Enabling Remote Diagnostics for IoT Devices

Implementing AI applications based on machine learning is a significant topic for organizations embracing digital transformation. By 2020, 30% of CIOs will include AI in their top five investment priorities according to Gartner’s Top 10 Strategic Technology Trends for 2018: Intelligent Apps and Analytics. But to deliver on the AI promise, organizations need to generate good quality data to train the algorithms. Failure to do so will result in the following scenario: "When you automate a mess, you get an automated mess."

This webinar covers:

- An introduction to machine learning use cases and challenges provided by Kirk Borne, Principal Data Scientist at Booz Allen Hamilton and top data science and big data influencer.
- How to achieve good data quality based on harmonized semantic metadata presented by Andreas Blumauer, CEO and co-founder of Semantic Web Company and a pioneer in the application of semantic web standards for enterprise data integration.
- How to apply a combined approach when semantic knowledge models and machine learning build the basis of your cognitive computing. (See Attachment: The Knowledge Graph as the Default Data Model for Machine Learning)
- Why a combination of machine and human computation approaches is required, not only from an ethical but also from a technical perspective.

In this webinar, Metadata.io CEO Gil Allouche will talk about the different ways AI is being used by marketers. From analyzing data to orchestrating new marketing campaigns, AI is powering marketing activities in new and exciting ways and affecting interactions throughout the entire customer lifecycle. As an example of how AI can have a tremendous impact on marketing practices, Gil will focus on its role in lead generation. Webinar attendees will learn:

- What Machine Learning is in relation to AI and how it connects your data to find patterns
- Examples of how machine learning can identify target audiences, including the 20 percent that creates 80 percent of your revenue
- How AI technology can help marketers prioritize their budgets to focus on the most effective programs
- Starting with small, iterative uses of AI in marketing can be the most effective way to understand what will yield the most ROI

Gil Allouche founded Metadata.io to make demand generation easy for non-technical marketers. The Metadata.io platform and AI Operator evolved from Gil's experiences hacking various marketing and CRM systems to get the solutions he needed.

AI is a powerful tool, but often companies get more excited about their technology than in the customer value they’re creating. Geordie Kaytes will share a framework for building customer-centered AI products. You’ll learn how to craft a far-reaching vision and strategy centered around customer needs and balance that vision with the day-to-day needs of your company.

Learn a framework for creating and communicating a vision that describes the overall direction of your AI product, a defined product strategy, a cross-functional roadmap aligned with the strategy, and a list of metrics that track progress towards the strategy

About the Speaker: Geordie Kaytes is the director of UX strategy for Boston-area UI/UX studio Fresh Tilled Soil and a partner at Heroic (https://www.heroicteam.com), a design leadership coaching firm that helps growing companies scale their digital product capabilities. A digital product design leader with deep experience in design process transformation and cross-functional expertise in design, strategy, and technology, Geordie has helped companies in a broad range of industries develop a 360-degree view of their product design processes. Previously, he did his obligatory tour of duty in management consulting. He holds a BA from Yale in political science. He is a coauthor of the Medium publication Radical Product.

As we move to the conversational UI and take advantage of NLP and AI in general, we change the way we interact with technology dramatically. The standard GUI is many times fully eliminated, leading to novel challenges in UX. Tasks are removed from the user’s oversight with invisible or seamless software, and the output is not always as expected. But sometimes that output is correct within the parameters given and simply perceived as an error.

Dennis will talk through where x.ai has encountered error perception issues as we seek to develop frictionless software, how we thought about the problem and the communication strategies we’re exploring to resolve it.

We are seeing a sea change in networking. SDN has enabled improvements in network telemetry and analytics.

In this presentation, I will talk about the current challenges that are out there and how the technology change is helping us to improve the overall network telemetry. Furthermore, I will share how deep learning techniques are being used in this field. Please join this webinar to understand how the field of network telemetry is changing.

