The big five future IT trends
Internet of Things:
Assets Turn Into Applications
Machine Intelligence:
AI Could Replace 50M Professional Jobs
Distributed Ledgers:
Block chain is becoming mainstream
Sharing Economy:
We don’t owe anything anymore
Virtual and Augmented Reality:
Remote experience merge visual & digital world
The complexity, criticality, and real-time demands of the energy sector make it a prime candidate to benefit from applying machine learning. This session presents two case studies of machine learning automating decisions for energy companies.
For the largest windfarm operator in North America, machine learning applies predictive and prescriptive analytics to the complex task of scheduling crews for maintenance and repairs. Automating the scheduling process across multiple windfarm sites saves the operator millions in labor costs per year and frees managers and crews to do actual work. Machine learning also evaluates ever-changing conditions and automatically reschedules workers and tasks as necessary.
For a large European energy company, online machine learning provides a systematic and automated approach to commodities trading, including creating and executing trading strategy and predicting prices.
How Applying an AI-Defined Infrastructure Can Boost Data Center OperationsCognizant
An artificial-intelligence-based infrastructure that uses the data available within the data center to optimize and automate infrastructure operations can enhance operational efficiencies and improve the quality of service offered to the business.
Automated AI The Next Frontier in Analytics - StampedeCon AI Summit 2017StampedeCon
This talk will walk through the important building blocks of Automated AI. Rajiv will highlight the current gaps in the analytics organizations, how to close those gaps using automated AI. Some of the issues discussed around automated AI are the accuracy of models, tradeoffs around control when using automation, interpretability of models, and integration with other tools. These issues will be highlighted with examples of automated analytics in different industries. The talk will end with some examples of how automated AI in the hands of data scientists and business analysts is transforming analytic teams and organizations.
AI in the Enterprise: Past, Present & Future - StampedeCon AI Summit 2017StampedeCon
Artificial Intelligence has entered a renaissance thanks to rapid progress in domains as diverse as self-driving cars, intelligent assistants, and game play. Underlying this progress is Deep Learning – driven by significant improvements in Graphic Processing Units and computational models inspired by the human brain that excel at capturing structures hidden in massive complex datasets. These techniques have been pioneered at research universities and digital giants but mainstream enterprises are starting to apply them as open source tools and improved hardware become available. Learn how AI is impacting analytics today and in the future.
Learn how AI is affecting the enterprise including applications like fraud detection, mobile personalization, predicting failures for IoT and text analysis to improve call center interactions. We look at how practical examples of assessing the opportunity for AI, phased adoption, and lessons going from research, to prototype, to scaled production deployment.
Benefits of ai enabled project managementOrangescrum
Adoption of Artificial Intelligence in project and task management tools is helping in developing chat bots and adding AI enabled functionalities to get engage with users.
The complexity, criticality, and real-time demands of the energy sector make it a prime candidate to benefit from applying machine learning. This session presents two case studies of machine learning automating decisions for energy companies.
For the largest windfarm operator in North America, machine learning applies predictive and prescriptive analytics to the complex task of scheduling crews for maintenance and repairs. Automating the scheduling process across multiple windfarm sites saves the operator millions in labor costs per year and frees managers and crews to do actual work. Machine learning also evaluates ever-changing conditions and automatically reschedules workers and tasks as necessary.
For a large European energy company, online machine learning provides a systematic and automated approach to commodities trading, including creating and executing trading strategy and predicting prices.
How Applying an AI-Defined Infrastructure Can Boost Data Center OperationsCognizant
An artificial-intelligence-based infrastructure that uses the data available within the data center to optimize and automate infrastructure operations can enhance operational efficiencies and improve the quality of service offered to the business.
Automated AI The Next Frontier in Analytics - StampedeCon AI Summit 2017StampedeCon
This talk will walk through the important building blocks of Automated AI. Rajiv will highlight the current gaps in the analytics organizations, how to close those gaps using automated AI. Some of the issues discussed around automated AI are the accuracy of models, tradeoffs around control when using automation, interpretability of models, and integration with other tools. These issues will be highlighted with examples of automated analytics in different industries. The talk will end with some examples of how automated AI in the hands of data scientists and business analysts is transforming analytic teams and organizations.
AI in the Enterprise: Past, Present & Future - StampedeCon AI Summit 2017StampedeCon
Artificial Intelligence has entered a renaissance thanks to rapid progress in domains as diverse as self-driving cars, intelligent assistants, and game play. Underlying this progress is Deep Learning – driven by significant improvements in Graphic Processing Units and computational models inspired by the human brain that excel at capturing structures hidden in massive complex datasets. These techniques have been pioneered at research universities and digital giants but mainstream enterprises are starting to apply them as open source tools and improved hardware become available. Learn how AI is impacting analytics today and in the future.
Learn how AI is affecting the enterprise including applications like fraud detection, mobile personalization, predicting failures for IoT and text analysis to improve call center interactions. We look at how practical examples of assessing the opportunity for AI, phased adoption, and lessons going from research, to prototype, to scaled production deployment.
