change the way economies, societies and businesses operate
• how AI will change the skills your workforce needs in the 21st century
• what AI means for the way we learn
• how AI will change the role of the HR function.
What impact will the cloud-enabled workplace have on your cybersecurity strategy? This year’s research shows that organisations are navigating a myriad of both old and new cybersecurity challenges to bring the cloud into scope.
Read this to discover:
• how growing cloud dependency has created distinctive challenges around cyber security
• what the biggest cyber challenges are for organisations in this context
• how intelligent automation and machine learning is being used to overcome operational obstacles hampering cloud security
• a set of cybersecurity considerations for modern IT environments.
High-volume administrative tasks are a feature of every business. We helped a global bank develop a machine learning algorithm to help with the task of reviewing over 100,000 ‘sanctions alerts’ every day.
Read this story to find out:
• what other benefits AI can deliver beyond cost savings
• how AI tools achieve greater accuracy than human reviewers
• what it takes to apply AI and Machine Learning successfully in a regulated sector.
New Techniques That Will Drive Revenue in 2019
If you’re ready to move beyond simple calculations and realize the vast potential of data driven selling, you’re ready to explore the next generation of SPM platforms.
Download the report to learn how the modern technologies like Artificial Intelligence and Machine Learning, can give your sales reps a roadmap to better performance and give sales management insights that will enable them to achieve more profitable sales.
Did you know that organizations with advanced finance teams are more likely to have a compelling digital customer experience? The driver behind this trend? A digital, customer-first way of working with greater investment in talent, innovation, and advanced technologies such as artificial intelligence (AI) and machine learning (ML).
While finance has long taken advantage of technology to help drive productivity and collaboration, the goalposts have recently moved. Today’s organizations must adopt an agile finance operating model— powered by emerging digital technologies and skillsets—to better support the demands of an economy driven by continuous innovation.
Digital disruption, economic instability, political upheavals and skills shortages have all at some point in the past 24 months been blamed for business failure, or at the very least, lost profitability and earnings.
It’s perhaps not a huge surprise that a Gartner CEO survey on business priorities revealed that digital business is a top priority for next year. Survey respondents were asked whether they have a management initiative or transformation program to make their business more digital. The majority (62 percent) said they did. Of those organisations, 54 percent said that their digital business objective is transformational while 46 percent said the objective of the initiative is optimisation.*
So, for businesses it’s a case of learning to evolve and be agile, to use technology to help compete more efficiently and not fall victim to inertia. As businesses become increasingly dependent on the insights from data analytics and face-up to competition fuelled by the 24/7 society of in
Published By: DataCore
Published Date: Apr 23, 2019
The emphasis on fast flash technology concentrates much attention on hot, frequently accessed data. However, budget pressures preclude consuming such premium-priced capacity when the access frequency diminishes. Yet many organizations do just that, unable to migrate effectively to lower cost secondary storage on a regular basis.
In this white paper, explore:
• How the relative proportion of hot, warm, and cooler data changes over time
• New machine learning (ML) techniques that sense the cooling temperature of data throughout its half-life
• The role of artificial intelligence (AI) in migrating data to the most cost-effective tier.
Watch this webinar to learn how Slalom helped Veripad enhance the accuracy of their machine learning models using AWS services. Together they helped health professionals detect fraudulent medications more accurately than the human eye.
Common daily media broadcaster tasks such as ad verification are slow and costly. Done manually, they may also introduce inefficiencies that can interfere with transparency and payment accountability—and impact your bottom line. Meanwhile, recent and archived media lies idle when you could repurpose it to increase brand exposure and generate revenue.
Learn how Veritone, Inc. used its aiWARE Operating System, building on Amazon Web Services (AWS), to help Westwood One, Inc., a large audio broadcasting network in the United States, develop Artificial Intelligence (AI) and Machine Learning (ML) solutions designed for ad verification and monetizing archived media.
Download our webinar to learn how you can
Automate ad verification and reporting tasks.
Enhance archive content to make media searchable and reusable.
Use AI and ML in the cloud for near real-time media intelligence.
Start applying machine learning tools.
