www.kantanmt.com.
Tony O’Dowd discusses the major developments in Machine Translation over the last few years with a particular focus on measurement technologies.
In the past, users of Machine Translation have had considerable difficulty in pre-evaluating the quality of their Machine Translation output. This has led to industry confusion with regards to both post editing pricing and client Machine Translation project pricing. Speaking about the ‘confidence scoring’ technology which has been co-developed with CNGL, Tony illustrates how LSPs and other users of Machine Translation can now accurately predict the quality of their Machine Translation output on a segment by segment basis.
Dokumen tersebut membahas tentang Windows Vista, sistem operasi dari Microsoft. Windows Vista merupakan sistem operasi berbasis grafis yang diluncurkan pada 2006 untuk menggantikan Windows XP. Windows Vista hadir dengan antarmuka baru bernama Windows Aero yang memiliki tampilan transparan dan animasi serta memerlukan spesifikasi tinggi. Dokumen ini juga membahas edisi-edisi Windows Vista beserta persyaratannya.
The document discusses AJAX and jQuery's AJAX methods. It defines AJAX as Asynchronous JavaScript and XML, which allows for asynchronous requests to a server without interrupting other browser tasks. It describes why AJAX is used to improve user experience by allowing asynchronous partial page updates. It then summarizes jQuery's main AJAX methods like $.ajax(), $.get(), $.post(), $.load(), and their parameters. It also discusses AJAX events in jQuery like ajaxComplete() and how data can be passed to the server.
This document provides tips for proper telephone etiquette when answering calls at the university, including speaking clearly, not eating while on calls, asking permission before putting callers on hold, identifying yourself when answering, thanking callers for waiting, taking complete messages, and using courteous language. The key is to treat callers with courtesy to represent your department professionally.
Dokumen tersebut membahas tentang tugas mata kuliah, virus komputer, cara kerja virus, jenis-jenis virus, cara mengatasi virus, antivirus, dan cara instalasi serta update antivirus Norton.
Dokumen tersebut membahas tentang Windows Vista, sistem operasi dari Microsoft. Windows Vista merupakan sistem operasi berbasis grafis yang diluncurkan pada 2006 untuk menggantikan Windows XP. Windows Vista hadir dengan antarmuka baru bernama Windows Aero yang memiliki tampilan transparan dan animasi serta memerlukan spesifikasi tinggi. Dokumen ini juga membahas edisi-edisi Windows Vista beserta persyaratannya.
The document discusses AJAX and jQuery's AJAX methods. It defines AJAX as Asynchronous JavaScript and XML, which allows for asynchronous requests to a server without interrupting other browser tasks. It describes why AJAX is used to improve user experience by allowing asynchronous partial page updates. It then summarizes jQuery's main AJAX methods like $.ajax(), $.get(), $.post(), $.load(), and their parameters. It also discusses AJAX events in jQuery like ajaxComplete() and how data can be passed to the server.
This document provides tips for proper telephone etiquette when answering calls at the university, including speaking clearly, not eating while on calls, asking permission before putting callers on hold, identifying yourself when answering, thanking callers for waiting, taking complete messages, and using courteous language. The key is to treat callers with courtesy to represent your department professionally.
Dokumen tersebut membahas tentang tugas mata kuliah, virus komputer, cara kerja virus, jenis-jenis virus, cara mengatasi virus, antivirus, dan cara instalasi serta update antivirus Norton.
This document discusses the pros and cons of statistical machine translation (SMT) and neural machine translation (NMT) for translation service providers and their clients. While NMT produces more fluent translations, it is harder to control and needs extensive testing, making SMT more predictable. MT can help increase translator productivity but only if the right conditions are met, such as content suited to MT, sufficient volume, and supportive workflows. Overall, MT is best viewed as a tool to aid translators rather than replace them, and human factors like motivation and compensation are important to realize any productivity gains.
The document discusses the development of KantanNeuralTM, a neural machine translation platform. It describes how the time to build neural machine translation engines has decreased from 4 weeks to 4 days to potentially 4 hours. The platform allows users to build, improve, and deploy their own neural machine translation engines through an easy-to-use interface. The system also supports seamless switching between statistical and neural machine translation methods.
Dr. Dimitar Shterionov (KantanLabs) and Laura Casanellas (KantanMT Professional Services) presented very interesting results gleaned from a comparative ranking of Neural and Statistical MT systems. These systems were developed with KantanMT and ranked using the KantanLQR quality evaluation platform. As ranked by Professional Translators, Neural MT demonstrated clear quality improvements in terms of fluency and adequacy compared to equivalent statistical based outputs.