This Webinar explains how Big Data, Artificial Intelligence, and Machine Learning is going to transform the future Banking Industry. Banks which can manage this Big Data evolution successfully will survive and thrive, and give a more holistic and personalized customer service, thereby increasing their revenues tremendously.

The key takeaway from this Webinar is that “Right information at the right place and the right time is going to be the real money and will shape the future of Banking Industry.”

Tariq is a Fintech Expert, writer, and thinker based in Toronto Canada and is currently working on an initiative to disrupt the conventional Banking Industry with “Big Data Predictive Analytics Model” of his startup.

In this webinar, Mustafa Kabul, Principal Data Scientist, SAS, will provide an introduction to deep learning and its applications.

Mustafa is a data scientist in the Artificial Intelligence and Machine Learning R&D at SAS, where he leads innovative projects for SAS’s next-generation AI-enabled analytics products, including applications of deep learning. His current focus is on applying deep reinforcement learning to operational problems in the CRM and IoT spaces. An operations research expert working at the interface of machine learning and optimization, previously, he developed distributed, large-scale integer optimization algorithms for marketing optimization problems. Ever the optimization enthusiast, Mustafa always looks into ways to improve the algorithms. Nowadays his favorites are the distributed stochastic gradient and online learning methods. Mustafa holds a PhD from the University of North Carolina at Chapel Hill, where his research focused on game theory models of supply chains selling to strategic customers.

Brought to you by the Vivit Automation & Cloud Builders Special Interest (SIG) Group.

Attend this webinar to receive a live demonstration of public cloud service brokering, aggregation and governance using the Micro Focus Hybrid Cloud Management solution. HCM allows IT to easily aggregate public cloud resources into an end-user catalog, while providing governance and analytics to ensure business unit consumption is visible and within budget. In addition, learn how improved control of public cloud spending can help you start building a strong business case for cloud management.

Cloud Aggregation & Brokering
- Cloud service aggregation to quickly aggregate hybrid cloud services and publish offerings in catalog
- Self-service web portal access to catalog services for end users to consume services

Hybrid Cloud Governance
- Get visibility into IT cloud costs with show-back reporting for LOBs/organizations
- Policy-based budget quota management to proactively track cloud costs and notify on quota overages

This webinar is part of BrightTALK's Founders Spotlight series, featuring fearless entrepreneurs and inspiring founders.

In this episode, Eva Murray & Andy Kriebel, Founders of Makeover Monday, will share their story of how they started the social data project, Makeover Monday, the challenges and successes they encountered along the way and how they overcame them.

This will be an interactive Q&A session and an excellent opportunity for entrepreneurs or professionals to have their questions answered.

This talk tells the story of implementation and optimization of a sparse logistic regression algorithm in spark. I would like to share the lessons I learned and the steps I had to take to improve the speed of execution and convergence of my initial naive implementation. The message isn’t to convince the audience that logistic regression is great and my implementation is awesome, rather it will give details about how it works under the hood, and general tips for implementing an iterative parallel machine learning algorithm in spark.

The talk is structured as a sequence of “lessons learned” that are shown in form of code examples building on the initial naive implementation. The performance impact of each “lesson” on execution time and speed of convergence is measured on benchmark datasets.

You will see how to formulate logistic regression in a parallel setting, how to avoid data shuffles, when to use a custom partitioner, how to use the ‘aggregate’ and ‘treeAggregate’ functions, how momentum can accelerate the convergence of gradient descent, and much more. I will assume basic understanding of machine learning and some prior knowledge of spark. The code examples are written in scala, and the code will be made available for each step in the walkthrough.

Lorand is a data scientist working on risk management and fraud prevention for the payment processing system of Zalando, the leading fashion platform in Europe. Previously, Lorand has developed highly scalable low-latency machine learning algorithms for real-time bidding in online advertising.

You can do a lot with a Raspberry and ASF projects. From a tiny object
connected to the internet to a small server application. The presentation
will explain and demo the following:

- Raspberry as small server and captive portal using httpd/tomcat.
- Raspberry as a IoT Sensor collecting data and sending it to ActiveMQ.
- Raspberry as a Modbus supervisor controlling an Industruino
(Industrial Arduino) and connected to ActiveMQ.