Benefits of ai enabled project managementOrangescrum
Adoption of Artificial Intelligence in project and task management tools is helping in developing chat bots and adding AI enabled functionalities to get engage with users.
From a session at OMEP's Manufacturing the Future Summit, January 14, 2014. By: Katie Moore Global Industry Manager – Food & Beverage GE Intelligent Platforms
Smart Data Slides: Modern AI and Cognitive Computing - Boundaries and Opportu...DATAVERSITY
We will kickoff the 2017 series with an overview of the current state of commercial artificial intelligence (AI) and cognitive computing. The research and commercial communities are far from consensus on a few important definitions, so we will start with two that are critical to our understanding and analysis.
#ModernAI applies research from computer science, psychology, mathematics, linguistics and neuroscience to develop problem-solving applications that supplant or augment human intellectual performance. Unlike more traditional AI R&D, #ModernAI typically leverages machine learning and big data.
Cognitive computing is a problem-solving approach based on #ModernAI that focuses on processes for understanding, reasoning, learning and planning.
In this webinar, we will present a framework for analyzing modern AI/cognitive computing tools and technologies, with an emphasis on the risks and reward of adopting them at varying stages of maturity.
Streaming Analytics for IoT-Oriented ApplicationsDATAVERSITY
The growth of connected devices on the Internet of Things (IOT) is already creating huge volumes of sensor- and system-oriented data. The pace will no doubt continue to increase for years to come. Finding and leveraging opportunities from this data faster and more effectively than your competition requires the effective use of streaming analytics. We simply don’t have time to apply legacy techniques and can’t interrupt the flow to analyze it. The good news is that tools and techniques enable us to get usable analytics in near-real time today, and to integrate current streams of data with historical archives to create prescriptive systems that direct next best action scenarios.
This webinar will present an overview of streaming analytics technologies and tools, and help participants identify opportunities for streaming analytics-enabled IOT applications.
DevOps took us from SysAdmins to DeployAdmins to improve availability but came with a tidal wave of tools and environments, leaving detecting anomalies and finding root cause a task for the overcrowded war-room of siloed experts.
Developers need to understand infrastructure, and operations needs to understand the SDLC.
The good news is AIOps can help!
Let’s look at what AIOps can realistically do for us, identify criteria for where to automate and lay out the stepping stones for achieving AIOps.
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/may-2019-embedded-vision-summit-tschudi
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Yohann Tschudi, Technology and Market Analyst at Yole Développement, presents the "AI Is Moving to the Edge—What’s the Impact on the Semiconductor Industry?" tutorial at the May 2019 Embedded Vision Summit.
Artificial intelligence is proliferating into numerous edge applications and disrupting numerous industries. Clearly this represents a huge opportunity for technology suppliers. But it can be difficult to discern exactly what form this opportunity will take. For example, will edge devices perform AI computation locally, or in the cloud? Will edge devices use separate chips for AI, or will AI processing engines be incorporated into the main processor SoCs already used in these devices?
In this talk, Tschudi answers these questions by presenting and explaining his firm's market data and forecasts for AI processors in mobile phones, drones, smart home devices and personal robots. He explains why there is a strong trend towards executing AI computation at the edge, and quantifies the opportunity for separate processor chips and on-chip accelerators that address visual and audio AI tasks.
Gamifying Strategy - Enterprise AI use cases on agent-based simulation and re...AnandSRao1962
This talk was presented at the 2018 O'Reilly AI conference in New York. It highlights how advances in AI gaming technology can be used to solve strategic problems in business. It combines agent-based modeling with reinforcement learning to solve strategic problems in financial services and mobility as a service sectors.
Smart Data Webinar: The Road to Autonomous ApplicationsDATAVERSITY
Autonomous systems are like teenagers. The decision to trust one to complete a task without strict supervision depends on the individual and the task. Performance and trust are variables on spectra. As with teens, some autonomous systems will be ready before we are ready to trust them, and some will take a little longer.
As we get comfortable with delegating routine domestic tasks to home robots and prepare for a world with self-driving cars and beyond, it is important to understand the opportunities and limits for autonomous systems. Participants in this webinar will learn about the technologies that enable autonomous systems, and how to critically assess design constraints for independent and collaborating autonomous solutions.
Artificial Intelligence is trendy. Every event, every strategy meeting and every consulting firm talks about it. This whitepaper aims to separate actual facts and important background information from the overarching marketing buzz.
You will get a short but information-rich wrap up about: What causes the current hype? Where are we today? What are the innovation leaders doing with AI? And what are immediate action points to focus on by applying artificial intelligence to your business?
IT Operation Management Automation Roadmap post PandemicManasKumarLenka1
Captures a roadmap as to how Post Pandemic, Organizations Like CGI can in grow in ITOM automation space considering they have existing IP and experience IN RPA , BPM space
Robotic Process Automation & Artificial Intelligence - Eric stiouiSITA
Big data is big... How big?