Tony (Chief Architect, KantanMT.com) opens the proceedings with a temporal look at how MT technology has progressed. While embracing Rule Based MT in the 1970s, the industry switched over to Statistical MT around 2002 and is now faced with a new paradigm of Neural MT in 2016. For each technology progression, improved translation quality and fluency were achieved.
Summary: https://www.youtube.com/watch?v=19yyDa6mAsc
Full video: https://www.youtube.com/watch?v=EtbML0DTNHk
2017 will see the emergence of Machine Translation 2.0, and KantanNeural signals a giant step towards using cutting-edge technology to improve automated translation accuracy and increase productivity.
In this webinar, Tony provides an overview of KantanNeural and discuss how users can translate documents using NMT. He discusses how to evaluate the translation quality of the NMT engines with the new A/B testing feature on KantanLQR™. Dimitar briefly talks about the benefits of translating using Neural technology and the future development plans for NMT at KantanLabs.
YouTube: https://youtu.be/_2yIZxVqqmw
This webinar will discuss connecting machine translation systems to various CAT tools, the benefits of customized MT systems such as instant deployment and support, and how to involve reviewers in the MT process to improve quality. It will also cover topics such as how many users can access the MT system, what types of content are best for MT, options for customers without sufficient translation memories, and various pricing models.
ATC Summit 2016: The 7th Habit of 7 Habits of Effective MT Systemskantanmt
Translation quality management is key for Project Managers to improving the translation process. Producing high quality translations from the start of projects will reduce costs and improve speed to market.
When considering automated translation, we think of automatic metrics, such as BLEU, F-Measure and TER and how they can correlate with the translation quality. However, the step of reviewing translation output for MT engine retraining is still a very manual process incorporating multiple iterations of excel documents. In this presentation, Brian will discuss how the process can be automated and the impact automation will have on reducing costs and increasing translation productivity.
Cross Border Selling: Breaking the Language Barrier with Automated Translationkantanmt
This document summarizes a webinar about using machine translation (MT) for cross-border e-commerce. It discusses how MT can help businesses sell across borders by overcoming language barriers. Specific benefits mentioned include faster translation to new markets, leveraging back catalogues to increase sales, improving communication to reduce costs, and providing auto-usable translations directly on websites. Case studies demonstrate productivity gains and cost savings when using MT for e-commerce catalogues and customer support.
Go global with this Winning Combination – Content strategy and Machine Transl...kantanmt
Reaching customers in new target locales requires an enterprise-wide content strategy that will circumvent language and cultural barriers, fit seamlessly into existing content workflows and not break the bank.
In this webinar Brian discusses how to develop a flawless content strategy by bringing the power of Custom Machine Translated content in the mix.
YouTube link: https://youtu.be/HG8-9vlKZkk
Webinar automotive and engineering content 16.06.16kantanmt
High quality translations that are delivered quickly are a result of a seamless and efficient translation process, but getting to this stage requires a well thought out plan, rigorous content preprocessing techniques and most importantly, clear and transparent communication between the automated translation vendor and language service provider.
In this webinar, Christian Taube and Brian Coyle discusses how the Matrix and KantanMT partnership delivers a high quality, scalable solution that increases translation productivity and supports engineering and automotive terminology standards. The webinar uses specific case study examples including a discussion on what types of content to focus on and preparing and managing Translation Memory data. Discussion includes:
• Managing content for best results
• Preparing TM data
• Tools that generate high quality results
Cloud computing in its various forms can offer significant business advantages for companies large and small. However, for companies considering moving their operations to the cloud many options exist and choices can be confusing and challenging. Not least of the many concerns are those about security and safety of data and indeed cloud computing poses both opportunity and risk in this regard. With the goal of drawing back the curtain on cloud security and helping companies make more informed choices on their cloud security posture IC4 is hosted a workshop on the challenges and opportunities of cloud security.
During this workshop, Dr Dimitar Shterionov, Machine Translation Researcher in KantanMT, presented a case study on the topic of cloud security and how it is implemented in a real-world business scenario.
New Ways to Engage Clients with Custom Machine Translationkantanmt
Brian Coyle, Chief Commercial Officer at KantanMT talks about the solid benefits of integrating a powerful Machine Translation tool in a localization project. He shares measurable and significant market facts and figures in order to discuss how Custom Machine Translation engines are a cut above broad-based MT systems. Brian goes on to discuss some of the main features that any scalable, powerful MT system must include in order to improve translation productivity for projects, and by extension to increase the returns for LSP clients.
