This document discusses the development of a Digital Readiness Level (DRL) model by the H S S M I institute. The DRL aims to provide a consistent measure of digital preparedness for UK manufacturers. It identifies six key capabilities (business case, technical, data, leadership, people, integration) and competencies within each. The DRL will be structured similar to other readiness levels and provide a concise assessment. HSSMI is working with industry partners to further develop and test the DRL model and capabilities.
LACE Project WP5 - Learning Analytics & Performance Support for Manufacturing...Fabrizio Cardinali
Presented by Fabrizio Cardinali at the Kick off of LACE Project (www.laceproject.eu), support action for learning analytics commuinity exchange. WP5 deals with promoting best practices and solutions for performance support and learning analytics in the industrial training mrketplace and manufacturing in particular
CD4ML - ThoughtWorks MeetUp Munich Christoph Windheuser May 8th 2019Christoph Windheuser
These are the slides of Christoph Windheuser at the MeetUp at ThoughtWorks in Munich on May 8th, 2019. Christoph spoke about how to build up a Continuous Delivery (CD) framework for Machine Learning and Data Science applications in the industry.
Additive Manufacturing
How do we shift paradigms and build new business models? In this presentation Mitch Free, a serial entrepreneur, shares experiences from CNC machining to launching two digital manufacturing companies. Find out the current state of additive manufacturing and how these concepts can be used to drive new business models.
Mitch Free, Founder, Chairman, and CEO of Fast Radius and ZYCI CNC Machining
From the 2017 Supply Chain Insights Global Summit
Sustainable manufacturing with AI
Improve your processes:
Defect detection to reduce waste
Predictive maintenance to improve energy efficiency
Generative design to reduce materials used in products
Process optimisation to improve energy usage
Inventory optimisation to reduce materials held
Improve your IT:
Go paperless
Move to carbon neutral clouds
Adopt green software products
Optimise your compute usage
Improve with Nightingale HQ
We’re doing bespoke and pilot projects with manufacturers and adjacent industries. Make your business more sustainable.
bit.ly/nhqaichat
Verbundprojekt im KMU-Instrument - Frische Einblicke in den AntragsprozessSimon Dierks
Tobias Dochow, Project Manager bei Sensorberg GmbH, beschreibt das Verbundprojekt im Bereich 'Smart Hospital', das mit dem Klinikum und der Universität Braunschweig realisiert werden soll und gibt frische Einblicke in den Antragsprozess.
Continuous Intelligence: Keeping Your AI Application in Production (NDC Sydne...Dr. Arif Wider
A talk about applying Continuous Delivery to Machine Learning (CD4ML) presented by Arif Wider from ThoughtWorks at NDC Sydney Conference 2019.
Abstract:
It is already challenging to transition a machine learning model or AI system from the research space to production, and maintaining that system alongside ever-changing data is an even greater challenge. In software engineering, Continuous Delivery practices have been developed to ensure that developers can adapt, maintain, and update software and systems cheaply and quickly, enabling release cycles on the scale of hours or days instead of weeks or months. Nevertheless, in the data science world Continuous Delivery is rarely been applied holistically.
This is partly due to different workflows: data scientists regularly work on whole sets of hypotheses, whereas software engineers work more linearly even when evaluating multiple implementation alternatives. Therefore, existing software engineering practices cannot be applied as-is to machine learning projects. Learn how we used our expertise in both fields to adapt practices and tools to allow for Continuous Intelligence–the practice of delivering AI applications continuously.
[GE Innovation Forum 2015] The Industrial Internet by Bill RuhGE코리아
[GE Innovation Forum 2015] The Industrial Internet by Bill Ruh
The Industrial Internet by Bill Ruh
GE의 산업인터넷: 제 3차 산업혁명
GE글로벌소프트웨어 총괄 빌 루 부사장
GE’s Industrial Internet: the 3rd Industrial Revolution
by Bill Ruh, Vice President, GE Global Software
GE코리아 뉴스레터를 구독하세요! http://goo.gl/IE8WS8
GE코리아 YouTube 채널을 구독하세요! http://goo.gl/M2gc8m
상상을 현실로 만듭니다. Imagination at work.