Big data and new behaviors influence customer experience and emotions influence decisions
Service level expectations are rising
... and how an evolving automation framework is producing results
AI in Business - Key drivers and future valueAPPANION
Artificial Intelligence is undoubtedly a hyped topic at the moment. But what is the reasoning for investors and digital platform players to bet very large amounts of money on this technology right now? To better understand the current market dynamics and to give an overview of renown predictions for the upcoming 2-3 years, we compiled a practical overview of this topic. This report covers the major driving forces of AI, assumptions for the future from the industry thought leaders as well as practical advice on how to start AI projects within your company.
EMA Research has shown many in IT operations feel they would be better served by fewer, more broadly functioning automation tools. The more effective automation tools are highly integrated and data-driven.
These slides—based on the webinar from EMA Research and Red Hat--explain how enterprises are addressing IT complexity with automation.
Building an AI Startup: Realities & TacticsMatt Turck
AI is all the rage in tech circles, and the press is awash in tales of AI entrepreneurs striking it rich after being acquired by one of the giants. As always, the realities of building a startup are different, and the path to success requires not just technical prowess but also thoughtful market positioning and business excellence.
In a talk of interest to anyone building or implementing an AI product, Matt Turck and Peter Brodsky leverage hundreds of conversations with AI (and big data) founders and hard-learned lessons building companies from the ground up to highlight successful strategies and tactics.
Topics include:
Successful data acquisition strategies
Data network effects
Competing with the giants
A pragmatic approach to building an AI team
Why social engineering is just as important to success as groundbreaking AI technology
IBM Academy of Technology & Cognitive ComputingNico Chillemi
I delivered this presentation at University at Chieti-Pescara in Abruzzo (Italy) in September 2015, introducing IBM Academy of Technology and talking about Cognitiva Computing and Analytics with IBM Watson and IBM IT Operations Analytics Log Analysis (ITOA). The video in Italian is available on YouTube, please contact me if you are interested. Thanks to Amanda Tenedini for the help with Social Media and to Piero Leo for the help with IBM Watson.
Technology that is going to create a revolution in every Industry including Health care. What is it, what are the tools and what is the outcome?
NASA started the research on Twins due to space travel and the need to have real time feedback of components. Now it is extending to even Health care to having a Human twin.
Internet is no longer just a global network for people to communicate with one another using computers, but it is also a platform for devices to communicate electronically with the world around them. The result is a world that is alive with information as data flows from one device to another and is shared and reused for a multitude of purposes. Harnessing the potential of all of this data for economic and social good is one of the primary challenges and opportunities. IoT enabled data driven predictive maintenance is becoming relevant in all the major industries as it can drive efficiency by providing higher levels of safety and quality at a fraction of the current costs. Thanks to Big Data, Analytics and IoT devices, predicting potential failures is going to be a real capability…but what happens after a failure is predicted, the need for maintenance is detected or a part replacement is required? Even if you can predict failures, dynamic technician scheduling associated with equipment maintenance management requires insight into real-time held inventory, technician location and estimated service completion time. Establishing an ecosystem where customers, equipment producers, service companies and all other digital service providers can collaborate is the right answer.
From a session at OMEP's Manufacturing the Future Summit, January 14, 2014. By: Katie Moore Global Industry Manager – Food & Beverage GE Intelligent Platforms
Smart Data Slides: Modern AI and Cognitive Computing - Boundaries and Opportu...DATAVERSITY
We will kickoff the 2017 series with an overview of the current state of commercial artificial intelligence (AI) and cognitive computing. The research and commercial communities are far from consensus on a few important definitions, so we will start with two that are critical to our understanding and analysis.
#ModernAI applies research from computer science, psychology, mathematics, linguistics and neuroscience to develop problem-solving applications that supplant or augment human intellectual performance. Unlike more traditional AI R&D, #ModernAI typically leverages machine learning and big data.
Cognitive computing is a problem-solving approach based on #ModernAI that focuses on processes for understanding, reasoning, learning and planning.
In this webinar, we will present a framework for analyzing modern AI/cognitive computing tools and technologies, with an emphasis on the risks and reward of adopting them at varying stages of maturity.
Streaming Analytics for IoT-Oriented ApplicationsDATAVERSITY
The growth of connected devices on the Internet of Things (IOT) is already creating huge volumes of sensor- and system-oriented data. The pace will no doubt continue to increase for years to come. Finding and leveraging opportunities from this data faster and more effectively than your competition requires the effective use of streaming analytics. We simply don’t have time to apply legacy techniques and can’t interrupt the flow to analyze it. The good news is that tools and techniques enable us to get usable analytics in near-real time today, and to integrate current streams of data with historical archives to create prescriptive systems that direct next best action scenarios.
This webinar will present an overview of streaming analytics technologies and tools, and help participants identify opportunities for streaming analytics-enabled IOT applications.
DevOps took us from SysAdmins to DeployAdmins to improve availability but came with a tidal wave of tools and environments, leaving detecting anomalies and finding root cause a task for the overcrowded war-room of siloed experts.
Developers need to understand infrastructure, and operations needs to understand the SDLC.
The good news is AIOps can help!
Let’s look at what AIOps can realistically do for us, identify criteria for where to automate and lay out the stepping stones for achieving AIOps.