Learning outcome:
• How Custom Machine Translation will help LSPs improve and enhance their service offerings
• The tangible quantitative benefits of integrating MT within the translation workflow
• What are the “must-have features” to look for when identifying a suitable MT system
• The webinar will empower Project Managers by providing them with information and industry insights that can be utilised to pitch projects to enterprise clients, and thereby bring bigger projects to the table
Improving your Bottom Line with Custom Machine Translationkantanmt
KantanMT’s Chief Commercial Officer, Brian Coyle provides in-depth insights into the growing Machine Translation (MT) industry, including the benefits of integrating Custom MT into existing workflows to generate exceptional localization cost savings by reducing translation time and increasing productivity.
This presentation is relevant to anyone selling products and services in global markets, or those who aim to enter newer markets fast, before their competitors.
You will learn:
• About the necessity of Machine Translation to be competitive
• Quantitative benefits of integrating MT within the Localization workflow
• What questions to ask your Localization Partner when choosing an MT system
How to Achieve Agile Localization for High-Volume Content with Machine Transl...kantanmt
This slide deck on achieving agile localization for high-volume content with the help of Machine Translation was presented by Tony O’Dowd, Founder and Chief Architect at KantanMT during the annual tcworld conference 2015, which was held in Stuttgart, Germany. It outlines the best practices for developing and implementing a dynamic and agile localization strategy that integrates Custom Machine Translation (CMT) into the localization workflow, with the final aim of developing a scalable localization strategy that makes it possible to create and publish high-volume multilingual content.
KantanMT Founder and Chief Architect, Tony O'Dowd and Technical Project Manager, Louise Faherty show you how to improve the translation productivity of your team, manage post-editing effort and translation project schedules better with powerful Machine Translation engines.
You will learn:
• How to deal with Translation challenges
• About the necessity of Machine Translation to be competitive
• How KantanMT.com can be integrated with existing Translation Management Systems
How to save 16 million euro for your start up businesskantanmt
The document discusses KantanMT, a statistical machine translation platform. It provides an overview of KantanMT's capabilities including being cloud-based, scalable, and providing high-quality translations through fusion of translation memory, machine translation, and rules. The document then discusses KantanMT's journey and growth, leveraging the cloud to maximize performance and availability while minimizing costs. It highlights how the cloud provides abundant and elastic computing resources to power KantanMT's machine translation engines.
What is the Economic Case for Machine Translation?kantanmt
Machine Translation (MT) is a productivity tool in the production workflow with the potential to significantly boost a company’s economic performance. In today’s world, one of the greatest challenges an organisation faces is how to increase profits when revenue streams become saturated.
This presentation covers the economic arguments in favour of including Machine Translation into existing content production workflows.
For more information about KantanMT.com, or to sign up to the platform, contact us (sales@kantanmt.com).
Tips for Preparing Training Data for High Quality Machine Translationkantanmt
This document discusses tips for preparing high quality training data for machine translation systems. It covers:
- The key factors that influence training data quality are quantity, quality, and relevance to the domain. Balancing these is important.
- Suitable training data sources include translation memories, terminology databases, and client translated documents.
- Statistical machine translation systems use bilingual and monolingual data to form patterns and map source to target language. Additional data and rules can improve accuracy.
- Data preparation includes preprocessing, training the translation and language models, and postprocessing. Ensuring data is clean, normalized, and domain relevant improves results.
What is an RPA CoE? Session 1 – CoE VisionDianaGray10
In the first session, we will review the organization's vision and how this has an impact on the COE Structure.
Topics covered:
• The role of a steering committee
• How do the organization’s priorities determine CoE Structure?
Speaker:
Chris Bolin, Senior Intelligent Automation Architect Anika Systems
This document discusses the pros and cons of statistical machine translation (SMT) and neural machine translation (NMT) for translation service providers and their clients. While NMT produces more fluent translations, it is harder to control and needs extensive testing, making SMT more predictable. MT can help increase translator productivity but only if the right conditions are met, such as content suited to MT, sufficient volume, and supportive workflows. Overall, MT is best viewed as a tool to aid translators rather than replace them, and human factors like motivation and compensation are important to realize any productivity gains.
The document discusses the development of KantanNeuralTM, a neural machine translation platform. It describes how the time to build neural machine translation engines has decreased from 4 weeks to 4 days to potentially 4 hours. The platform allows users to build, improve, and deploy their own neural machine translation engines through an easy-to-use interface. The system also supports seamless switching between statistical and neural machine translation methods.