GE가 꿈꾸는 가치입니다. 아니, GE는 단지 꿈만 꾸고 있는 것이 아닙니다. 상상을 현실로 만들기 위해, 불가능했던 것을 가능하게 만들기 위해 쉬지 않고 움직이고 있습니다. GE는 에너지, 의료, 항공, 수송, 금융 등의 여러 분야에서 고객과 인류사회의 진보를 위해 더 편리하고 빠르며 친환경적인 솔루션을 찾아냅니다.
Connect with GE Online:
GE코리아 웹사이트: http://www.ge.com/kr/
GE리포트코리아: http://www.gereports.kr/
GE코리아 페이스북 페이지: hhttps://www.facebook.com/GEKorea
GE코리아 슬라이드쉐어: http://www.slideshare.net/GEKorea
Continuous Intelligence: Moving Machine Learning into Production ReliablyDr. Arif Wider
A workshop by Danilo Sato, Christoph Windheuser, Emily Gorcenski, and Arif Wider, given at Strata Data Conference 2019 in London.
Abstract:
So you want to include a machine learning component in your IT systems? The process is a little more involved than clicking through an AI tutorial on your laptop. It’s not just the first working model you run that you need to consider; you also need to think about things like integration, scaling, and testing. What’s more, postlaunch, you’ll want to continuously adapt your model to respond to the changing environment.
ThoughtWorks pioneered continuous delivery—a set of tools and processes that ensure that software under development can be reliably released to production at any time and with high frequency.
Danilo Sato and Christoph Windheuser demonstrate how to apply continuous delivery to machine learning—what’s known as continuous intelligence. In a live scenario, you’ll change a machine learning model in a development environment, test its new performance, and, depending on the outcome, automatically deploy the new model into a production environment. The tech stack for this scenario will be Python, DVC (Data Science Version Control), and GoCD.
A roundtable discussion on various CRM models from the Creative Industries Clusters Programme Award Holders Workshop held in Belfast in February 2019. Session facilitated by Nicola Osborne, Programme Manager and Michaela Turner, Business Development Manager for Creative Informatics at the University of Edinburgh.
Continuous Intelligence: Keeping your AI Application in ProductionDr. Arif Wider
A talk by Emily Gorcenski and Arif Wider presented a Strata Data Conference 2019 in London.
Abstract:
It’s already challenging to transition a machine learning model or AI system from the research space to production, and maintaining that system alongside ever-changing data is an even greater challenge. In software engineering, continuous delivery practices have been developed to ensure that developers can adapt, maintain, and update software and systems cheaply and quickly, enabling release cycles on the scale of hours or days instead of weeks or months.
Nevertheless, in the data science world, continuous delivery is rarely applied holistically—due in part to different workflows: data scientists regularly work on whole sets of hypotheses, whereas software engineers work more linearly even when evaluating multiple implementation alternatives. Therefore, existing software engineering practices cannot be applied as is to machine learning projects.
Arif Wider and Emily Gorcenski explore continuous delivery (CD) for AI/ML along with case studies for applying CD principles to data science workflows. Join in to learn how they drew on their expertise to adapt practices and tools to allow for continuous intelligence—the practice of delivering AI applications continuously.
Hendrik Witt (Ubimax GmbH) Enterprise Smartglasses ProjectsAugmentedWorldExpo
Rapidly changing innovation cycles and growing complexity & variance require flexible and efficient technologies in the Enterprise business processes. On the path towards Industry 4.0, Wearable Computing is increasingly playing a crucial role in the field of the human-machine interfaces. As a leading provider for Wearable Computing solutions Ubimax is facing those industry challenges and offers a worldwide unique portfolio of proven Smart Glass solutions within its “Enterprise Wearable Computing Suite”. Based on state-of-the-art Augmented Reality and Smart Glasses technology, Ubimax’ customers like Daimler, DHL, Schnellecke Logistics, Samsung or Volkswagen are already working with those innovative and award-winning solutions in their production environments – achieving performance increases of up to 40%! In his talk, Ubimax CEO Dr. Hendrik Witt provides exclusive insights into selected Wearable Computing projects and answers the question of how the Industry 4.0 requirements can be countered with Augmented Reality and hands-free Wearable Computing solutions – with main focus on the existing benefits and future potential of this technology for Enterprises.
CWIN17 Toulouse / Business that rely on data stax enterprise make smart decis...Capgemini
Data comes from different geographical locations and across multiple channels.
Managing this explosion of high velocity dynamic data while maintaining
customer privacy is a challenge with legacy systems.