The 10x growth of transaction volumes, 50x growth in data volumes and drive for real-time visibility and responsiveness over the last decade have pushed traditional technologies including databases beyond their limits. Your choices are either buy expensive hardware to accelerate the wrong architecture, or do what other companies have started to do and invest in technologies being used for modern hybrid transactional analytical applications (HTAP).

Learn some of the current best practices in building HTAP applications, and the differences between two of the more common technologies companies use: Apache® Cassandra™ and Apache® Ignite™. This session will cover:

- The requirements for real-time, high volume HTAP applications
- Architectural best practices, including how in-memory computing fits in and has eliminated tradeoffs between consistency, speed and scale
- A detailed comparison of Apache Ignite and GridGain® for HTAP applications

About the speaker: Denis Magda is the Director of Product Management at GridGain Systems, and Vice President of the Apache Ignite PMC. He is an expert in distributed systems and platforms who actively contributes to Apache Ignite and helps companies and individuals deploy it for mission-critical applications. You can be sure to come across Denis at conferences, workshop and other events sharing his knowledge about use case, best practices, and implementation tips and tricks on how to build efficient applications with in-memory data grids, distributed databases and in-memory computing platforms including Apache Ignite and GridGain.

Before joining GridGain and becoming a part of Apache Ignite community, Denis worked for Oracle where he led the Java ME Embedded Porting Team -- helping bring Java to IoT.

Attend this session to learn how to easily share state in-memory across multiple Spark jobs, either within the same application or between different Spark applications using an implementation of the Spark RDD abstraction provided in Apache Ignite. During the talk, attendees will learn in detail how IgniteRDD – an implementation of native Spark RDD and DataFrame APIs – shares the state of the RDD across other Spark jobs, applications and workers. Examples will show how IgniteRDD, with its advanced in-memory indexing capabilities, allows execution of SQL queries many times faster than native Spark RDDs or Data Frames.

Akmal Chaudhri has over 25 years experience in IT and has previously held roles as a developer, consultant, product strategist and technical trainer. He has worked for several blue-chip companies such as Reuters and IBM, and also the Big Data startups Hortonworks (Hadoop) and DataStax (Cassandra NoSQL Database). He holds a BSc (1st Class Hons.) in Computing and Information Systems, MSc in Business Systems Analysis and Design and a PhD in Computer Science. He is a Member of the British Computer Society (MBCS) and a Chartered IT Professional (CITP).

When monitoring an increasing number of machines, the infrastructure and tools need to be rethinked. A new tool, ExDeMon, for detecting anomalies and raising actions, has been developed to perform well on this growing infrastructure. Considerations of the development and implementation will be shared.

Daniel has been working at CERN for more than 3 years as Big Data developer, he has been implementing different tools for monitoring the computing infrastructure in the organisation.

As data analytics becomes more embedded within organizations, as an enterprise business practice, the methods and principles of agile processes must also be employed.

Agile includes DataOps, which refers to the tight coupling of data science model-building and model deployment. Agile can also refer to the rapid integration of new data sets into your big data environment for "zero-day" discovery, insights, and actionable intelligence.

The Data Lake is an advantageous approach to implementing an agile data environment, primarily because of its focus on "schema-on-read", thereby skipping the laborious, time-consuming, and fragile process of database modeling, refactoring, and re-indexing every time a new data set is ingested.

Another huge advantage of the data lake approach is the ability to annotate data sets and data granules with intelligent, searchable, reusable, flexible, user-generated, semantic, and contextual metatags. This tag layer makes your data "smart" -- and that makes your agile big data environment smart also!

With new technologies such as Hive LLAP or Spark SQL, do you still need a data warehouse or can you just put everything in a data lake and report off of that? No! In the presentation, James will discuss why you still need a relational data warehouse and how to use a data lake and an RDBMS data warehouse to get the best of both worlds.

