Name: RIDE Containerized Data Science IDE server For Enterprise
Start: 2017-12-14T16:00:00Z
End: 2017-12-14T16:00:44.000Z
Location: BrightTALK
Rating: 0

This channel covers the advent of artificial intelligence in business and society. Join the discussion with webinars and videos covering everything from neural networks, to computer vision and NLP, to machine learning and AI application in the real world.

As organizations are looking for ways to stay on top of an evolving threatscape, many are
looking towards AI to enhance their security strategies and fend off cyber attacks before they
happen. In the 2022 CIO and Technology Executive Survey by Gartner, 66% of respondents
reported that they expected to increase cyber and information security investments for the
next year. More than half of respondents reported that they planned to heavily invest in
business intelligence and data analytics.

However some security leaders are cautious about adding artificial intelligence into their
security arsenal. Despite rapid advancements in AI, these solutions can also come with their
own unique set of drawbacks. Some skeptics say that AI technology is still immature and
that there may be simpler, more cost-effective solutions. With all the interest surrounding AI
in cybersecurity, it’s important for organisations to establish realistic expectations.

Join this panel to learn more about:
- The current state of AI in security
- What CISOs and their teams should keep in mind about AI
- How AI impacts your workforce strategy
- And more!

Speakers:
- Dan Lohrmann, Field CISO at Presidio
- Earl Duby, CISO at Lear Corporation
- Aidan Walden, Director, Public Cloud Architecture & Engineering at Fortinet
- Warsamé Ahmed, Co-Founder & CEO at BR[AI|YT.ai

Using AI in Cyber Security: Boon or Bust?

By most estimates, fewer than 20% of machine learning projects make it past the initial pilot stage. In order to succeed, data scientists must work closely with developers and IT operations teams to plan for future needs and model success to help justify costs. This webcast will explore the biggest challenges to implementing a machine learning project, where teams get tripped up and how to avoid these roadblocks. It will also cover advice for IT leaders about how to scale and support a machine learning project as it grows.

How to Get Your Machine Learning Project Past the Pilot Stage

AI is not a one-size-fits-all technology; each AI project is customized to solve a specific business problem, with machine learning models. These models rely on data and algorithms to address a project’s needs. Learn the seven steps to building an effective machine learning model in this five-minute rapid session that gets you up to speed without disrupting your day.

Learn in Less Than 5 Minutes: 7 Steps to Build a Machine Learning Model

Credit unions that seek digital solutions to improve overall operating efficiency and member satisfaction will hear how a large credit union successfully implemented process automation to achieve significant business goals. We will discuss the lessons learned, as well as best and worst decisions made along the way.  Join Ashwin Krishnamurthi, a Process and Automation Expert at a large credit union and Karen Diamond, VP of Enterprise Accounts at pureIntegration for this fascinating discussion.

Digitally Evolving Credit Unions: A Business Case for Automation

Enterprise Analytics are currently often the purview of a narrow group of data scientists and trained analysts, with business users bottlenecked by those experts, or left to rely on static BI dashboards that are too slow for data exploration, but the economy increasingly demands that front-line business decision makers need real-time self-service analytics to make decisions faster and improve the customer experience. 

In this talk, Peter Kacandes, a Sr. Technical Product Marketing Lead at Imply.io, will discuss:

The origins of this problem in the architecture of the current analytics tech stack, and the emerging hot analytics technology stack, which opens up self-service analytics on real-time big data to hundreds or thousands of business people at a company.  

How a real-time data store that is 10-100X faster than data warehouses or data lake query engines, combined with an intuitive and high-speed UI, can empower untrained “citizen analysts” such as marketing, product, and operations managers, to make myriad daily decisions faster and data-driven. 

The learnings of well-known companies who have implemented hot analytics for use cases such as user behavior, network, application and service performance monitoring, and real-time fraud detection.

Putting Big Data Self-Service Analytics in the hands of Business People

Far too many companies struggle with data-related issues such as integrating online and offline data, a lack of collaboration between teams, low data accuracy, and poor data accessibility. You already know that creating a single source of truth for your customer data is the first step to good customer data management. Having your data all in one place provides a single data set that everyone in the company can use. This is the key to making your tools and teams work better together. A Customer Data Platform (CDP) can do all this and more. CDPs are designed to normalize large amounts of data across a wide variety of systems gathering data on the same individual in very different ways. 

