Published By: Red Hat
Published Date: Jun 26, 2019
When any organization starts planning for cloud-native applications, it is important to consider
the entire time span: from selecting a development platform until an application is truly production-grade and ready for delivery in the cloud. It can be a long journey, with many decisions
along the way that can help or hinder progress.
For example, at the beginning of a move to cloud-native development, it is easy for inefficiencies
to occur if developers begin selecting tools and frameworks before they know where the application will be deployed. While enterprise developers want choice of runtimes, frameworks, and
languages, organizations need standards that address the entire application life cycle in order
to reduce operational costs, decrease risks, and meet compliance requirements. Organizations
also want to avoid lock-in, whether it is to a single provider of cloud infrastructure or the latest
In addition, given the steep learning curve in cloud development, con
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
LOOK TO RELEVANT USE CASES FOR YOUR BUSINESS. While use cases vary across industries, the most common ones fall into these categories and are usually associated with the listed neural network:
• Image classification or object detection: convolutional neural network (CNN) • Time-series predictions: long short-term memory (LSTM) • Natural language processing: recurrent neural network (RNN) • Unlabeled data classification and data labeling: autoencoder (AE) • Anomaly detection: autoencoder (AE) • Recommender systems: multilayer perceptron (MLP)
Work with your deep learning talent or consultants to identify which use cases best match your organization and desired solutions. Then recreate a successful, already proven method.
How can you open your analytics program to all
types of programming languages and all levels of
users? And how can you ensure consistency across
your models and your resulting actions no matter
where they initiate in the company?
With today’s analytics technologies, the conversation
about open analytics and commerical analytics is no
longer an either/or discussion. You can now combine
the benefits of SAS and open source analytics
technology systems within your organization.
As we think about the entire analytics life cycle, it’s
important to consider data preparation, deployment,
performance, scalability and governance, in addition
to algorithms. Within that cycle, there’s a role for
open source and commercial analytics.
For example, machine learning algorithms can
be developed in SAS or Python, then deployed in
real-time data streams within SAS Event Stream
Processing, while also integrating with open systems
through Java and C APIs, RESTful web services,
Apache Kafka, HDFS and more.
Advances in deep neural networks have ignited a new wave of algorithms and tools for data scientists to tap into their data with artificial intelligence (AI). With improved algorithms, larger data sets, and frameworks such as TensorFlow, data scientists are tackling new use cases like autonomous driving vehicles and natural language processing. Read this technical white paper to learn reasons for and benefits of an end-to-end training system. It also shows performance benchmarks based on a system that combines the NVIDIA® DGX-1™, a multi-GPU server purpose-built for deep learning applications and FlashBlade, a scale-out, high performance, dynamic data hub for the entire AI data pipeline.
Language training is a crowd favorite in any global company's training mix. But how valuable is it to the business? How does an organization convert the time spent conversing with virtual tutors or playing listening games into actual business value? The Rosetta Stone Business Impact Survey answered these and other questions by surveying thousands of users of its business products. This e-book shares the key results to help human resource, learning and development, and business line leaders better understand how language impacts business.
Published By: Microsoft
Published Date: Jul 20, 2018
Although AI research has been ongoing for decades, the past few years have seen
a leap in practical innovations, catalyzed by vast amounts of digital data, online
services, and enormous computing power. As a result, technologies such as
natural-language understanding, sentiment analysis, speech recognition, image
understanding, and machine learning have become accurate enough to power
applications across a broad range of industries.
Recognizing the shift to a subscription business model required real-time customer support, Autodesk turned to IBM technology to enhance its customer experience.
Using Watson Assistant, Autodesk developed a virtual agent to interact with customers, applying natural language processing (NLP) and deep learning techniques to recognize and extract the intent, context and meaning behind inquiries. Quickly resolving easy customer concerns, Watson Assistant is supporting 100,000 conversations per month, with response times 99% faster than before and leading to a 10-point increase in customer satisfaction levels for Autodesk.
Find out how Watson Assistant can accelerate your customer support experience.
Click here to find out more about how embedding IBM technologies can accelerate your solutions’ time to market.
"The appearance of your reports and dashboards – the actual visual appearance of your data analysis -- is important. An ugly or confusing report may be dismissed, even though it contains valuable insights about your data. Cognos Analytics has a long track record of high quality analytic insight, and now, we added a lot of new capabilities designed to help even novice users quickly and easily produce great-looking and consumable reports you can trust.
Watch this webinar to learn:
• How you can more effectively communicate with data.
• What constitutes an intuitive and highly navigable report
• How take advantage of some of the new capabilities in Cognos Analytics to create reports that are more compelling and understandable in less time.
• Some of the new and exciting capabilities coming to Cognos Analytics in 2018 (hint: more intelligent capabilities with enhancements to Natural Language Processing, data discovery and Machine Learning)."
