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.
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
"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)."
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.
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.
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.
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
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.
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
MarketBridge, a leading global provider of sales and marketing services, surveyed 493 senior and upper management-level business professionals in a variety of functional roles at leading international corporations to learn more about their company's language-learning needs. Please download this free white paper for more information.
Proving the value of language training to business can be challenging so we decided to take the guesswork out of it. We surveyed 56,000 of our business product users to gain key insights into how language training has changed their businesses. This infographic shares the key results to help human resource, learning and development, and business line leaders better understand how language impacts business.
Baldwin County Public Schools has built a curriculum that includes preparing students for the world of intelligent machines and empowering them to participate in the global community through language acquisition. The district sought a technology-based solution to provide students with the opportunity for long-term language learning.
Making your talent global-ready is key to your organization's future. A big part of global readiness lies in language and cultural skills. Knowledge of another language and culture builds bridges to customers and colleagues, and studies show that the ability to connect delivers measurable business impact. Building effective language and cultural learning programs is not difficult, but first HR must uncover the need - which often remains hidden from plain view.
A key element in the equation is communication, and if your employees can't communicate with their peers--or worse their customer--your business will fail. Explore this infographic to understand how Rosetta Stone Catalyst balances the equation.
Virtually all growth in the U.S. Labor force in the next four decades is expected to come from immigrants and their children. With this growth comes the need for manufacturers to enable their workforce to communicate more effectively. In order to increase productivity and reduce safety incidents, manufacturers are implementing English language learning programs.
The top clients of enterprise language learning companies consist of global companies that recognize the value of multilingual employees. While companies understand the necessity of language learning, there is room for improvement in incorporating language learning into corporate culture. This report looks at what companies are doing in the realm of language learning, to understand what best-in-class organizations are doing, and to provide businesses aspiring to be truly successful on a global stage with strategies for incorporating language learning into their business model.
Forbes Insights and Rosetta Stone surveyed 214 executives around the globe to find out if and how companies are training their employees to speak and work in more languages and what impact that training has on both the employees and the company. In addition, the narrative is rounded out with in-depth interviews with executives and experts.
Foodservice managers who have lingering doubts about investing in on-site
language training should consider this:
By 2027, over one million new jobs are expected to be added to the restaurant
According to the National Restaurant Association, “All of this means that
foreign-born employees will be increasingly important to the restaurant
industry’s ability to expand and create jobs in the years ahead.”38
For foodservice operators and managers who want to plan for their future now,
the question is obvious: What’s the best way to address these issues?
Rosetta Stone can provide some answers.
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.