Trupanion, a Seattle-based medical insurance provider for cats and dogs, needed to find data insights quickly. With only 1% of pet owners insured, the process of evaluating a claim to approve or deny payment was manual and time-consuming. Building accurate predictive models for decision-making required manpower, time, and technology that the small company simply did not have.
DataRobot Cloud, built on AWS, helped Trupanion create an automated method for building data models using machine learning that reduced the time required to process claims from minutes to seconds. Join our webinar to hear how Trupanion transformed itself into an AI-driven organization, with robust data analysis and data science project prototyping that empowered the company to make better decisions and optimize business processes in less time and at a reduced cost.
Join our webinar to learn:
Why you don’t need to be an expert in data science to create accurate predictive models.
How you can build and deploy pr
Join us to learn why Human-in-the-Loop training data should be powering your machine learning (ML) projects and how to make it happen. If you’re curious about what human-in-the-loop machine learning actually looks like, join Figure Eight CTO Robert Munro and AWS machine learning experts to learn how to effectively incorporate active learning and human-in-the-loop practices in your ML projects to achieve better results.
When to use human-in-the-loop as an effective strategy for machine learning projects
How to set up an effective interface to get the most out of human intelligence
How to ensure high-quality, accurate data sets
When: Available On Demand (please register to view)
Who Should Attend: IT leaders and professionals, line-of-business managers, business decision makers, data scientists, developers, and other experts interested in implementing AI/ML on the cloud are encouraged to attend this webinar.
AWS Speaker: Chris Burns, Solutions Architect
Figure Eight Spea
Artificial intelligence (AI) and machine learning (ML) are emerging technologies that will transform organizations faster than ever before. In the digital transformation era, success will be based on using analytics to discover the insights locked in the massive volume of data being generated today. Historically, these insights were discovered through manually intensive data analytics—but the amount of data continues to grow, as does the complexity of data. AI and ML are the latest tools for data scientists, enabling them to refine the data into value faster.
As digital business evolves, however, we’re finding that the best form of security and enablement will likely remove any real responsibility from users. They will not be required to carry tokens, recall passwords or execute on any security routines. Leveraging machine learning, artificial intelligence, device identity and other technologies will make security stronger, yet far more transparent. From a security standpoint, this will lead to better outcomes for enterprises in terms of breach prevention and data protection. Just as important, however, it will enable authorized users in new ways. They will be able to access the networks, data and collaboration tools they need without friction, saving time and frustration. More time drives increased employee productivity and frictionless access to critical data leads to business agility. Leveraging cloud, mobile and Internet of Things (IoT) infrastructures, enterprises will be able to transform key metrics such as productivity, profitabilit
The bar for success is rising in higher education. University leaders and IT administrators are aware of the compelling benefits of digital transformation overall—and artificial intelligence (AI) in particular. AI can amplify human capabilities by using machine learning, or deep learning, to convert the fast-growing and plentiful sources of data about all aspects of a university into actionable insights that drive better decisions. But when planning a transformational strategy, these leaders must prioritize operational continuity. It’s critical to protect the everyday activities of learning, research, and administration that rely on the IT infrastructure to consistently deliver data to its applications.
Artificial Intelligence (AI) has already begun to improve targeting, segmentation, media buying and planning in the advertising industry. AI algorithms can extract complex patterns from vast numbers of data points, and in so doing, are able to self-correct and learn patterns. The revenue potential that improved personalization, segmentation and targeting that AI provides to marketers is huge.
At HERE Technologies, we are placing AI and machine learning at the center of our products and services. We see the opportunity in automated machine learning to enrich the targeting and effectiveness of mobile advertising campaigns in real time. But the outcome of implementing such technology depends on the quality of data being fed into it from the outset. AI wouldn’t be as helpful if it’s being used alongside questionable location data or audience data.
HERE’s location data provides a strong thread that can be woven throughout every stage of the media buying process, offering more context and
Published By: Cisco EMEA
Published Date: Nov 13, 2017
Big data and analytics is a rapidly expanding field of information technology. Big data incorporates technologies and practices designed to support the collection, storage, and management of a wide variety of data types that are produced at ever increasing rates. Analytics combine statistics, machine learning, and data preprocessing in order to extract valuable information and insights from big data.