Google Translator is an online free translator that supports many languages. The document analyzes Google Translator's performance on a text about the origins of Coca-Cola in Atlanta. It finds several mistakes in vocabulary, word order, and syntax. While Google Translator is useful for translating texts into multiple languages, the summary concludes that the translated text may not be entirely accurate and mistakes should be considered when using the tool.
Machine translation is an easy tool for translating text from one language to another. You've probably used it. But do you know what machine translation really is? Or when you should or shouldn't use it? Navigate through this presentation to learn more!
This document reviews and compares three online translation tools: Google Translate, Reverso, and Yahoo Babel Fish. It analyzes translations of both a Shakespearean sonnet and a news article produced by each tool. All three tools produced translations with errors such as incorrect word order, lack of agreement, failure to translate certain words, and loss of intended meaning. While automatic translators are imperfect, they provide a useful service when human translation is not possible or practical.
The document discusses using the Google Translate app in classrooms to help English language learners (ESL students) participate and understand classroom materials. It describes how students can instantly scan and translate printed texts using the app. The updated app allows students to translate materials in real-time, helping ESL students who have been in the US for less than two months to complete reading activities and answer questions. Their teachers noticed they seemed smarter and were able to participate more after using the translation app in class. The app gives ESL students a boost by allowing them to understand and perform at their grade level, even when just starting to learn English.
Google Translate is a translation service developed by Google that allows users to translate text and websites between many different languages. It can translate text entered or selected on a webpage in real-time and offers translation of voice input and camera images. Users can save favorite translations to quickly access them later or adjust settings like language detection and text-to-speech options.
This slides covers introduction about machine translation, some technique using in MT such as example based MT and statistical MT, main challenge facing us in machine translation, and some examples of application using in MT
The document discusses different approaches to machine translation, including rule-based, statistical, example-based, and dictionary-based approaches. It provides details on each approach, such as rule-based methods using linguistic rules and extensive lexicons, statistical methods relying on probabilistic models trained on parallel texts, example-based methods translating by analogy to examples in aligned corpora, and dictionary-based methods translating words directly with or without morphological analysis. The document also compares transfer-based and interlingual rule-based machine translation, noting interlingual methods aim to represent the source text independently of languages.
Google Translator is an online free translator that supports many languages. The document analyzes Google Translator's performance on a text about the origins of Coca-Cola in Atlanta. It finds several mistakes in vocabulary, word order, and syntax. While Google Translator is useful for translating texts into multiple languages, the summary concludes that the translated text may not be entirely accurate and mistakes should be considered when using the tool.
Machine translation is an easy tool for translating text from one language to another. You've probably used it. But do you know what machine translation really is? Or when you should or shouldn't use it? Navigate through this presentation to learn more!
This document reviews and compares three online translation tools: Google Translate, Reverso, and Yahoo Babel Fish. It analyzes translations of both a Shakespearean sonnet and a news article produced by each tool. All three tools produced translations with errors such as incorrect word order, lack of agreement, failure to translate certain words, and loss of intended meaning. While automatic translators are imperfect, they provide a useful service when human translation is not possible or practical.
The document discusses using the Google Translate app in classrooms to help English language learners (ESL students) participate and understand classroom materials. It describes how students can instantly scan and translate printed texts using the app. The updated app allows students to translate materials in real-time, helping ESL students who have been in the US for less than two months to complete reading activities and answer questions. Their teachers noticed they seemed smarter and were able to participate more after using the translation app in class. The app gives ESL students a boost by allowing them to understand and perform at their grade level, even when just starting to learn English.
Google Translate is a translation service developed by Google that allows users to translate text and websites between many different languages. It can translate text entered or selected on a webpage in real-time and offers translation of voice input and camera images. Users can save favorite translations to quickly access them later or adjust settings like language detection and text-to-speech options.