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/may-2019-embedded-vision-summit-tschudi
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Yohann Tschudi, Technology and Market Analyst at Yole Développement, presents the "AI Is Moving to the Edge—What’s the Impact on the Semiconductor Industry?" tutorial at the May 2019 Embedded Vision Summit.
Artificial intelligence is proliferating into numerous edge applications and disrupting numerous industries. Clearly this represents a huge opportunity for technology suppliers. But it can be difficult to discern exactly what form this opportunity will take. For example, will edge devices perform AI computation locally, or in the cloud? Will edge devices use separate chips for AI, or will AI processing engines be incorporated into the main processor SoCs already used in these devices?
In this talk, Tschudi answers these questions by presenting and explaining his firm's market data and forecasts for AI processors in mobile phones, drones, smart home devices and personal robots. He explains why there is a strong trend towards executing AI computation at the edge, and quantifies the opportunity for separate processor chips and on-chip accelerators that address visual and audio AI tasks.
Gamifying Strategy - Enterprise AI use cases on agent-based simulation and re...AnandSRao1962
This talk was presented at the 2018 O'Reilly AI conference in New York. It highlights how advances in AI gaming technology can be used to solve strategic problems in business. It combines agent-based modeling with reinforcement learning to solve strategic problems in financial services and mobility as a service sectors.
Smart Data Webinar: The Road to Autonomous ApplicationsDATAVERSITY
Autonomous systems are like teenagers. The decision to trust one to complete a task without strict supervision depends on the individual and the task. Performance and trust are variables on spectra. As with teens, some autonomous systems will be ready before we are ready to trust them, and some will take a little longer.
As we get comfortable with delegating routine domestic tasks to home robots and prepare for a world with self-driving cars and beyond, it is important to understand the opportunities and limits for autonomous systems. Participants in this webinar will learn about the technologies that enable autonomous systems, and how to critically assess design constraints for independent and collaborating autonomous solutions.
Artificial Intelligence is trendy. Every event, every strategy meeting and every consulting firm talks about it. This whitepaper aims to separate actual facts and important background information from the overarching marketing buzz.
You will get a short but information-rich wrap up about: What causes the current hype? Where are we today? What are the innovation leaders doing with AI? And what are immediate action points to focus on by applying artificial intelligence to your business?
IT Operation Management Automation Roadmap post PandemicManasKumarLenka1
Captures a roadmap as to how Post Pandemic, Organizations Like CGI can in grow in ITOM automation space considering they have existing IP and experience IN RPA , BPM space
Robotic Process Automation & Artificial Intelligence - Eric stiouiSITA
Big data is big... How big?
Big data and new behaviors influence customer experience and emotions influence decisions
Service level expectations are rising
... and how an evolving automation framework is producing results
AI in Business - Key drivers and future valueAPPANION
Artificial Intelligence is undoubtedly a hyped topic at the moment. But what is the reasoning for investors and digital platform players to bet very large amounts of money on this technology right now? To better understand the current market dynamics and to give an overview of renown predictions for the upcoming 2-3 years, we compiled a practical overview of this topic. This report covers the major driving forces of AI, assumptions for the future from the industry thought leaders as well as practical advice on how to start AI projects within your company.
EMA Research has shown many in IT operations feel they would be better served by fewer, more broadly functioning automation tools. The more effective automation tools are highly integrated and data-driven.
These slides—based on the webinar from EMA Research and Red Hat--explain how enterprises are addressing IT complexity with automation.
Building an AI Startup: Realities & TacticsMatt Turck
AI is all the rage in tech circles, and the press is awash in tales of AI entrepreneurs striking it rich after being acquired by one of the giants. As always, the realities of building a startup are different, and the path to success requires not just technical prowess but also thoughtful market positioning and business excellence.
In a talk of interest to anyone building or implementing an AI product, Matt Turck and Peter Brodsky leverage hundreds of conversations with AI (and big data) founders and hard-learned lessons building companies from the ground up to highlight successful strategies and tactics.
Topics include:
Successful data acquisition strategies
Data network effects
Competing with the giants
A pragmatic approach to building an AI team
Why social engineering is just as important to success as groundbreaking AI technology
IBM Academy of Technology & Cognitive ComputingNico Chillemi
I delivered this presentation at University at Chieti-Pescara in Abruzzo (Italy) in September 2015, introducing IBM Academy of Technology and talking about Cognitiva Computing and Analytics with IBM Watson and IBM IT Operations Analytics Log Analysis (ITOA). The video in Italian is available on YouTube, please contact me if you are interested. Thanks to Amanda Tenedini for the help with Social Media and to Piero Leo for the help with IBM Watson.
Technology that is going to create a revolution in every Industry including Health care. What is it, what are the tools and what is the outcome?
NASA started the research on Twins due to space travel and the need to have real time feedback of components. Now it is extending to even Health care to having a Human twin.