Rely on the database designed for the age of the Internet of Things.
DataStax is built from the ground up to consume time-series and sensor-based
information faster than any other database. Easily add scale and capacity while
maintaining 100% uptime – no matter what. Search and analyze information to
deliver mind blowing experiences that will drive engagement and growth
BRM - Bridging the gap webinar HandoutPMIUKChapter
This document contains useful references/further reading identified during PMI UK webinar on 14 April 2020.
Prepared by Merv Wyeth
http://bit.ly/PMIUKBRMResults
In the context in which effective management and exploitation of information through IT is indispensable to achieve competitive advantage, the architecture provide a strategic tool for the evolution of the IT systems in response to the constantly changing needs of the business environment.
This presentation focus on the main processes and roles of an effective architecture capability within an organisation.
Please feel free to add comments to it.
Zinnov examines the growing trend of enterprises setting up digital labs to drive the next leg of their digital journey. Geographies with rich product development capabilities and a talent pool with key skills are emerging as hot spots for the establishment of innovative digital labs
For Companies who want to build agile networks, the Digital Team Platform delivers Digital Leadership Capabilities which enables dynamic value creation trough the collective intelligence of cross-boundary interactions and cooperation.
LACE Project WP5 - Learning Analytics & Performance Support for Manufacturing...Fabrizio Cardinali
Presented by Fabrizio Cardinali at the Kick off of LACE Project (www.laceproject.eu), support action for learning analytics commuinity exchange. WP5 deals with promoting best practices and solutions for performance support and learning analytics in the industrial training mrketplace and manufacturing in particular
CD4ML - ThoughtWorks MeetUp Munich Christoph Windheuser May 8th 2019Christoph Windheuser
These are the slides of Christoph Windheuser at the MeetUp at ThoughtWorks in Munich on May 8th, 2019. Christoph spoke about how to build up a Continuous Delivery (CD) framework for Machine Learning and Data Science applications in the industry.
Additive Manufacturing
How do we shift paradigms and build new business models? In this presentation Mitch Free, a serial entrepreneur, shares experiences from CNC machining to launching two digital manufacturing companies. Find out the current state of additive manufacturing and how these concepts can be used to drive new business models.
Mitch Free, Founder, Chairman, and CEO of Fast Radius and ZYCI CNC Machining
From the 2017 Supply Chain Insights Global Summit
Sustainable manufacturing with AI
Improve your processes:
Defect detection to reduce waste
Predictive maintenance to improve energy efficiency
Generative design to reduce materials used in products
Process optimisation to improve energy usage
Inventory optimisation to reduce materials held
Improve your IT:
Go paperless
Move to carbon neutral clouds
Adopt green software products
Optimise your compute usage
Improve with Nightingale HQ
We’re doing bespoke and pilot projects with manufacturers and adjacent industries. Make your business more sustainable.
bit.ly/nhqaichat
Verbundprojekt im KMU-Instrument - Frische Einblicke in den AntragsprozessSimon Dierks
Tobias Dochow, Project Manager bei Sensorberg GmbH, beschreibt das Verbundprojekt im Bereich 'Smart Hospital', das mit dem Klinikum und der Universität Braunschweig realisiert werden soll und gibt frische Einblicke in den Antragsprozess.
Continuous Intelligence: Keeping Your AI Application in Production (NDC Sydne...Dr. Arif Wider
A talk about applying Continuous Delivery to Machine Learning (CD4ML) presented by Arif Wider from ThoughtWorks at NDC Sydney Conference 2019.
Abstract:
It is already challenging to transition a machine learning model or AI system from the research space to production, and maintaining that system alongside ever-changing data is an even greater challenge. In software engineering, Continuous Delivery practices have been developed to ensure that developers can adapt, maintain, and update software and systems cheaply and quickly, enabling release cycles on the scale of hours or days instead of weeks or months. Nevertheless, in the data science world Continuous Delivery is rarely been applied holistically.
This is partly due to different workflows: data scientists regularly work on whole sets of hypotheses, whereas software engineers work more linearly even when evaluating multiple implementation alternatives. Therefore, existing software engineering practices cannot be applied as-is to machine learning projects. Learn how we used our expertise in both fields to adapt practices and tools to allow for Continuous Intelligence–the practice of delivering AI applications continuously.