This slides covers introduction about machine translation, some technique using in MT such as example based MT and statistical MT, main challenge facing us in machine translation, and some examples of application using in MT
The document discusses different approaches to machine translation, including rule-based, statistical, example-based, and dictionary-based approaches. It provides details on each approach, such as rule-based methods using linguistic rules and extensive lexicons, statistical methods relying on probabilistic models trained on parallel texts, example-based methods translating by analogy to examples in aligned corpora, and dictionary-based methods translating words directly with or without morphological analysis. The document also compares transfer-based and interlingual rule-based machine translation, noting interlingual methods aim to represent the source text independently of languages.
Error Analysis of Rule-based Machine Translation OutputsParisa Niksefat
Rule-based machine translation systems were evaluated based on errors in translations from English to Persian. Several error categories were identified including syntactic errors (word order, missing words, parts of speech), unknown words, and semantic errors (incorrect words, idiomatic expressions). Three texts (a short story, user guide, and magazine article) were translated using two machine translation systems and analyzed sentence-by-sentence to identify errors according to the defined categories.
Multi lingual corpus for machine aided translationAashna Phanda
This document summarizes a student's research project on developing a multi-lingual machine translation corpus. The student aims to build a system that can generate reliable translations across multiple languages by breaking text into linguistic units or phrases and translating each unit using a database of generic phrase translations, providing a more accurate translation than typical probabilistic approaches. The system is proposed to have three layers - unit identification by translators, algorithm development jointly by translators and developers, and coding by developers. While this approach aims to improve accuracy over existing systems, limitations include its initial focus on only English, Hindi and Japanese and applicability to only a single domain. Further work could expand it to additional languages and domains.
This document discusses the basic tools and technologies that modern translators and interpreters use. It recommends having a computer, laptop, translation software like Trados, OmegaT, Wordfast, and online resources like Linguee and ProZ. It emphasizes using translation memory for better productivity and consistency. It also discusses teamwork, marketing services through blogs, forums and profiles, and using the internet as a resource for word meanings, translator networks, and staying up to date in the field. Overall, the document stresses that technology helps translators but is not a replacement for language skills, and recommends familiarizing oneself with digital tools and online resources.
This document provides an overview of a tutorial on statistical machine translation given by Dr. Khalil Sima'an. The tutorial is divided into two parts, with Part I covering data and models, including word-based models, alignment, symmetrization, and phrase-based models. Part II, given by Trevor Cohn, will cover decoding and efficiency. The tutorial will examine the statistical approach to machine translation using parallel corpora and will discuss generative source-channel frameworks and challenges in estimating translation probabilities from sparse data. It will also explore how current models induce structure in translation data using alignments between source and target language structures.
Mixing Computer-Assisted Translation and Machine Translationallinportuguese
Curious to learn more about how much a translator could really benefit from this daunting combination, Cris Silva and Giovana Boselli conducted an experiment in which we combined machine translation and translation memory. This slide discusses our process and statistics in an attempt to provide translation and localization professionals with some empirical information on the combined use of machine translation and computer-assisted translation.
Human Translation keeps the original meaning and usually shows errors and has to be thoroughly edited. Machine translations are much more cost effective than hiring a human to work on conversion. It’s vital to determine which translation provider service is most suitable for your business when it comes to both cost and accuracy.
Machine translation vs human translationLanguages Pro
Languages Pro is a translation and interpretation company located at 701 Fifth Avenue, Suite 4200 in Seattle, WA. They can be contacted toll-free at (800) 471-6567 or via fax at (866) 936-5554. Additional contact information includes an email address of info@languagespro.com and a website of www.languagespro.com.
Effect of Machine Translation in Interlingual Conversation: Lessons from a Fo...Kotaro Hara
Our talk at CHI2015 in Seoul, South Korea. Find more information at www.kotarohara.com .