Dr. Dimitar Shterionov (KantanLabs) and Laura Casanellas (KantanMT Professional Services) presented very interesting results gleaned from a comparative ranking of Neural and Statistical MT systems. These systems were developed with KantanMT and ranked using the KantanLQR quality evaluation platform. As ranked by Professional Translators, Neural MT demonstrated clear quality improvements in terms of fluency and adequacy compared to equivalent statistical based outputs.
Tony (Chief Architect, KantanMT.com) opens the proceedings with a temporal look at how MT technology has progressed. While embracing Rule Based MT in the 1970s, the industry switched over to Statistical MT around 2002 and is now faced with a new paradigm of Neural MT in 2016. For each technology progression, improved translation quality and fluency were achieved.
Summary: https://www.youtube.com/watch?v=19yyDa6mAsc
Full video: https://www.youtube.com/watch?v=EtbML0DTNHk
2017 will see the emergence of Machine Translation 2.0, and KantanNeural signals a giant step towards using cutting-edge technology to improve automated translation accuracy and increase productivity.
In this webinar, Tony provides an overview of KantanNeural and discuss how users can translate documents using NMT. He discusses how to evaluate the translation quality of the NMT engines with the new A/B testing feature on KantanLQR™. Dimitar briefly talks about the benefits of translating using Neural technology and the future development plans for NMT at KantanLabs.
YouTube: https://youtu.be/_2yIZxVqqmw
This webinar will discuss connecting machine translation systems to various CAT tools, the benefits of customized MT systems such as instant deployment and support, and how to involve reviewers in the MT process to improve quality. It will also cover topics such as how many users can access the MT system, what types of content are best for MT, options for customers without sufficient translation memories, and various pricing models.
ATC Summit 2016: The 7th Habit of 7 Habits of Effective MT Systemskantanmt
Translation quality management is key for Project Managers to improving the translation process. Producing high quality translations from the start of projects will reduce costs and improve speed to market.
When considering automated translation, we think of automatic metrics, such as BLEU, F-Measure and TER and how they can correlate with the translation quality. However, the step of reviewing translation output for MT engine retraining is still a very manual process incorporating multiple iterations of excel documents. In this presentation, Brian will discuss how the process can be automated and the impact automation will have on reducing costs and increasing translation productivity.
Cross Border Selling: Breaking the Language Barrier with Automated Translationkantanmt
This document summarizes a webinar about using machine translation (MT) for cross-border e-commerce. It discusses how MT can help businesses sell across borders by overcoming language barriers. Specific benefits mentioned include faster translation to new markets, leveraging back catalogues to increase sales, improving communication to reduce costs, and providing auto-usable translations directly on websites. Case studies demonstrate productivity gains and cost savings when using MT for e-commerce catalogues and customer support.
Go global with this Winning Combination – Content strategy and Machine Transl...kantanmt
Reaching customers in new target locales requires an enterprise-wide content strategy that will circumvent language and cultural barriers, fit seamlessly into existing content workflows and not break the bank.
In this webinar Brian discusses how to develop a flawless content strategy by bringing the power of Custom Machine Translated content in the mix.
YouTube link: https://youtu.be/HG8-9vlKZkk
Webinar automotive and engineering content 16.06.16kantanmt
High quality translations that are delivered quickly are a result of a seamless and efficient translation process, but getting to this stage requires a well thought out plan, rigorous content preprocessing techniques and most importantly, clear and transparent communication between the automated translation vendor and language service provider.
In this webinar, Christian Taube and Brian Coyle discusses how the Matrix and KantanMT partnership delivers a high quality, scalable solution that increases translation productivity and supports engineering and automotive terminology standards. The webinar uses specific case study examples including a discussion on what types of content to focus on and preparing and managing Translation Memory data. Discussion includes:
• Managing content for best results
• Preparing TM data
• Tools that generate high quality results
Cloud computing in its various forms can offer significant business advantages for companies large and small. However, for companies considering moving their operations to the cloud many options exist and choices can be confusing and challenging. Not least of the many concerns are those about security and safety of data and indeed cloud computing poses both opportunity and risk in this regard. With the goal of drawing back the curtain on cloud security and helping companies make more informed choices on their cloud security posture IC4 is hosted a workshop on the challenges and opportunities of cloud security.
During this workshop, Dr Dimitar Shterionov, Machine Translation Researcher in KantanMT, presented a case study on the topic of cloud security and how it is implemented in a real-world business scenario.
New Ways to Engage Clients with Custom Machine Translationkantanmt
Brian Coyle, Chief Commercial Officer at KantanMT talks about the solid benefits of integrating a powerful Machine Translation tool in a localization project. He shares measurable and significant market facts and figures in order to discuss how Custom Machine Translation engines are a cut above broad-based MT systems. Brian goes on to discuss some of the main features that any scalable, powerful MT system must include in order to improve translation productivity for projects, and by extension to increase the returns for LSP clients.