Have you heard of a CDP before and the value it brings?

In this webinar, you’ll learn:

-What is a CDP?
-What are the advantages of a CDP over a data lake?
-How can a CDP enable better business intelligence reporting?
-How CDPs can be leveraged with use cases designed for marketing, product and operations teams?
-And so much more!

About the presenter: 
Aimee applies her vast analytics, project management, and leadership experience to help our client teams deliver the best analytics consulting solutions possible. Specifically, she works closely with clients to develop reports and analyze data, identify trends and relationships between different types of data, draw appropriate conclusions, and translate findings into marketing and sales strategies that drive revenue. 

Aimee has more than 10 years of experience with web analytics solutions, including Adobe Analytics and Google Analytics, applying data-driven methodologies to business, product, sales, and growth initiatives. In addition to her strong analytics consulting expertise, she is a strategic thinker with the ability to influence decision making and a strong leader who ensures on-time, on-budget project completion.

Customer Experience Focused Business Intelligence - Better with a CDP

Today’s enterprises are embracing a deep and drastic transformation and modernization to deliver their customers 100% business uptime while being nimble, simple and agile from an operational standpoint. While micro-service architectures, hyper-automation, and cloud are the de-facto agreed technologies driving this massive transformation, their impact to IT and Cloud operations cannot be neglected. 

A software glitch in a micro-service functional component propagates fast and impacts many business services at the same time. Datacenter-Cloud borderless infrastructure increases the surface of failures, and prolongs the time to detect, triage and remediate the problem.

IT and Cloud operations need to refresh their decade-old tools, systems and processes to overcome todays challenges. Alert fatigue, difficulty in identifying the root cause of the problem, little to no time to analyze, inefficient communication, poor collaboration & poor remediation processes are their daily pain-points.

In this talk, we will introduce AIOps and Self-healing Enterprise, a new technology paradigm designed to address todays remote working environments to improve business uptime and reduce operational pain points. The benefits of AI predictive intelligence, collaboration and automation in a turnkey, SaaS ready solution that automates the end-to-end IT/Cloud/Devops lifecycle – from early detection, root cause analysis to effective remediation. In doing so, AIOps drives higher business uptime, reduces resources required to manage, shorter the mean-time-to-resolution (MTTR) and drastic reduce the cost of ownership.

Presented by:

Muddu Sudhakar
CEO, Aisera
Twitter: @smuddu
Linkedin: https://www.linkedin.com/in/muddusudhakar/

and

MuckAI Girish
Chief Revenue Officer, Appnomic Systems
Twitter: @muckai 
Linkedin: https://www.linkedin.com/in/muckaigirish/

Autonomous Enterprise and the Rise of AIOps in Remote Working Environments

A fundamental need in various industries is to find underlying causal relations and use them to improve the business outlook of companies. All companies bar none would like to understand why their sales are declining, what leads customers to buy, how to improve employee motivation, where to allocate resources and what is the best competitive strategy. 

The knowledge of causal relations is essential in achieving these goals. However, in most analyses, scientists draw inferences from correlation. However, correlation is not causation, and such correlative inferences can often be disastrously incorrect. 

This talk covers the following:

- An insight into the data science of Causal Discovery
- How to generate causal hypotheses to determine root causes of operational situations
- How to conduct “natural experiments” to validate these hypotheses from a historical dataset
- Real-world case studies of the successful application of causal discovery in industry

About the speaker:
Vijay Nadkarni is Vice President Artificial Intelligence at Tech Mahindra, responsible for AI technology
and customer engagements across multiple verticals including automotive, manufacturing, aerospace,
healthcare, retail, semiconductor and others. Previously, Vijay was VP and global head of AI at Visteon,
responsible for AI across its product lines, notably autonomous driving and infotainment. A veteran of
Silicon Valley, Vijay has co-founded multiple startups in AI and cloud computing of which Veraz
Networks, a VoIP company, had a NASDAQ IPO, and another, Wellcore, was acquired.

The Use of Causal Discovery in Understanding the Root Causes of Business Trends

In honor of International Internal Audit Awareness Month (May 2020), come hear from Greg Jordan, Nationwide's Senior Vice President and Chief Audit Executive, Pat Shanahan, AVP Information Technology Audit Office, Internal Audit and Emigdio Zambada, Nationwide's IA Data Analytics Director, discuss how their department expanded the use of data & analytics by building a continuous auditing program in the cloud.  Partnering with Covail, they leveraged advanced analytics like AI and have provided education and resources to all of their auditors to enhance their data analytics skill set.