YouTube: https://youtu.be/isqsYLkX9gA
Makeability Lab: http://www.cs.umd.edu/~jonf/
Microsoft Research: http://research.microsoft.com/
ABSTRACT
Language barrier is the primary challenge for effective cross-lingual conversations. Spoken language translation (SLT) is perceived as a cost-effective alternative to less affordable human interpreters, but little research has been done on how people interact with such technology. Using a prototype translator application, we performed a formative evaluation to elicit how people interact with the technology and adapt their conversation style. We conducted two sets of studies with a total of 23 pairs (46 participants). Participants worked on storytelling tasks to simulate natural conversations with 3 different interface settings. Our findings show that collocutors naturally adapt their style of speech production and comprehension to compensate for inadequacies in SLT. We conclude the paper with the design guidelines that emerged from the analysis.
Machine Translation And Computer Assisted TranslationTeritaa
Machine translation and computer-assisted translation are new ways of translating that utilize technology. The demand for translations has increased due to factors like the Cold War, cultural independence, and the internet providing universal access to information. The history of machine translation began in the 1930s and involved researchers developing methods using editors and computers to analyze words and convert them between languages. In the 1950s and 1960s, early machine translation programs used bilingual dictionaries and rules for word order but faced issues. Later developments included various machine translation systems in universities, companies, and the European Union from the 1980s onward. Computer-assisted translation tools now help translators through resources like dictionaries, terminology databases, translation memories, and analyzing previous translations.
Semantic Text Processing Powered by WikipediaMaxim Grinev
The document discusses using Wikipedia as a resource for semantic text processing and natural language processing techniques. It describes using Wikipedia's comprehensive coverage of terms, rich structure of links and categories, and ability to be continuously updated to power text analysis algorithms. These include word sense disambiguation, keyword extraction, topic inference, ontology management, semantic search, and improved recommendations. The techniques analyze Wikipedia's link structure and build semantic graphs of documents to discover related concepts and group keywords.
Indianapolis - Wikipedia and the Cultural Sectorwittylama
Presentation given at IUPUI on 19th April 2010. "Wikipedia and the Cultural Sector" - about some of the problems and advantages that the two communities have in working with each other.
Effective Approach for Disambiguating Chinese Polyphonic AmbiguityIDES Editor
One of the difficult tasks on Natural Language
Processing (NLP) is to resolve the sense ambiguity of
characters or words on text, such as polyphones, homonymy,
and homograph. The paper addresses the ambiguity issue of
Chinese character polyphones and disambiguity approach for
such issues. Three methods, dictionary matching, language
models and voting scheme, are used to disambiguate the
prediction of polyphones. Compared with the well-known MS
Word 2007 and language models (LMs), our approach is
superior to these two methods for the issue. The final precision
rate is enhanced up to 92.75%. Based on the proposed
approaches, we have constructed the e-learning system in
which several related functions of Chinese transliteration are
integrated.
Natural Language Generation: New Automation and Personalization OpportunitiesAutomated Insights
Discover how natural language generation technology is providing new opportunities for writing automation in business, significantly increasing productivity, efficiency and personalization across a range of industries.
Outlining new practical applications for using natural language generation technology to automate personalized content for clients, prospects, shoppers and internal audiences.
The document discusses online handwritten character recognition in the Devanagari script using a hierarchical partitioned hidden Markov model approach. Key steps include preprocessing strokes, extracting directional features, using single linkage clustering to select prototypes, and building a two-layer model with bottom HMMs for clusters and an upper attribute graph layer. Mathematical foundations show that pruning points does not impact the dynamic time warping distance measure between strokes. The approach achieves a recognition rate of 91.24% on a test dataset.
Limitations in automated translation services showcase the need for active professionals to conduct your translation work and this is where Nordictrans comes into actions providing high quality translation services from and into just about any language.
The document discusses combining Google Translate with TectoMT, a modular NLP software system. It provides background on each tool, noting Google Translate supports 34 languages via API and handles large amounts of text using computing power, while TectoMT takes a more linguistic approach. Examples are given showing translations from both Google Translate alone and combined with TectoMT, with the combination approach generating more accurate translations by conditioning on governing and dependent words rather than linear context. The document concludes by noting results from initial experiments combining the tools, and outlines plans to improve the approach.