James will go into detail on the characteristics of a data lake and its benefits and why you still need data governance tasks in a data lake. He'll also discuss using Hadoop as the data lake, data virtualization, and the need for OLAP in a big data solution, and he will put it all together by showing common big data architectures.

The hype surrounding AI has reached a fever pitch, but practical uses that are delivering concrete, practical business results are here, and it’s time to get real.

From taking over the routine requests for customer service agents, reducing costs, speeding up service, and boosting customer satisfaction, to reliably helping marketers deliver what a customer wants, when they want it and where, AI is popping up everywhere, and companies need to figure out where they stand, fast, to stay competitive.

Join this VB Live event, hosted by Forrester Senior Analyst Brandon Purcell and Kayak Chief Scientist Matthias Keller to learn more about how to identify the AI use cases that can transform your business, and how to get started, stat.

You’ll learn:
* What technologies fall under the AI umbrella
* How companies like Kayak use AI to understand customers and personalize experiences
* How to identify the right AI use case for your business
* Common challenges firms face when implementing AI
* Why AI’s time in the sun has finally come, and why it’s here to stay

Speakers:
* Brandon Purcell, Principal Analyst, Forrester
* Matthias Keller, Chief Scientist, Kayak
* Martine van der Lee, Director of Social Media, KLM
* Pradeep Elankumaran, CEO and Co-Founder of Farmstead
* Rachael Brownell, Moderator, VentureBeat

AI isn’t a nice-to-have any more, it’s a must-have. There’s a reason why corporate giants like Google, IBM, Yahoo, Intel, Apple, and Salesforce are competing to snatch up private AI companies. In the first quarter of 2017 alone, 37 AI companies were swallowed whole.

Companies aren’t just using these AI tools to enable existing marketing strategies; they’re taking those strategies to the next level, going beyond simple retention and delivering active engagement. AI technology offers companies unprecedented insight into customer behaviors, patterns, and beliefs, allowing you to seamlessly anticipate customer needs and serve up hyper-personalized, emotionally resonant campaigns where and when they’re most welcome.

2018 is the year to seize the AI advantage. To learn more about the technology you need, the opportunities it unlocks, and what it takes to get your ball in the game, don’t miss this VB Live event!

In this webinar, you'll learn:
* What’s new in AI for 2018 -- and what’s coming down the pike
* How businesses are using AI to drive results
* How to go beyond customer retention and power customer engagement

Speakers:
* Brian Gross, VP Digital Innovation, Aeromexico
* Dan Wulin, Director of Data Science, Wayfair
* Michael Healey, President, Yeoman Technology Group
* Rachael Brownell, Moderator, VentureBeat

Sponsored by Lytics

Watson is a computer system capable of answering questions posed in natural language. Watson was named after IBM's first CEO, Thomas J. Watson. The computer system was specifically developed to answer questions on the quiz show Jeopardy! (where it beat its human competitors) and was then used in commercial applications, the first of which was helping with lung cancer treatment.

NetApp is now using IBM Watson in Elio, a virtual support assistant that responds to queries in natural language. Elio is built using Watson’s cognitive computing capabilities. These enable Elio to analyze unstructured data by using natural language processing to understand grammar and context, understand complex questions, and evaluate all possible meanings to determine what is being asked. Elio then reasons and identifies the best answers to questions with help from experts who monitor the quality of answers and continue to train Elio on more subjects.

Elio and Watson represent an innovative and novel use of large quantities of unstructured data to help solve problems, on average, four times faster than traditional methods. Join us at this webcast, where we’ll discuss:

•The challenges of utilizing large quantities of valuable yet unstructured data
•How Watson and Elio continuously learn as more data arrives, and navigates an ever growing volume of technical information
•How Watson understands customer language and provides understandable responses

Learn how these new and exciting technologies are changing the way we look at and interact with large volumes of traditionally hard-to-analyze data.

After the webcast, check-out the Q&A blog http://www.sniacloud.com/?p=296