Massive amounts of data are being created driven by
billions of sensors all around us such as cameras, smart
phones, cars as well as the large amounts of data across
enterprises, education systems and organizations. In
the age of big data, artificial intelligence (AI), machine
learning and deep learning deliver unprecedented
insights in the massive amounts of data.
Amazon CEO Jeff Bezos spoke about the potential of
artificial intelligence and machine learning at the 2017
Internet Association‘s annual gala in Washington, D.C.,
“It is a renaissance, it is a golden age,” Bezos said.
“We are solving problems with machine learning and
artificial intelligence that were in the realm of science
fiction for the last several decades. Natural language
understanding, machine vision problems, it really is
an amazing renaissance.” Machine learning and AI is a
horizontal enabling layer. It will empower and improve
every business, every government organization, every
When augmenting the benefits package
for your organization, it’s natural to focus
on traditional perks that employees have come to
expect: PTO, health insurance, and maybe a tuition
assistance credit here or there. But if you’re looking
for creative and effective ways to stimulate
employee engagement while also driving business
results, you’ll want to consider the powerful impact
of offering language-learning opportunities.
Why language learning? It offers immediate and
long-term benefits to both employees and employers.
Research shows that organizations that offer access
to language learning see an increase in employee
engagement factors like loyalty, morale, and
productivity, which in turn boosts business performance
factors such as customer satisfaction
and internal communications.
Where’s the connection? And how can you reproduce
these benefits within your organization? This
playbook offers a deeper look at why language
learning has such a positive influence on employee
Published By: LogMeIn
Published Date: Feb 27, 2018
Most customer engagement solutions on the market require complex data analysis and months of implementation before you start seeing results. But Bold360 ai uses Natural Language Understanding to start learning your customers’ needs from the very first interaction. Its smart routing capability directs customers to the best resource available, and captures data in an intuitive dashboard. Start seeing results now with Bold360 ai.
With global opportunities on the rise,. having a multilingual workforce has become a critical market success factor. Language proficiency and awareness of a market's culture, local customs, and business traditions conveys respect for customers and colleagues, which leads to greater trust and improved business results.
Businesses are providing language-learning resources that prepare employees to engage in these markets. Forbes Insights and Rosetta Stone surveyed 200+ executives globally to understand the impact of language training on companies and employees. Read this guide to learn the key themes and data from the report.
Language training is a crowd favorite in any global company's training mix. But how valuable is it to the business?
The 2016 Rosetta Stone Business Impact Survey answered this and other key questions by surveying thousands of users of its business products. This e-book shares the key results to help human resource, learning and development, and business line leaders better understand how language impacts business.
There's a need for better language learning, and a strong case for it.
87% of business executives say their business relies on more than one critical languages. Those that invest in learning outperform the market by more than 45%. Learn how improvements in your language programs provide tangible business returns.
When augmenting the benefits package for your organization, it’s natural to focus on traditional perks that employees have come to
expect: PTO, health insurance, and maybe a tuition assistance credit here or there. But if you’re looking for creative and effective ways to stimulate employee engagement while also driving business results, you’ll want to consider the powerful impact of offering language-learning opportunities.
Where’s the connection? And how can you reproduce these benefits within your organization? This playbook offers a deeper look at why language learning has such a positive influence on employee engagement and business performance, as well as step-by-step instructions for implementing a language-learning program in your organization.
In this informational webinar, we focus on identifying funding streams for K-12 ELL and world language programs. Hear perspectives and insights on funding streams in K-12 education from funding expert David DeSchryver, Senior Vice President of Education Policy at Whiteboard Advisors.
ELLs are a diverse group of about ?ve million students in the U.S. who speak a primary language other than English and are not yet pro?cient in English. To catch and keep up with their native English speaking peers, ELLs need more instructional time and specialized instruction, including specially designed materials and advanced educational tools to accelerate their learning.
Well utilized state-of-the-art technology tools can transform not only learning but academic success itself for ELLs and their families.
To read the complete white paper and learn more about Rosetta Stone, go to k12hub.rosettastone.com.
Designing the most comprehensive language program involves proven and cost-effective technology. Rosetta Stone's Language Learning Suite for K-12 has interactive solutions that complement any language curriculum. Take a look at the infographic to discover how the rise of technology enhances instruction and encourages learning.
Technology plays an increasingly significant role in how we help language students develop the skills they need to be successful in today's competitive, global workplace. The benefits of integrating technology into the classroom can be seen throughout the learning experience.
In October 2013, Getting Smart partnered with Rosetta Stone to release a report called “The Next Generation of
World Language Learning.” The goal of the report was to create a vision for world language learning that acknowledged
its role in global competency and to frame the vision inside broader shifts to personalized learning and blended
instruction. Pointing to the potential of educational technology, we advocated for accessible, high-quality world
language instruction for all students—from elementary through high school.