The document is a short personal text from a 51-year-old mother of 3 who lives in Israel. She describes her busy day running between activities and commitments, working in high-tech recruitment while also volunteering at least once a week. She implies that no further explanation is needed about her busy lifestyle.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
Error Analysis of Rule-based Machine Translation OutputsParisa Niksefat
Rule-based machine translation systems were evaluated based on errors in translations from English to Persian. Several error categories were identified including syntactic errors (word order, missing words, parts of speech), unknown words, and semantic errors (incorrect words, idiomatic expressions). Three texts (a short story, user guide, and magazine article) were translated using two machine translation systems and analyzed sentence-by-sentence to identify errors according to the defined categories.
Multi lingual corpus for machine aided translationAashna Phanda
This document summarizes a student's research project on developing a multi-lingual machine translation corpus. The student aims to build a system that can generate reliable translations across multiple languages by breaking text into linguistic units or phrases and translating each unit using a database of generic phrase translations, providing a more accurate translation than typical probabilistic approaches. The system is proposed to have three layers - unit identification by translators, algorithm development jointly by translators and developers, and coding by developers. While this approach aims to improve accuracy over existing systems, limitations include its initial focus on only English, Hindi and Japanese and applicability to only a single domain. Further work could expand it to additional languages and domains.
This document discusses the basic tools and technologies that modern translators and interpreters use. It recommends having a computer, laptop, translation software like Trados, OmegaT, Wordfast, and online resources like Linguee and ProZ. It emphasizes using translation memory for better productivity and consistency. It also discusses teamwork, marketing services through blogs, forums and profiles, and using the internet as a resource for word meanings, translator networks, and staying up to date in the field. Overall, the document stresses that technology helps translators but is not a replacement for language skills, and recommends familiarizing oneself with digital tools and online resources.
This document provides an overview of a tutorial on statistical machine translation given by Dr. Khalil Sima'an. The tutorial is divided into two parts, with Part I covering data and models, including word-based models, alignment, symmetrization, and phrase-based models. Part II, given by Trevor Cohn, will cover decoding and efficiency. The tutorial will examine the statistical approach to machine translation using parallel corpora and will discuss generative source-channel frameworks and challenges in estimating translation probabilities from sparse data. It will also explore how current models induce structure in translation data using alignments between source and target language structures.
Mixing Computer-Assisted Translation and Machine Translationallinportuguese
Curious to learn more about how much a translator could really benefit from this daunting combination, Cris Silva and Giovana Boselli conducted an experiment in which we combined machine translation and translation memory. This slide discusses our process and statistics in an attempt to provide translation and localization professionals with some empirical information on the combined use of machine translation and computer-assisted translation.
Human Translation keeps the original meaning and usually shows errors and has to be thoroughly edited. Machine translations are much more cost effective than hiring a human to work on conversion. It’s vital to determine which translation provider service is most suitable for your business when it comes to both cost and accuracy.
Machine translation vs human translationLanguages Pro
Languages Pro is a translation and interpretation company located at 701 Fifth Avenue, Suite 4200 in Seattle, WA. They can be contacted toll-free at (800) 471-6567 or via fax at (866) 936-5554. Additional contact information includes an email address of info@languagespro.com and a website of www.languagespro.com.
Effect of Machine Translation in Interlingual Conversation: Lessons from a Fo...Kotaro Hara
Our talk at CHI2015 in Seoul, South Korea. Find more information at www.kotarohara.com .
YouTube: https://youtu.be/isqsYLkX9gA
Makeability Lab: http://www.cs.umd.edu/~jonf/
Microsoft Research: http://research.microsoft.com/
ABSTRACT
Language barrier is the primary challenge for effective cross-lingual conversations. Spoken language translation (SLT) is perceived as a cost-effective alternative to less affordable human interpreters, but little research has been done on how people interact with such technology. Using a prototype translator application, we performed a formative evaluation to elicit how people interact with the technology and adapt their conversation style. We conducted two sets of studies with a total of 23 pairs (46 participants). Participants worked on storytelling tasks to simulate natural conversations with 3 different interface settings. Our findings show that collocutors naturally adapt their style of speech production and comprehension to compensate for inadequacies in SLT. We conclude the paper with the design guidelines that emerged from the analysis.