[GE Innovation Forum 2015] The Industrial Internet by Bill RuhGE코리아
[GE Innovation Forum 2015] The Industrial Internet by Bill Ruh
The Industrial Internet by Bill Ruh
GE의 산업인터넷: 제 3차 산업혁명
GE글로벌소프트웨어 총괄 빌 루 부사장
GE’s Industrial Internet: the 3rd Industrial Revolution
by Bill Ruh, Vice President, GE Global Software
GE코리아 뉴스레터를 구독하세요! http://goo.gl/IE8WS8
GE코리아 YouTube 채널을 구독하세요! http://goo.gl/M2gc8m
상상을 현실로 만듭니다. Imagination at work.
GE가 꿈꾸는 가치입니다. 아니, GE는 단지 꿈만 꾸고 있는 것이 아닙니다. 상상을 현실로 만들기 위해, 불가능했던 것을 가능하게 만들기 위해 쉬지 않고 움직이고 있습니다. GE는 에너지, 의료, 항공, 수송, 금융 등의 여러 분야에서 고객과 인류사회의 진보를 위해 더 편리하고 빠르며 친환경적인 솔루션을 찾아냅니다.
Connect with GE Online:
GE코리아 웹사이트: http://www.ge.com/kr/
GE리포트코리아: http://www.gereports.kr/
GE코리아 페이스북 페이지: hhttps://www.facebook.com/GEKorea
GE코리아 슬라이드쉐어: http://www.slideshare.net/GEKorea
Continuous Intelligence: Moving Machine Learning into Production ReliablyDr. Arif Wider
A workshop by Danilo Sato, Christoph Windheuser, Emily Gorcenski, and Arif Wider, given at Strata Data Conference 2019 in London.
Abstract:
So you want to include a machine learning component in your IT systems? The process is a little more involved than clicking through an AI tutorial on your laptop. It’s not just the first working model you run that you need to consider; you also need to think about things like integration, scaling, and testing. What’s more, postlaunch, you’ll want to continuously adapt your model to respond to the changing environment.
ThoughtWorks pioneered continuous delivery—a set of tools and processes that ensure that software under development can be reliably released to production at any time and with high frequency.
Danilo Sato and Christoph Windheuser demonstrate how to apply continuous delivery to machine learning—what’s known as continuous intelligence. In a live scenario, you’ll change a machine learning model in a development environment, test its new performance, and, depending on the outcome, automatically deploy the new model into a production environment. The tech stack for this scenario will be Python, DVC (Data Science Version Control), and GoCD.
A roundtable discussion on various CRM models from the Creative Industries Clusters Programme Award Holders Workshop held in Belfast in February 2019. Session facilitated by Nicola Osborne, Programme Manager and Michaela Turner, Business Development Manager for Creative Informatics at the University of Edinburgh.
Continuous Intelligence: Keeping your AI Application in ProductionDr. Arif Wider
A talk by Emily Gorcenski and Arif Wider presented a Strata Data Conference 2019 in London.
Abstract:
It’s already challenging to transition a machine learning model or AI system from the research space to production, and maintaining that system alongside ever-changing data is an even greater challenge. In software engineering, continuous delivery practices have been developed to ensure that developers can adapt, maintain, and update software and systems cheaply and quickly, enabling release cycles on the scale of hours or days instead of weeks or months.
Nevertheless, in the data science world, continuous delivery is rarely applied holistically—due in part to different workflows: data scientists regularly work on whole sets of hypotheses, whereas software engineers work more linearly even when evaluating multiple implementation alternatives. Therefore, existing software engineering practices cannot be applied as is to machine learning projects.
Arif Wider and Emily Gorcenski explore continuous delivery (CD) for AI/ML along with case studies for applying CD principles to data science workflows. Join in to learn how they drew on their expertise to adapt practices and tools to allow for continuous intelligence—the practice of delivering AI applications continuously.