Continuous Audit - Achieve More Through Analytics

Artificial intelligence (AI) and machine learning (ML) have been having quite the impact on most industries in the last couple of years, but what about our own IT industry? In this webcast find out how the rise of machine learning has created a new type of demand on IT operations teams as well as how those same teams can utilize new insights and capabilities driven by machine learning. We will explore:
•The demand on infrastructure 
•Storage and data pipelines 
•The growing field of IT operations leveraging AI (aka AIOps)

After you watch the webcast, check out the Q&A blog at: https://bit.ly/3fsj45e

The Impact of Artificial Intelligence on Storage and IT

Join Artem Golubev, CEO of TestRigor and Aleksey Malyshev, Machine Learning Engineer at TestRigor as they discuss the current state of artificial intelligence from an engineering & business perspective.

What is AI for the enterprise truly capable of and how much of the conversation surrounding AI is just hype? Tune in to find out!

The State of Artificial Intelligence: Where Are We Now and Where Are We Headed?

In this webinar the audience will learn how Machine Learning and AI is being adopted in the real-world working with Google. 

Google uses 4000+ machine learning models to run everything from their search engine, to Gmail and much more. The same infrastructure is now being used across multiple industries like supply chain, retail, manufacturing, and health care, to solve a myriad of problems like:

- Improving the taste of beer
- Beating humans in forecast accuracy
- Driving delivery of fresher fruits and helping online retailers reduce inventory carrying costs by over 50% 
- and much, much more.

All this is being accomplished in ways that were never imagined before using machine learning and AI technology. 

In this webinar we will walk you through how customers of all sizes are going through this digital transformation and how these results signal a huge wave ahead for businesses worldwide.

Manju Devadas is CEO of Pluto7, a Google “Global Breakthrough Partner of the Year” finalist company focused on Machine Learning and AI. At Pluto7, Manju utilizes his 17+ years of experience in predictive analytics to transform business on Google Cloud Provider (GCP). He believes that the next 10 years will be the age of machines and companies like Google and Pluto7 are early adopters.

Business Transformation with Machine Learning and AI Use Cases on Google Cloud

Alexey Malanov joined Kaspersky Lab in 2004, where he began his work as a virus analyst. He has since been appointed Head of Kaspersky's Anti-Malware Team and in 2012, shifted his focus to analyzing technology trends and risks.

The threat posed by a Strong AI (artificial intelligence where the machine's intellectual capability is functionally equal to a human's) is well-considered in many science fiction films. But the invention of a Strong AI will take many years, so we can afford not to hurry with the study of "laws of robotics."

However, we are already facing growing concerns. The use of machine learning in various fields has shown that algorithms often make strange, discriminatory and difficult-to-understand decisions. Moreover, it has been clearly demonstrated that a person can cheat algorithms to achieve desired results.

Alexey addresses some of the looming issues surrounding the AI algorithms that are becoming a part of our daily lives, and will increasingly affect us and our decisions.

Ask the Malware Expert: Ethics in AI

With the increasingly connected world revolving around the revolution of internet and new technologies like mobiles, smartphones, and tablets, and with the wide usage of wireless technologies, the information security risks have increased. Both individuals and organizations are under regular attacks for commercial or non-commercial gains. The objectives of such attacks may be to take revenge, malign the reputation of a competitor organization, understand the strategies and sensitive information about the competitor, simply have fun of exploiting the vulnerabilities. Hence, the need to protect information assets and ensure information security receives adequate attention.

In this session, Dr. Umesh Rao Hodeghatta will discuss:
- How AI and Machine Learning can be applied in detecting, predicting and preventing cyber security / information security vulnerabilities
- The benefits of using Machine Learning and AI
- Tools available to perform the same.

Applying Machine Learning in Cyber Security

In this webinar the audience will learn how Machine Learning and AI is being adopted in the real-world working with Google. 

Google uses 4000+ machine learning models to run everything from their search engine, to Gmail and much more. The same infrastructure is now being used across multiple industries like supply chain, retail, manufacturing, and health care, to solve a myriad of problems like:

- Improving the taste of beer
- Beating humans in forecast accuracy
- Driving delivery of fresher fruits and helping online retailers reduce inventory carrying costs by over 50% 
- and much, much more.