Machine Translation And Computer Assisted TranslationTeritaa
Machine translation and computer-assisted translation are new ways of translating that utilize technology. The demand for translations has increased due to factors like the Cold War, cultural independence, and the internet providing universal access to information. The history of machine translation began in the 1930s and involved researchers developing methods using editors and computers to analyze words and convert them between languages. In the 1950s and 1960s, early machine translation programs used bilingual dictionaries and rules for word order but faced issues. Later developments included various machine translation systems in universities, companies, and the European Union from the 1980s onward. Computer-assisted translation tools now help translators through resources like dictionaries, terminology databases, translation memories, and analyzing previous translations.
Semantic Text Processing Powered by WikipediaMaxim Grinev
The document discusses using Wikipedia as a resource for semantic text processing and natural language processing techniques. It describes using Wikipedia's comprehensive coverage of terms, rich structure of links and categories, and ability to be continuously updated to power text analysis algorithms. These include word sense disambiguation, keyword extraction, topic inference, ontology management, semantic search, and improved recommendations. The techniques analyze Wikipedia's link structure and build semantic graphs of documents to discover related concepts and group keywords.
Indianapolis - Wikipedia and the Cultural Sectorwittylama
Presentation given at IUPUI on 19th April 2010. "Wikipedia and the Cultural Sector" - about some of the problems and advantages that the two communities have in working with each other.
Effective Approach for Disambiguating Chinese Polyphonic AmbiguityIDES Editor
One of the difficult tasks on Natural Language
Processing (NLP) is to resolve the sense ambiguity of
characters or words on text, such as polyphones, homonymy,
and homograph. The paper addresses the ambiguity issue of
Chinese character polyphones and disambiguity approach for
such issues. Three methods, dictionary matching, language
models and voting scheme, are used to disambiguate the
prediction of polyphones. Compared with the well-known MS
Word 2007 and language models (LMs), our approach is
superior to these two methods for the issue. The final precision
rate is enhanced up to 92.75%. Based on the proposed
approaches, we have constructed the e-learning system in
which several related functions of Chinese transliteration are
integrated.
Natural Language Generation: New Automation and Personalization OpportunitiesAutomated Insights
Discover how natural language generation technology is providing new opportunities for writing automation in business, significantly increasing productivity, efficiency and personalization across a range of industries.
Outlining new practical applications for using natural language generation technology to automate personalized content for clients, prospects, shoppers and internal audiences.
The document discusses online handwritten character recognition in the Devanagari script using a hierarchical partitioned hidden Markov model approach. Key steps include preprocessing strokes, extracting directional features, using single linkage clustering to select prototypes, and building a two-layer model with bottom HMMs for clusters and an upper attribute graph layer. Mathematical foundations show that pruning points does not impact the dynamic time warping distance measure between strokes. The approach achieves a recognition rate of 91.24% on a test dataset.
Limitations in automated translation services showcase the need for active professionals to conduct your translation work and this is where Nordictrans comes into actions providing high quality translation services from and into just about any language.
The document discusses combining Google Translate with TectoMT, a modular NLP software system. It provides background on each tool, noting Google Translate supports 34 languages via API and handles large amounts of text using computing power, while TectoMT takes a more linguistic approach. Examples are given showing translations from both Google Translate alone and combined with TectoMT, with the combination approach generating more accurate translations by conditioning on governing and dependent words rather than linear context. The document concludes by noting results from initial experiments combining the tools, and outlines plans to improve the approach.
The document is a short personal text from a 51-year-old mother of 3 who lives in Israel. She describes her busy day running between activities and commitments, working in high-tech recruitment while also volunteering at least once a week. She implies that no further explanation is needed about her busy lifestyle.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
17. texts can be well understood need for articles: not respected !! not capable of understanding some structures !!! Tenses quite badly used !!! Helpfultooltoget a general idea of thetext !!!