Learning outcome:
• How Custom Machine Translation will help LSPs improve and enhance their service offerings
• The tangible quantitative benefits of integrating MT within the translation workflow
• What are the “must-have features” to look for when identifying a suitable MT system
• The webinar will empower Project Managers by providing them with information and industry insights that can be utilised to pitch projects to enterprise clients, and thereby bring bigger projects to the table
Improving your Bottom Line with Custom Machine Translationkantanmt
KantanMT’s Chief Commercial Officer, Brian Coyle provides in-depth insights into the growing Machine Translation (MT) industry, including the benefits of integrating Custom MT into existing workflows to generate exceptional localization cost savings by reducing translation time and increasing productivity.
This presentation is relevant to anyone selling products and services in global markets, or those who aim to enter newer markets fast, before their competitors.
You will learn:
• About the necessity of Machine Translation to be competitive
• Quantitative benefits of integrating MT within the Localization workflow
• What questions to ask your Localization Partner when choosing an MT system
How to Achieve Agile Localization for High-Volume Content with Machine Transl...kantanmt
This slide deck on achieving agile localization for high-volume content with the help of Machine Translation was presented by Tony O’Dowd, Founder and Chief Architect at KantanMT during the annual tcworld conference 2015, which was held in Stuttgart, Germany. It outlines the best practices for developing and implementing a dynamic and agile localization strategy that integrates Custom Machine Translation (CMT) into the localization workflow, with the final aim of developing a scalable localization strategy that makes it possible to create and publish high-volume multilingual content.
KantanMT Founder and Chief Architect, Tony O'Dowd and Technical Project Manager, Louise Faherty show you how to improve the translation productivity of your team, manage post-editing effort and translation project schedules better with powerful Machine Translation engines.
You will learn:
• How to deal with Translation challenges
• About the necessity of Machine Translation to be competitive
• How KantanMT.com can be integrated with existing Translation Management Systems
How to save 16 million euro for your start up businesskantanmt
The document discusses KantanMT, a statistical machine translation platform. It provides an overview of KantanMT's capabilities including being cloud-based, scalable, and providing high-quality translations through fusion of translation memory, machine translation, and rules. The document then discusses KantanMT's journey and growth, leveraging the cloud to maximize performance and availability while minimizing costs. It highlights how the cloud provides abundant and elastic computing resources to power KantanMT's machine translation engines.
What is the Economic Case for Machine Translation?kantanmt
Machine Translation (MT) is a productivity tool in the production workflow with the potential to significantly boost a company’s economic performance. In today’s world, one of the greatest challenges an organisation faces is how to increase profits when revenue streams become saturated.
This presentation covers the economic arguments in favour of including Machine Translation into existing content production workflows.
For more information about KantanMT.com, or to sign up to the platform, contact us (sales@kantanmt.com).
Tips for Preparing Training Data for High Quality Machine Translationkantanmt
This document discusses tips for preparing high quality training data for machine translation systems. It covers:
- The key factors that influence training data quality are quantity, quality, and relevance to the domain. Balancing these is important.
- Suitable training data sources include translation memories, terminology databases, and client translated documents.
- Statistical machine translation systems use bilingual and monolingual data to form patterns and map source to target language. Additional data and rules can improve accuracy.
- Data preparation includes preprocessing, training the translation and language models, and postprocessing. Ensuring data is clean, normalized, and domain relevant improves results.
What is an RPA CoE? Session 1 – CoE VisionDianaGray10
In the first session, we will review the organization's vision and how this has an impact on the COE Structure.
Topics covered:
• The role of a steering committee
• How do the organization’s priorities determine CoE Structure?
Speaker:
Chris Bolin, Senior Intelligent Automation Architect Anika Systems
AppSec PNW: Android and iOS Application Security with MobSFAjin Abraham
Mobile Security Framework - MobSF is a free and open source automated mobile application security testing environment designed to help security engineers, researchers, developers, and penetration testers to identify security vulnerabilities, malicious behaviours and privacy concerns in mobile applications using static and dynamic analysis. It supports all the popular mobile application binaries and source code formats built for Android and iOS devices. In addition to automated security assessment, it also offers an interactive testing environment to build and execute scenario based test/fuzz cases against the application.
This talk covers:
Using MobSF for static analysis of mobile applications.
Interactive dynamic security assessment of Android and iOS applications.
Solving Mobile app CTF challenges.
Reverse engineering and runtime analysis of Mobile malware.