Internet is no longer just a global network for people to communicate with one another using computers, but it is also a platform for devices to communicate electronically with the world around them. The result is a world that is alive with information as data flows from one device to another and is shared and reused for a multitude of purposes. Harnessing the potential of all of this data for economic and social good is one of the primary challenges and opportunities. IoT enabled data driven predictive maintenance is becoming relevant in all the major industries as it can drive efficiency by providing higher levels of safety and quality at a fraction of the current costs. Thanks to Big Data, Analytics and IoT devices, predicting potential failures is going to be a real capability…but what happens after a failure is predicted, the need for maintenance is detected or a part replacement is required? Even if you can predict failures, dynamic technician scheduling associated with equipment maintenance management requires insight into real-time held inventory, technician location and estimated service completion time. Establishing an ecosystem where customers, equipment producers, service companies and all other digital service providers can collaborate is the right answer.
Sensing-as-a-Service - An IoT Service Provider's PerspectivesDr. Mazlan Abbas
UM-MCMC Connected Communities and Internet of Things (IoT): Building Value through Visibility
at Universiti Malaya (UM)
Wednesday, December 10, 2014 from 8:00 AM to 4:00 PM (MYT)
Kuala Lumpur, Malaysia
Learn how and why leading oil & gas companies are developing real-time applications to power their mission-critical business functions and see how VANTIQ enables this digital transformation.
Internet of things - Introduction and Variations (Architecture)Mayank Vijh
The slides includes the IOT Architecture introduction and how that is being used in certain use cases around the industries.
Topics include :
Introduction
Trends and Hype cycle
Major IOT Players
Real World Problems
IOT Architecture and variations
Challenges and Tools
Difference between M2M and IOT practice.
KPI and Criteria
Evaluation and Decision
Conclusion
Get Cloud Resources to the IoT Edge with Fog ComputingBiren Gandhi
Fog Computing as a foundational architectural concept for Internet of Things (IoT) and Internet of Everything (IoE).
Embedded devices in the IoT are hampered by the compute, storage, and service limitations of living life on the edge. As IoT edge devices comprise broader sensor networks for industrial automation, transportation, and other safety critical applications, their high uptime requirements are nonnegotiable and service latencies must be kept within realtime or near real time parameters. However, the size, weight, power, and cost constraints of edge platforms also inhibit the ondevice resources available for executing such functions. In this session, Gandhi will introduce Fog Computing, a new paradigm for the IoT that extends compute, storage, and application resources from the cloud to the network edge. Beyond the interplay between Fog and Cloud, Gandhi will show how Fog services can be leveraged across a range of heterogeneous platforms—from end user devices and access points to edge routers and switches—through software technology that facilitates the collection, storage, analysis, and fusion of data to drive success in your next IoT device deployment.
The What and Why of Event-Driven Applications - VANTIQ/EDA OverviewVANTIQ
There is a paradigm shift sweeping across all industries - event-driven architecture. Learn how and why leading companies are developing real-time applications to power their mission-critical business functions and see how VANTIQ enables this digital transformation.
Want to learn more about how VANTIQ is powering the future through real-time event-driven applications? Check us out at: vantiq.com
Webinar - Transforming Manufacturing with IoTHARMAN Services
The Manufacturing industry is realizing the tremendous benefits in the “Internet of Things” (IoT), an inevitable evolution to traditional M2M solutions. Innovations across embedded devices, advanced analytics, and enriched user experiences all powered by cloud, has enabled new opportunities for both perpetual revenue and perpetual customer value. In this session we will break down benefits of IoT for Manufacturing with real-world examples.
Integrierte Anwendungsfälle - Von der einzelnen Nachricht, über zeitnahe Anal...AWS Germany
In der Sessions zum Thema Integrierte Anwendungsfälle werden folgende Punkte besprochen:
Gewinnen Sie relevante Informationen aus Ihren Gerätedaten mit agilen Business Intelligence Lösungen
Integrieren Sie Ihre Gerätenetze mit software-gestützten Geschäftsprozessen
Ermöglichen Sie automatisierte Entscheidungen für autonome Netzwerke mit Machine Learning
Informieren Sie sich jetzt über das kostenlose Nutzungskontingent von AWS: http://amzn.to/1Qh9stj
More and more people in mega cities, more sensors, more apps, Smart is everywhere for smart living. but what's about security, what's about the people. How to deliver better living, happy living. HPE provides IoT solutions with connectivity management, processing at the edge and in the cloud, security, data management, etc to help industry verticals, telecom operators deliver secured trusted IoT solutions
Mr. Paul Chang's presentation at QITCOM 2011QITCOM
QITCOM 2011
Presentation:
City Operations Centre for Managing City
Presenter:
Mr. Paul Chang - Business Development Executive for Emerging Markets, IBM
Similar to Future IT Trends Talk @Stanford OIT 554 Class - Guest Speaker - 3.7.17 (20)
Reasoning by Similarity on Top of an Associative MemoryPaul Hofmann
IBM Research - Almaden Colloquium: The Cognitive Enterprise November 19, 2013 at IBM Research - Almaden in San Jose, CA. IBM Research has convened a stellar list of speakers including the founder of Palm, Jeff Hawkins; Paul Hofmann, CTO of Saffron Technology; John Hollar, President of the Computer History Museum; Dick Karp, Turing Award and Kyoto Prize recipient; Olivier Lictharge, Baylor School of Medicine; and distinguished panelists from the Silicon Valley VC community.