Hendrik Witt (Ubimax GmbH) Enterprise Smartglasses ProjectsAugmentedWorldExpo
Rapidly changing innovation cycles and growing complexity & variance require flexible and efficient technologies in the Enterprise business processes. On the path towards Industry 4.0, Wearable Computing is increasingly playing a crucial role in the field of the human-machine interfaces. As a leading provider for Wearable Computing solutions Ubimax is facing those industry challenges and offers a worldwide unique portfolio of proven Smart Glass solutions within its “Enterprise Wearable Computing Suite”. Based on state-of-the-art Augmented Reality and Smart Glasses technology, Ubimax’ customers like Daimler, DHL, Schnellecke Logistics, Samsung or Volkswagen are already working with those innovative and award-winning solutions in their production environments – achieving performance increases of up to 40%! In his talk, Ubimax CEO Dr. Hendrik Witt provides exclusive insights into selected Wearable Computing projects and answers the question of how the Industry 4.0 requirements can be countered with Augmented Reality and hands-free Wearable Computing solutions – with main focus on the existing benefits and future potential of this technology for Enterprises.
CWIN17 Toulouse / Business that rely on data stax enterprise make smart decis...Capgemini
Data comes from different geographical locations and across multiple channels.
Managing this explosion of high velocity dynamic data while maintaining
customer privacy is a challenge with legacy systems.
Rely on the database designed for the age of the Internet of Things.
DataStax is built from the ground up to consume time-series and sensor-based
information faster than any other database. Easily add scale and capacity while
maintaining 100% uptime – no matter what. Search and analyze information to
deliver mind blowing experiences that will drive engagement and growth
BRM - Bridging the gap webinar HandoutPMIUKChapter
This document contains useful references/further reading identified during PMI UK webinar on 14 April 2020.
Prepared by Merv Wyeth
http://bit.ly/PMIUKBRMResults
In the context in which effective management and exploitation of information through IT is indispensable to achieve competitive advantage, the architecture provide a strategic tool for the evolution of the IT systems in response to the constantly changing needs of the business environment.
This presentation focus on the main processes and roles of an effective architecture capability within an organisation.
Please feel free to add comments to it.
Zinnov examines the growing trend of enterprises setting up digital labs to drive the next leg of their digital journey. Geographies with rich product development capabilities and a talent pool with key skills are emerging as hot spots for the establishment of innovative digital labs
For Companies who want to build agile networks, the Digital Team Platform delivers Digital Leadership Capabilities which enables dynamic value creation trough the collective intelligence of cross-boundary interactions and cooperation.
A Digital Enterprise is one that leverages customer, contextual and enterprise data and use new-age technologies to drive exponential business impact. To facilitate digital transformation, enterprises are increasingly setting up Digital Labs/Hubs in geographies with rich product capabilities, such as the Bay Area (US) and Bangalore (India).
For Businesses who want become a Smart Services Leader, TMG provides a Digital Improvement Program which drives dynamic value creation through the alignment of business models, organization, talents and infrastructure
What is Digital Transformation?
Digital transformation is the integration of digital technology into all areas of a business, fundamentally changing how you operate and deliver value to customers.
Digital transformation is imperative for all businesses, from the small to the enterprise.
Emerging technologies have become a key part of the discussion around modern digital organizations. Across the high-tech industry.
Digital transformation refers to the integration of digital technology into all areas of a business, resulting in fundamental changes to how the business operates and delivers value to customers. This process involves using technology to streamline processes, increase efficiency, improve customer experiences, and create new business models. It often involves rethinking and redesigning the way products and services are delivered, how employees work, and how data is collected and utilized. Digital transformation can help companies stay competitive in an increasingly digital world and enable them to better adapt to changing customer needs and market conditions.
Why Digital Transformation?
Improved efficiency: Digital transformation can help businesses streamline their processes, automate routine tasks, and reduce manual errors. This can lead to increased efficiency and productivity, allowing employees to focus on higher-value tasks.
Enhanced customer experiences: Digital transformation can enable businesses to better understand their customers and their needs, and provide personalized experiences that meet those needs. This can lead to increased customer satisfaction and loyalty.
Increased agility: Digital transformation can make businesses more agile and responsive to changes in the market and customer needs. By using data and analytics to inform decision-making, businesses can quickly adapt to new challenges and opportunities.
New business models: Digital transformation can enable businesses to create new business models and revenue streams, such as subscription-based services or digital marketplaces. This can open up new opportunities for growth and innovation.