How to shift left and integrate MobSF/mobsfscan SAST and DAST in your build pipeline.
Essentials of Automations: Exploring Attributes & Automation ParametersSafe Software
Building automations in FME Flow can save time, money, and help businesses scale by eliminating data silos and providing data to stakeholders in real-time. One essential component to orchestrating complex automations is the use of attributes & automation parameters (both formerly known as “keys”). In fact, it’s unlikely you’ll ever build an Automation without using these components, but what exactly are they?
Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
You’ll leave this webinar with a better understanding of how to maximize the potential of automations by making use of attributes & automation parameters, with the ultimate goal of setting your enterprise integration workflows up on autopilot.
High performance Serverless Java on AWS- GoTo Amsterdam 2024Vadym Kazulkin
Java is for many years one of the most popular programming languages, but it used to have hard times in the Serverless community. Java is known for its high cold start times and high memory footprint, comparing to other programming languages like Node.js and Python. In this talk I'll look at the general best practices and techniques we can use to decrease memory consumption, cold start times for Java Serverless development on AWS including GraalVM (Native Image) and AWS own offering SnapStart based on Firecracker microVM snapshot and restore and CRaC (Coordinated Restore at Checkpoint) runtime hooks. I'll also provide a lot of benchmarking on Lambda functions trying out various deployment package sizes, Lambda memory settings, Java compilation options and HTTP (a)synchronous clients and measure their impact on cold and warm start times.
Session 1 - Intro to Robotic Process Automation.pdfUiPathCommunity
👉 Check out our full 'Africa Series - Automation Student Developers (EN)' page to register for the full program:
https://bit.ly/Automation_Student_Kickstart
In this session, we shall introduce you to the world of automation, the UiPath Platform, and guide you on how to install and setup UiPath Studio on your Windows PC.
📕 Detailed agenda:
What is RPA? Benefits of RPA?
RPA Applications
The UiPath End-to-End Automation Platform
UiPath Studio CE Installation and Setup
💻 Extra training through UiPath Academy:
Introduction to Automation
UiPath Business Automation Platform
Explore automation development with UiPath Studio
👉 Register here for our upcoming Session 2 on June 20: Introduction to UiPath Studio Fundamentals: https://community.uipath.com/events/details/uipath-lagos-presents-session-2-introduction-to-uipath-studio-fundamentals/
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor IvaniukFwdays
At this talk we will discuss DDoS protection tools and best practices, discuss network architectures and what AWS has to offer. Also, we will look into one of the largest DDoS attacks on Ukrainian infrastructure that happened in February 2022. We'll see, what techniques helped to keep the web resources available for Ukrainians and how AWS improved DDoS protection for all customers based on Ukraine experience
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
The Department of Veteran Affairs (VA) invited Taylor Paschal, Knowledge & Information Management Consultant at Enterprise Knowledge, to speak at a Knowledge Management Lunch and Learn hosted on June 12, 2024. All Office of Administration staff were invited to attend and received professional development credit for participating in the voluntary event.
The objectives of the Lunch and Learn presentation were to:
- Review what KM ‘is’ and ‘isn’t’
- Understand the value of KM and the benefits of engaging
- Define and reflect on your “what’s in it for me?”
- Share actionable ways you can participate in Knowledge - - Capture & Transfer
LF Energy Webinar: Carbon Data Specifications: Mechanisms to Improve Data Acc...DanBrown980551
This LF Energy webinar took place June 20, 2024. It featured:
-Alex Thornton, LF Energy
-Hallie Cramer, Google
-Daniel Roesler, UtilityAPI
-Henry Richardson, WattTime
In response to the urgency and scale required to effectively address climate change, open source solutions offer significant potential for driving innovation and progress. Currently, there is a growing demand for standardization and interoperability in energy data and modeling. Open source standards and specifications within the energy sector can also alleviate challenges associated with data fragmentation, transparency, and accessibility. At the same time, it is crucial to consider privacy and security concerns throughout the development of open source platforms.
This webinar will delve into the motivations behind establishing LF Energy’s Carbon Data Specification Consortium. It will provide an overview of the draft specifications and the ongoing progress made by the respective working groups.
Three primary specifications will be discussed:
-Discovery and client registration, emphasizing transparent processes and secure and private access
-Customer data, centering around customer tariffs, bills, energy usage, and full consumption disclosure
-Power systems data, focusing on grid data, inclusive of transmission and distribution networks, generation, intergrid power flows, and market settlement data
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
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12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
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3. What we aim to cover today?
The MT & Quality Relationship
What is quality?