Cognitive computing with associative memories reasoning by similarityPaul Hofmann
We combine two very powerful ideas, Associative Memories (also called Depp Learning w/o back propagation) and Kolmogorov Complexity for Cognitive Computing in order to make meaning from huge data sets in real time. Associative Memories mimic how humans learn and think but much faster and more powerfully. Saffron Technology has implemented a most efficient Associative Memory storing graphs as matrices in a triple store. The Associative Memory functions as a universal compressor for approximating Kolmogorov Complexity K(x). The universal cognitive distance based on K(x) is used for reasoning by similarity like a super brain.
We'll show use cases from health care @Mt Sinai Hospital in NY - automatic diagnosis of echocardiograms in real time, global risk @The Bill and Melinda Gates Foundation - real time threat scoring reading incoming emails, and maintenance and repair @Boeing - predicting before a part breaks.
New Business Applications Powered by In-Memory Technology @MIT Forum for Supp...Paul Hofmann
Talk about 4 leading edge projects:
1) Optimal pricing for energy management, online pricing, and truck scheduling @Princeton University
2) Infinite DRAM - RAMCloud @Stanford University
Applications: Extremely low latency and very high bandwidth
a) Facebook like problems with high read AND write rate,
b) advanced analytics, c) what-if scenarios for demand planning
3) Hybrid In-Memory Store @MIT CSAIL
4) Multithreading Real Time Event Platform @MIT Auto-ID Lab
500k events/s and millions of threads in-memory or distributed used for automatic meter reading, online billing, mobile billing and Smart Grid
The Big Five IT Mega Trends - talk @ Filene Research Institute at Kansas City for executives and technology leaders of US and CA Federal Credit Unions and keynote @MEDES
1) Mobile
2) Big data - data doubles every 18 month - the information age economy will create value by sense making form data
3) Social Media
4) Cloud
5) Consumerization
Dynamic Search Using Semantics & StatisticsPaul Hofmann
This presentation shows 3 applications of successfully combining semantics and statistics for text mining and interactive search.
1) We predict the Lehman bankruptcy using statistical topic modeling, SAP Business Objects entity extraction and associative memories (powered by Saffron Technologies).
2) We semi-automatically handle service requests at Cisco using knowledge extraction and knowledge reuse.
3) We discover user intent for interactive retrieval. User intent is defined as a latent state. The observations of this latent state are the reformulated query sequence, and the retrieved documents, together with the positive or negative feedback provided by the user. Demo shows recognizing user’s intent for health care search.
Viewpoints CACM paper
Economic and Business Dimensions-
Cloud Computing and Electricity:
Beyond the Utility Model Assessing the strengths, weaknesses, and general applicability of the computing-as-utility business model.
New Technologies For The Sustainable Enterprise; keynote @WhartonPaul Hofmann
Dinner keynote at Wharton May 9th 2011 @ 11th Annual Strategy and the Business Environment Conference (SBE) jointly with the 3rd Annual Research Conference Alliance for Research on Corporate Sustainability (ARCS)
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
2. The Big Five IT Mega Trends
• Internet of Things
Assets Turn Into Applications
• Machine Intelligence
AI Could Replace 50M Professional Jobs
• Distributed Ledgers
Block chain is becoming mainstream
• Sharing Economy
We don’t owe anything anymore
• Virtual and Augmented Reality
Remote experience merge visual & digital
world
4. Assets Turn Into Applications
• The Internet of Things is driving
automation in asset-intensive
industries.
• Everything will have a digital twin.
• Everything becomes software.
• Assets become applications.
Examples:
Amazon
Retail experience as application.
Goods, warehouses, delivery trucks
are peripherals.
Uber
Transportation as application.
Drivers, cars are peripherals.
5. Asset Sentinel
Application: Mobile Asset Monitoring
Asset Sentinel Listener is mounted on or in the trailer,
establishing connection with beacons on each pallet or
container. It reports environmental conditions such as
temperature, pressure, barometric pressure and light.
Custody of containers and palettes is maintained
throughout the journey, transferring from the origination,
to the trailer and driver, and then to the destination.
Can discern theft or misappropriation vs. package
not loaded.
Asset Sentinel is able to reconcile the beacons it heard
with the bill of lading as the driver pulls away. If the
real-time load does not reconcile, driver is alerted with a
push notification even before they leave
the yard.
Take custody of entire loads with a push of a button.
6. Asset Sentinel
Application: Mobile Asset Monitoring
Near real-time location and proximity of
trucks / containers / drivers at docks,
and at every point along the route. Real-
time logging of all environmental changes
to trailers and containers. Accelerometers
provide shock and drop information. Chain
of custody with bill of lading.
Take custody of entire loads with a push of a button.
Understand production line impact and
continuously optimize operations
based on condition monitoring of
cargo/container and needed parts.
During oceanic transfer, data is collected
during the entire journey then transmitted
once connectivity is re-established.