Key Components of Digital Transformation
Customer Experience
Business Processes
Data Analytics
Innovation and New Business Models
Employee Empowerment
Organizational Culture
Security and Risk Management
Strategy and Leadership
Culture Change and Communication
Optimizing Processes
Data
Need for Digital Transformation
Accelerating change
Digital competition
Changing Customer Expectations
Digital adoption
Data-Driven Insights
Operational Efficiency
Talent Acquisition and Retention
Regulatory Compliance
Overall, digital transformation is needed to enable organizations to stay competitive, improve customer experience, drive growth, and improve operational efficiency. By embracing digital transformation, organizations can create a culture of innovation and agility that enables them to adapt to changing market conditions and to seize new opportunities.
ETDP 2015 D1 SMAC & the Journey from Automation to Digital Factory - Snjeev K...Comit Projects Ltd
COMIT/Fiatech Conference 2015, Hallam, London
Sanjeev Kapoor, Senior Project Manager, Emerging Technologies, Ford Motor Company
Note: This presentation is an amalgam of the two presentations in the agenda.
• Introduction to Manufacturing Automation, Digital Factory and Industry
• Smarter, safer robots bringing automation in manufacturing industry
• The Digital Factory Lifecycle and Case Studies
• How Digital Factory has positively impacted manufacturers enabling them to produce
Faster, Cheaper and Better Products
• Difference between “looking digital and being digital”
• The DNA of a Digital Enterprise & how Digital Factory is enabling Digital Industry
What is SMAC (Social, Mobile, Analytics and Cloud)?
• Key Trends in Social, Mobile, Analytics and Cloud Technologies
• How SMAC Technologies collectively can digitally transform your organization?
• Case Studies – How organizations across industries are leveraging SMAC Technologies for innovation and business growth?
• Future of SMAC Technologies
This presentation was held by Professor Christine Legner (HEC Lausanne) at the Swiss Day on November 8, 2017, in Lausanne, Switzerland. It addresses the need for organisations to think about data and its management in new ways, as many corporations engage in the digital and data-driven transformation of their business. It concludes with three recommendations: 1) assess data's business value and impact, 2) measure and improve data quality, and 3) democratize data and support data citizenship.
Delivering on Digital - The innovations and technologies that are transformin...Deloitte Australia
www2.deloitte.com/au/en/pages/public-sector/articles/delivering-on-digital.html
We now have the digital tools (cloud computing, mobile devices, analytics) and the talent to stage a real transformation in government. A digital mindset is a different way of thinking about customers, products, and process. It’s faster, iterative, and adaptable. And if government adopts it, the changes can be just as revolutionary. This book provides the handbook to make it happen.
To understand the different recruitment strategies adopted by the organization
To determine how sourcing of employees is done in the organization
To assess the importance of recruitment and selection in the HRM
To analyze the challenges encountered by the recruiters and the employees while recruitment.
Ben Peace, Knowledge Transfer Manager - Sustainable Manufacture, at the KTN presented on the funding opportunities available through Innovate UK and the Knowledge Transfer Network
More from WMG centre High Value Manufacturing Catapult (7)
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
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
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During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
2. Collaborate. Innovate. Deploy.
Our
Mission
As an independent institute, we collaborate
with manufacturers, other academic
institutes and solution providers to
deploy innovative technologies,
tools and methods to support
the manufacturing
sector.
Our
Vision
To lead in providing
outstanding value and
knowledge for sustainable
manufacturing
5. Collaborate. Innovate. Deploy.
How has we the concept developed?
TO DATE:
• Talked to stakeholders, both industrial and academic
• Held a workshop through the Digital Engineering and Test Centre Programme
(DETC)
• Refined through contact and internal workshops
• Engagement with the Digital Catapult (Manufacturing is a key work stream)
NEXT:
• Create a wider steering group
• Gain greater support and mass
• Feedback loop
• Qualitative testing of the model
6. Collaborate. Innovate. Deploy.
Digital Readiness Level (for manufacturing)
Vision:
• To provide UK Manufacturing with a consistent
technology and process based measure to assess the
digital preparedness of a company or production facility
• A design a measure that is widely applied and utilised
based on sound research and experience
• A measure that challenges toward the best, irrespective
of size (or sector), and delivers with a fast pace of change
7. Collaborate. Innovate. Deploy.
Digital Readiness Level (for manufacturing)
Objectives:
1. To give context to the Industry 4.0, Factory of the Future, Digital
Manufacturing landscape to a wide range of manufacturing businesses
2. To create a clear platform for communication – digital needs
consistency of language and style to be understood, discussed,
interpreted, developed and deployed
3. To identify value from digital in manufacturing – focus to deliver the
productivity and process improvements of up to 20 per cent
generically discussed
4. To be seen in the same capacity as Technology Readiness Level (TRL)
and Manufacturing Readiness Level (MRL)
8. Collaborate. Innovate. Deploy.
How might the model work
The model will focus on a manufacturers:
A. Capabilities – Are the core capabilities needed to support Digital Readiness
present?