Possible ways of measuring it
Automated/Manual methods
Who needs to measure quality
Localisation stakeholders
The Missing Link - KantanMT Analytics
Segment level quality analysis
Helping to build predictable business models
45 Mins Presentation
15 Mins Q&A
Q&A
KantanMT Analytics - The Missing Link
4. What is KantanMT.com?
Statistical MT System
Cloud-based
Highly scalable
Inexpensive to operate
Quick to deploy
Our Vision
To put Machine Translation
Customization
Improvement
Deployment
into your hands
Fully Operational 7 months
Active KantanMT Engines
6,632
Training Words Uploaded
23,653,605,925
Member Words Translated
362,291,925
KantanMT Analytics - The Missing Link
5. The Quality & MT Relationship
Let’s agree a model for defining quality!
Quality Target (defined by client)
No Quality (baseline)
Taking into consideration quality of MT outputs and level of quality defined by your clients.
KantanMT Analytics - The Missing Link
6. Attributes of Quality
Attributes of Quality – Model
Language Attributes
Adequacy
Fluency
Adequacy
Meaning of generated texts
expressed in source/target
Fluency
Comprehensibility & readability
Factors include
Task-oriented Attributes
Productivity
Post-editing speed
Acceptability
Fit-for-purpose measurement
Usable translations within the
context of the end user/client
Acceptability
Grammar errors
word selection
syntax
Language
Productivity
Task
KantanMT Analytics - The Missing Link
7. Attributes of Quality
Attributes of Quality – Model
Language Attributes
Adequacy
Fluency
Adequacy
Meaning of generated texts
expressed in source/target
Fluency
Comprehensibility & readability
Factors include
Task-oriented Attributes
Productivity
Post-editing speed
Acceptability
Fit-for-purpose measurement
Usable translations within the
context of the end user/client
Acceptability
Grammar errors
word selection
syntax
Language
Translation Style
Productivity
Task
Business Model
KantanMT Analytics - The Missing Link
8. Attributes of Quality
Attributes of Quality – Model
Language Attributes
Task-oriented Attributes
What we want?
Fluency
Adequacy
Productivity
Acceptability
FuzzyMatch
Language
Translation Style
Task
Business Model
KantanMT Analytics - The Missing Link
9. Measuring MT Quality
Automated
Fast
Repeatable
Objective
Scalable
Cheap
Based on samples
Can’t be used by PMs
Scope/Cost predictions
Manual
Slow
Cumbersome
Subjective
Not scalable
Expensive
Based on samples
Can’t be used by PMs
Scope/Cost predictions
KantanMT Analytics - The Missing Link
10. Measuring MT by hand!
Sample Translations based on template
Style
Wrong terminology
Wrong Spelling
Source not Capitalization
Translated/Omissions
Syntax & Grammar
Compliance with client specs
Wrong Word Form
Literal translation Part of Speech
Wrong
Text/Information added
Punctuation
Technical
Tags and Markup
Sentence Structure
Locale Adaptation
Overall
Spacing Adequacy Score
Fluency Score
Overall Quality Score
KantanMT Analytics - The Missing Link
11. Manual Framework
Adequacy Score (Range 1 – 5)
5
Full Meaning
All meaning expressed in the source segment appears in the translated
segment
Most Meaning
Most of the source segment meaning is expressed in the translated segment
Much Meaning
Much of the source segment meaning is expressed in the translated segment
Little Meaning
Little of the source segment is expressed in the translated segment
No Meaning
None of the meaning expressed in the source segment is expressed in the
translated segment
1
KantanMT Analytics - The Missing Link
12. Manual Framework
Fluency Score (Range 1 – 5)
5
Native language fluency
No grammar errors, excellent word selection and good syntax. No post-editing
required.
Near native fluency
Few terminology/grammar errors. No impact on overall understanding of the
meaning. Little post-editing required.
Not very fluent
About half of translation contains errors and requires post-editing.
Little fluency
Wrong word choice, poor grammar and syntax. A lot of post-editing required.
No fluency
Absolutely ungrammatical and doesn’t make any sense. Re-translate from
scratch .
1
KantanMT Analytics - The Missing Link
13. Source
MT Target
Spacing
Syntax and Grammar
Locale Adaptation
Tags and Markup
Sentence Structure
Punctuation
Wrong Part of Speech
Style
Wrong Word Form
Capitalization
Text/Information added
Literal translation
Compliance with client specs
Source not
Translated/Omissions
Wrong Spelling
Wrong terminology
Overall quality (1-4)
Fluency (Score 1-5)
Adequacy (Score 1-5)
Manual Framework
Tech
KantanMT Analytics - The Missing Link
14. Manual Framework
Attributes of Quality – Model
Language Attributes
Fluency
Task-oriented Attributes
Productivity
Manual
Methods
Adequacy
Acceptability
Language
Translation Style
Task
Business Model
KantanMT Analytics - The Missing Link
15. Automated Methods
Many different methods available
BLEU, F-Measure, GTM, TER, NIST, Meteor, etc.