7. • End to end supply tracking, from sourced components to
assembly plants
• Connecting to the carriers
• Real-time tracking of cargo, where it is, what condition is it in,
who has possession
• Chain of custody – was it stolen, forgotten, or misplaced?
• Accurately predicting ETA / POD and condition of cargo
BLE Beacons + User/Device Management +
Discovery Service + Location Service + Chat Service
+ Asset Management + Chain of Custody + Machine
Learning
Logistics and Supply Chain
8. • Builds on existing infrastructure to improve service uptime
• Intelligent agents monitor network of sensors and devices
• Instrumentation and health monitoring of track switches
• When critical condition occurs, automatically find nearest
technician with right certifications and right tools and parts
• Automatic dispatch of maintenance crews, repairs, spare
parts
• Integrated with machine learning optimization
Switch Sensors + BLE Beacons + User/Device Management
+ Discovery Service + Location Service + Chat Service +
Asset Management + Chain of Custody + Job Scheduling +
Machine Learning
Rail Switch Health
9. Connect Everything
• Single solution delivers cloud, edge, and
devices
• Device agnostic : Supports any protocol
• Rapid edge device development: robust
SDKs/libraries
• Smart Agents make any device a peer
• Logic in the cloud allows solution recipes
• Operationally simple - deploy on AWS, Google
Cloud Engine, or on premise
• Can be embedded in hardware and systems
Warp IoT Capabilities
Field service and
asset tracking
with auto dispatch
Real-time fleet, driver,
and asset tracking
Mobile work
force
Predict rail switch health
and optimize maintenanceReal-time visualization
and analytics for
operational monitoring
and response
10. Applications for Actionable Insight and Automation
Our Technologies
• Continuous learning on
streaming data for
predictive and
prescriptive application
• IIoT services for
essential connectivity
and data collection
• Real-time actionable
insight visualization
12. By 2019 A $1000 Computer Will Have The Same Processing Power As The
Human Brain
13. Exponential Productivity Growth Due To Cognitive Machines
In the Second Machine Age, Brynjolfsson and
McAfee argue, “we are beginning to automate a
lot more cognitive tasks, a lot more of the control
systems that determine what to use that power
for. In many cases today artificially intelligent
machines can make better decisions than
humans.”
The Next Phase of the Digital
Economy
How we build, use, and live with our digital creations will define
our success as a civilization in the twenty-first century. Will our
new technologies lift us all up or leave more and more of us
behind? The Second Machine Age is the essential guide to
how and why that success will, or will not, be achieved.”
Garry Kasparov, thirteenth World Chess Champion
14. Machine Intelligence
• Machines will talk to each other
• Understand, learn, predict, adapt and
operate autonomously
• AI Could Replace 50M Professional Jobs
~ 40% of employment
Martin Ford in The Lights in the Tunnel:
Automation, Accelerating Technology and the
Economy of the Future
Software Will Eat The World
16. Applying Probabilistic Graphs To Time
Series
- Pricing Optimal Battery Warranty
- Commodities Trading
- Case Study Predictive &
Prescriptive
Windpark Maintenance
17. Use Time Series To Predict Nonlinear Battery Failure
Innovative machine learning to find hidden
patterns in time series
Predict capacity degradation without having
seen it in the wild
Combine Hidden Markov Model with
Hierarchical Mixture Models
Why
Reduce accruals by reducing
financial risk of warranties
How
Predict degradation over time
Find optimal policy for
warranties
18. CBM with
Prediction
Assumes failure at A:
lower asset life, increased
repair/replacement costs
Time in Operation
Advanced machine learning for optimized asset lifecycle
Failure
SpaceTime
Machine Learning
● Predict forward in time
without loss of confidence
● “See over the hill” to extend
asset life
● Produce better optimization
for lower costs and
increased productivity
A
Optimization
Zone
Probability of
Failure
Predict Failure
Optimize
Operations
Detect
Anomalies
Extended Asset Life
B
19. The failure prediction
gives you the probability
of failure into the future -
at any point in time
Battery Capacity Prediction Example
Look Into The Future From Any
Point In Time
Example Of Capacity Prediction
30% Rated
Capacity
Depletion
70% Capacity
20. The Holy Grail Of Time Series Beating The EMH
Innovative machine learning to find hidden
patterns in time series
Combine deep learning with hierarchical
dynamic Bayesian Models to predict price
Use stochastic optimization for money
management
Learn optimal trading policy
EMH
Efficient Market Hypothesis
Market reflects all relevant
info
Systematics Trading
Make money beating the
EMH
21. Futures Contracts
Energy
BRENT CRUDE
WTI CRUDE
US NATURAL
GAS
UK NATURAL
GAS
ETHANOL
Brent CrudeMetals
GOLD
SILVER
COPPER
PALLADIUM
Crops
CORN
WHEAT
SOYBEANS
OIL
SOYBEANS
MEAL
22. Helping Largest Wind Farm Operator
Make Decisions Under Uncertainty
• Reduced crew hours: $2.3 million
savings/location
• Optimized crew schedule
• Improved crew safety and regulatory compliance
• Solution – Crew Optimization – 250 users
Success Story: Predictive Maintenance & Optimization
● Largest wind farm operator in the world; 19
states and 4 Canadian provinces
● 100+ sites; 10,000+ turbines; 1,000
teammates
“Using advanced analytics to
optimize resources and efficiency
allowing us to reclaim thousands of
lost hours of productivity”
General Manager
Largest Windfarm Operator Energy Resources
23. Optimization
Weather Forecasts
Crew Availability
Work Order List
Sensor
Data
Crew Schedule
Crew Route
Work Order
List
Traffic
Value of Activities
Performed
Risk and Cost
Managed
Crew Skills
Asset Failure
Model
Other Models
DATA INPUTS OUTPUTS/ACTION
Remaining
Useful Life
SpaceTime can perform optimization even when
inputs involve uncertainty, like weather or
traffic, and constantly changing inputs like the
probability of asset failure.