B. Competencies – Are certain competencies demonstrated under each
capability as evidence to support that capability?
C. Evaluators – A set of questions to assess competencies
Delivering a summary – a concise, key phrase development of each stage of
Digital Readiness Level (DRL)
9. Collaborate. Innovate. Deploy.
Capabilities
In its work so far HSSMI has identified six capabilities that combine to develop a platform for
Digital Readiness, these are:
1. Development of the business case process
2. Technical capability technical
3. Data management technical
4. Leadership process
5. People process and technical
6. Systems integration technical
These are a balance of process and technical – we need to assess to ensure we have got this
balance right
10. Collaborate. Innovate. Deploy.
Competencies
4. Leadership
A. Strategic direction
B. Partnerships for development
5. People
A. Skills and upskilling
B. Culture
6. Systems Integration
A. Supplier engagement
B. Customer engagement
C. Internal integration management
1. Development of the Digital business case
A. Identifying value from Digital
B. Commercialising benefits of Digital
2. Technical capability
A. Development and testing tools (virtual)
B. Equipment infrastructure (physical)
3. Data Management
A. Data usage strategy
B. Ownership and control of data
Within each of the capabilities two or three competencies have been identified to support the capability:
11. Collaborate. Innovate. Deploy.
Developing DRL
Through or work at the Advanced
Propulsion Centre Digital Spoke
we have a set of inputs that will
help HSSMI define the
competences and question sets
for Digital Readiness Level
12. Collaborate. Innovate. Deploy.
A progressive and parallel change in attitude
1. Development of the business case
2. Technical capability
3. Data management
4. Leadership
5. People
6. Systems integration
1 2 3 4
Readiness
levels are
based on
business
challenges
and can be
used to
highlight and
action issues
horizontally,
they are not
system or
vertical
based
system
approached
Awareness of
machine data
Full machine
connectivity
All resources
linked
Machine and
assets connected
External use of RFID
track & trace
Links to Suppliers
in place
Prognostic
maintenance
13. Collaborate. Innovate. Deploy.
Examples of Value - People and Data Management
New skills (IT, programming,
Virtual tools)
New ways of working –
Collaboration internally and
externally
Companies to be attractive to new
employees from other sectors
Data sharing between various
departments
Data sharing with the supply chain
New approach to data protection whilst
still maintaining confidentiality and IP
security
Value of data / information becomes
more important
“Data only” companies will enter
manufacturing
14. Collaborate. Innovate. Deploy.
Examples - stretching the Technical Capabilities for Digital
Level 1: Data capture – Capture of data related to machines,
production performance, facilities and operator across the
value chain
Level 2: Connectivity and visualisation – Connect the relevant
data to create a “single source of truth” / digitally map the
production processes with the digital representation
Level 3: Interpretation – big data, data analytics for production
planning, maintenance, training
Level 4: Pre-emptive decision making / new business
opportunities – production scheduling, “self-healing” or self-
maintaining system, …
15. 15
Comparison of dimensions
Non technical dimensions
Strategy and organisation
• Strategy
• Investments
• Innovation management
Employees
• Employees skill set
• Skill acquisition
Leadership
• Strategic direction
• Partnerships
People
• Skills and upskilling
• Culture
Development of the business case
• Identifying value of digital
• Commercialising benefits of digital
I4.0 readiness model Digital readiness model
16. 16
Comparison of dimensions
Technology dimensions
Smart factory
• Digital modelling
• Equipment infrastructure
• Data usage
• IT systems
Smart products
• ICT add-on
functionalities
• Data analytics in usage
phase
Technical dimension
• Development and Testing
• Tools and Technology
Data management
• Usage of Data
• Ownership and Control
System integration
• Supply chain engagement
• Customer engagement
• Internal integration
I4.0 readiness model
Digital readiness model
Data-driven services
• Data driven services
• Shares of revenue
• Share of data used
Smart operations
• Cloud usage
• IT security
• Autonomous processes
• Information sharing