Common characteristics
Compute similarity of generated texts to reference texts
The smaller the difference => the better the quality!
Broad adoption
Industry & Academia
KantanMT Analytics - The Missing Link
17. Automated Methods
WER (Word Error Rate)
Min number of edits to transform output to reference
Reference Translation
MT Output
WER
Substitutions + insertions + deletions
Reference-length
Levenshtein distance measure
General indicator of Post-Editing Effort
KantanMT Analytics - The Missing Link
18. Automated Methods
BLEU Score
Put simply – measures how many words overlap, giving
higher scores to sequential words
High correlation between BLEU and human judgement of
translation quality
Reference Translation
MT Output
KantanMT Analytics - The Missing Link
19. Automated Methods
KantanWatch™ can be used to track and monitor
automated scores
* KantanWatch Reports
KantanMT Analytics - The Missing Link
20. Automated Methods
Improvements can be monitored during the build-
measure-learn cycle of a KantanMT deployment
* KantanWatch Reports
KantanMT Analytics - The Missing Link
21. Automated Methods
Time-graphs offer good overview of the maturing of a
KantanMT engine
* KantanWatch Reports
KantanMT Analytics - The Missing Link
22. Automated Methods
Can also present a holistic view of the potential quality
of KantanMT outputs
* KantanWatch Reports
KantanMT Analytics - The Missing Link
23. Automated Methods
Attributes of Quality – Model
Language Attributes
Task-oriented Attributes
NIST
Fluency
Productivity
GTM
F-Measure
Adequacy
TER
Acceptability
BLEU
METEOR
Language
Task
Translation Style
Business Model
Major Flaw: All measurements based on reference translations
KantanMT Analytics - The Missing Link
24. Who uses these measurements?
The Localisation Stakeholder Dilemma
Developers of MT Engines
Automated BLEU, METEOR, F-MEASURE, TER ideal and practical
No individual measurement has absolute meaning
but points quality curve in the right direction within a domain
KantanMT Analytics - The Missing Link
25. Who needs to measure Quality?
The Localisation Stakeholder Dilemma
Production Teams (PMs, LEs and QEs)
Need segment measurements on quality and PE efforts
Determine tiered segment post-edit rate
Distribution of post-editing tasks based on segment quality
Localisation Managers
Need productivity measurements to predict budget and schedule
Aka Project Segment Reports
MT Measurements need to ‘fit’ business planning and charge models
Translators
Unfortunately, don’t get a fair deal
No segment information, just top level project ‘inferences’ based on samples
KantanMT Analytics - The Missing Link
27. Conclusions
There are many automated MT quality measurements
Mostly suitable for MT developers
Not optimal for production teams
Of no use to translators
All rely on reference texts to compute measurements
What’s needed?
Segment level measurements
Drive project schedule and charge model
High correlation to human effort
Do not rely on reference texts to compute measurements
KantanMT Analytics - The Missing Link
28. Attributes of Quality
Attributes of Quality – Model
Language Attributes
Task-oriented Attributes
What you want…
Fluency
Adequacy
Productivity
Acceptability
KantanMT Analytics
Language
Translation Style
Task
Business Model
KantanMT Analytics - The Missing Link
29. Introducing KantanMT Analytics™
Segment level scoring for MT output
Designed to make it possible to create predictable
Business Models
Project Schedule
Cost Models
Co-developed
KantanMT.com
CNGL – Centre of Next Generation Localisation
KantanMT Analytics - The Missing Link
32. KantanMT Analytics™
KantanMT Analytics Report
created
XML based for consumption by
TMS/GMS platforms
KantanMT Analytics - The Missing Link
33. KantanMT Analytics™
XLIFF document created
Contains scores for each segment
KantanMT Analytics - The Missing Link
34. The Missing Link
Attributes of Quality – Model
Language Attributes
Task-oriented Attributes
Fluency
Productivity
KantanMT Analytics™
Adequacy
Language
Translation Style
Acceptability
Task
Business Model
KantanMT Analytics - The Missing Link
Editor's Notes
No more expensive deploymentsMonthly subscription plan Customised subscription planNo more complexityKantanMT does all the heavy liftingYou focus on what you do best – grow and develop your business