Global Optimization of Operations
24. Hub Optimization
Reinforcement learning to optimize
throughput over time subject to constraints
service level by product
available workforce
system capacity
System enables dynamical real-time
reassignment based on latest IoT updates
Why
Better throughput, improved
preventive maintenance,
reduce inventory
How
Queuing Theory
25. Reasoning Under Uncertainty Over Graphs
Speech Recognition Computer Vision
Assets As ApplicationsGames
Time in
Operation
Failur
e
A
Optimiza
tion
Zone
Probability
of Failure
Predict
Failure
Optimize
Operation
s
Detect
Anomalies
Extended Asset Life
B
27. Distributed Ledgers – Thriving On Mutual Distrust
• Institutions –> reduce uncertainty
• Informal rules, formal rules, online institutions
• Create trust with technology alone
• Who? Public attestation -> portable ID
• Transparency? Digital token in supply chain
• Reneging? Enforce contract w/o 3rd party
• Unique innovation in CS and business
https://www.youtube.com/watch?v=r43LhSUUGTQ
Autonomous Systems For Exchanging
Value
The Business Wikipedia – Shared
Monopoly
29. The Sharing Economy – Access Economy
• Travel, car sharing, finance, staffing & streaming
• $15 billion in 2014 ~ 5% of the total spending
• $335 billion by 2025 ~ 50% of the total spending
• E.g. UberX produces ~ $6.8 billion social value/a
Using Big Data to Estimate Consumer Surplus -
The Case of Uber, Peter Cohen, Robert Hahn,
Jonathan Hall, Steven Levitt, and Robert Metcalfe
The Tragedy of the Commons Is the Distributed Ledger the
Solution?
31. Visualization Technologies
Virtual Reality Augmented Reality
Immerse the user in a virtual world
e.g. Oculus Rift – Facebook – Available now
Project virtual content over top of the real world
e.g. Microsoft HoloLens ~ 1 year out
32. Combining LIDAR Data With Ortho Photos - Orthofusion
OrthofusionLIDAR elevation data + an “ortho” =
(aerial) photo
35. Virtual Augmented Reality
LIDAR Data + Virtual Reality = Virtual Augmented Reality
Reality captured
as a LIDAR
point cloud
Use VR technology to
- Render the point cloud
- Augment it with
- Simple highlights
- Asset Models
- Artificial Intelligence
- Veg Growth models
- What-if
- Risk
- etc
-
Real vegetation
LIDAR snapshot
Virtual Tree
overlaid
36. Vegetation Intelligence – Outer Loop Learning Model using
LIDAR
LIDAR
Data
Update
Growth
Model
Predict
Growth
Areas
(Machine
Learning)
LIDAR
Data
Optimize Trim Plan
Risk/Cost
(Produce
Schedule)
Trim
Operations
Other Data
- Climate
- Outages
- Environment
37. A Day In The Life For Next Gen Vegetation
Planning
Review Trim
Plan
View
Scheduled
Points of
Interest by
Analytics
Risk Score
Click on
browser to
teleport to
LIDAR View
of Area
Adjust plan
or add notes
for crews
Move to
next Point of
Interest
Share Notes
and “Tour” of
schedule
with Crew
Manager
Planners
(central)
Crew
Managers
(central or Remote /
third party)
Crew Manager
Views Notes and is
Taken on spatial
“tour” of trim
schedule
38. Next Gen Vegetation Analytics
Tree &
conductor
data
Growth Study
Data
Weather Data
Vegetation Analytics
LIDAR Data
Click Button on Web Page
For user “teleportation”
Multi-year 3D LIDAR data
used as input for growth
modeling and feature
detection
User can teleport to a location
and compare predicted growth
against exact LIDAR measurements.
Understand situation crew is entering
Trim
History
Outage Data
39. The Big Five IT Mega Trends - Summary
• Internet of Things
Assets Turn Into Applications
• Machine Intelligence
AI Could Replace 50 M Professional Jobs
• Distributed Ledgers
Block chain is becoming mainstream
• Sharing Economy
We don’t owe anything anymore
• Virtual and Augmented Reality
Remote experience merge visual & digital
world