All this is being accomplished in ways that were never imagined before using machine learning and AI technology. 

In this webinar we will walk you through how customers of all sizes are going through this digital transformation and how these results signal a huge wave ahead for businesses worldwide.

Manju Devadas is CEO of Pluto7, a Google “Global Breakthrough Partner of the Year” finalist company focused on Machine Learning and AI. At Pluto7, Manju utilizes his 17+ years of experience in predictive analytics to transform business on Google Cloud Provider (GCP). He believes that the next 10 years will be the age of machines and companies like Google and Pluto7 are early adopters.

Join BrightTALK's BI & Analytics group on LinkedIn: http://bit.ly/2PJlPHm

In this webinar, we will describe a number of use cases spanning Artificial Intelligence, Machine Learning, Augmented reality and Virtual Reality that are propelling enterprises to realize significant value, increase efficiencies and provide unparalleled customer and employee experiences. 

With rampant advances in deep learning technologies, access to large volumes of data, massive innovations in AR/VR devices and software, we are in a unique position, today, to leverage them for a plethora of use cases that are addressing real-life scenarios positively. They include customer service automation, employee productivity, training, visualization and remote troubleshooting, inspection and documentation.

About the Speakers:

With over 22 years of start-up and large-company experience in the high-tech industry, Girish is the CEO of Muck.AI, helping start-ups and enterprises realize the benefits of AI/ML, Cloud, Security and Networking. Girish served as the VP of Business Development & Strategy at Passage AI (www.passage.ai), a Silicon Valley startup developing conversational chatbot solutions using deep learning, natural language processing and artificial intelligence. He worked with Juniper Networks, Reliance Jio, Entropic Communications, ARRIS Group and SBC Labs, helping bring security, cloud, broadband and wireless communications solutions to market. Girish serves as an advisor and mentor to a number of start-ups.

DP Prakash is presently the worldwide leader in the CIO office of Global Foundries for Innovation in enterprise productivity through AI ML AR VR applications. In 2018, DP Prakash and his Team have created world leading solutions in AI ML and AR VR including the ability to visualize walking inside chips made with nano technology.

AI/ML and AR/VR Applications in Real Life

Enterprise AI is a target state where every business process is AI-augmented and every employee is an AI beneficiary. But is that really attainable? And, if so, what is the path to get there? In this talk, Larry Orimoloye, Sales Engineer at Dataiku, will share learnings from the field, describing how companies of different sizes and across different sectors have begun this journey. Some are farther along than others, and by making the right decisions now and avoiding stumbling blocks, you can supercharge your quest to this AI-fueled future.

Larry Orimoloye is an applied statistician with strong expertise in driving ROI from all analytics investment. He possesses a solid grasp and understanding of analytics life cycle (end-to-end process). Larry has acted as strategic adviser and domain expert to wide range of clients including Apple, EE(T-Mobile/Orange), Sky, ExxonMobil, FedEx among others.

The Path to Enterprise AI: Tales from the Field

RIDE is an all-in-one, multi-user, multi-tenant, secure and scalable platform for developing and sharing Data Science and Analytics, Machine Learning (ML) and Artificial Intelligence (AI) solutions in R, Python and SQL. 

RIDE supports developing in notebooks, editor, RMarkdown, shiny app, Bokeh and other frameworks. Supported by R-Brain’s optimized kernels, R and Python 3 have full language support, IntelliSense, debugger and data view. Autocomplete and content assistant are available for SQL and Python 2 kernels. Spark (standalone) and Tesnsorflow images are also provided.

Using Docker in managing workspaces, this platform provides an enhanced secure and stable development environment for users with a powerful admin control for controlling resources and level of access including memory usage, CPU usage, and Idle time. 

The latest stable version of IDE is always available for all users without any need of upgrading or additional DevOps work. R-Brain also delivers customized development environment for organizations who are able to set up their own Docker registry to use their customized images.

The RIDE Platform is a turnkey solution that increases efficiency in your data science projects by enabling data science teams to work collaboratively without a need to switch between tools. Explore and visualize data, share analyses, all in one IDE with root access, connection to git repositories and databases.

RIDE Containerized Data Science IDE server For Enterprise

#IDE

#machine learning

#artificial intelligence

#cloud

#data science

#platform

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RIDE Containerized Data Science IDE server For Enterprise

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