Presentation of the paper "Hydra: A Vocabulary for Hypermedia-Driven Web APIs" at the 6th Workshop on Linked Data on the Web (LDOW2013) at the WWW2013 in Rio de Janeiro, Brazil
Presentation of the paper "On Using JSON-LD to Create Evolvable RESTful Services" at the 3rd International Workshop on RESTful Design (WS-REST 2012) at WWW2012 in Lyon, France
Model Your Application Domain, Not Your JSON StructuresMarkus Lanthaler
Presentation of the paper "Model Your Application Domain, Not Your JSON Structures" at the 4th International Workshop on RESTful Design (WS-REST 2013) at the WWW2013 in Rio de Janeiro, Brazil
JSON-LD is a set of W3C standards track specifications for representing Linked Data in JSON. It is fully compatible with the RDF data model, but allows developers to work with data entirely within JSON.
More information on JSON-LD can be found at http://json-ld.org/
Importing Data into Neo4j quickly and easily - StackOverflowNeo4j
In this GraphConnect presentation Mark and Michael show several ways to import large amounts of highly connected data from different formats into Neo4j. Both Cypher's LOAD CSV as well as the bulk importer is demonstrated along with many tips.
We use the well know StackOverflow Q&A site data which is interestingly very graphy.
Presentation of the paper "On Using JSON-LD to Create Evolvable RESTful Services" at the 3rd International Workshop on RESTful Design (WS-REST 2012) at WWW2012 in Lyon, France
Model Your Application Domain, Not Your JSON StructuresMarkus Lanthaler
Presentation of the paper "Model Your Application Domain, Not Your JSON Structures" at the 4th International Workshop on RESTful Design (WS-REST 2013) at the WWW2013 in Rio de Janeiro, Brazil
JSON-LD is a set of W3C standards track specifications for representing Linked Data in JSON. It is fully compatible with the RDF data model, but allows developers to work with data entirely within JSON.
More information on JSON-LD can be found at http://json-ld.org/
Importing Data into Neo4j quickly and easily - StackOverflowNeo4j
In this GraphConnect presentation Mark and Michael show several ways to import large amounts of highly connected data from different formats into Neo4j. Both Cypher's LOAD CSV as well as the bulk importer is demonstrated along with many tips.
We use the well know StackOverflow Q&A site data which is interestingly very graphy.
Best Practices for Middleware and Integration Architecture Modernization with...Claus Ibsen
What are important considerations when modernizing middleware and moving towards serverless and/or cloud native integration architectures? How can we make the most of flexible technologies such as Camel K, Kafka, Quarkus and OpenShift. Claus is working as project lead on Apache Camel and has extensive experience from open source product development.
The talk was recorded and runs for 30 minutes and published on youtube at: https://www.youtube.com/watch?v=d1Hr78a7Lww
This presentation will demonstrate how you can use the aggregation pipeline with MongoDB similar to how you would use GROUP BY in SQL and the new stage operators coming 3.4. MongoDB’s Aggregation Framework has many operators that give you the ability to get more value out of your data, discover usage patterns within your data, or use the Aggregation Framework to power your application. Considerations regarding version, indexing, operators, and saving the output will be reviewed.
Mark and Wes will talk about Cypher optimization techniques based on real queries as well as the theoretical underlying processes. They'll start from the basics of "what not to do", and how to take advantage of indexes, and continue to the subtle ways of ordering MATCH/WHERE/WITH clauses for optimal performance as of the 2.0.0 release.
This talk is focused on tuning analysing and optimizing MongoDB query and index with the use of Database Profiler and "explain()" function.
Also, performance of database can also be impacted by configuring the underline ( Linux ) OS with some recommended settings which do not come by default.
An online training course run by the FIWARE Foundation in conjunction with the i4Trust project and IShare Foundation. The core part of this virtual training camp (27 Jun - 01 Jul 2022) covered all the necessary skills to develop smart solutions powered by FIWARE. It introduces the basis of Digital Twin programming using NGSI-LD (the simple yet powerful open standard API enabling to publish and access digital twin data) combined with common smart data models
In addition, it covers the supplementary FIWARE technologies used to implement the rest of functions typically required when architecting a complete smart solution: Identity and Access Management (IAM) functions to secure access to digital twin data, and functions enabling the interface with IoT and 3rd systems, or the connection with different tools for processing and monitoring current and historic big data.
Extending this core part, the training camp also cover how you can easily integrate FIWARE systems with blockchain networks to create audit-proof logs of processes and ensure transparency.
It is a basic presentation which can help you understand the basic concepts about Graphql and how it can be used to resolve the frontend integration of projects and help in reducing the data fetching time
This presentation also explains the core features of Graphql and why It is a great alternative for REST APIs along with the procedure with which we can integrate it into our projects
Modularized ETL Writing with Apache SparkDatabricks
Apache Spark has been an integral part of Stitch Fix’s compute infrastructure. Over the past five years, it has become our de facto standard for most ETL and heavy data processing needs and expanded our capabilities in the Data Warehouse.
Since all our writes to the Data Warehouse are through Apache Spark, we took advantage of that to add more modules that supplement ETL writing. Config driven and purposeful, these modules perform tasks onto a Spark Dataframe meant for a destination Hive table.
These are organized as a sequence of transformations on the Apache Spark dataframe prior to being written to the table.These include a process of journalizing. It is a process which helps maintain a non-duplicated historical record of mutable data associated with different parts of our business.
Data quality, another such module, is enabled on the fly using Apache Spark. Using Apache Spark we calculate metrics and have an adjacent service to help run quality tests for a table on the incoming data.
And finally, we cleanse data based on provided configurations, validate and write data into the warehouse. We have an internal versioning strategy in the Data Warehouse that allows us to know the difference between new and old data for a table.
Having these modules at the time of writing data allows cleaning, validation and testing of data prior to entering the Data Warehouse thus relieving us, programmatically, of most of the data problems. This talk focuses on ETL writing in Stitch Fix and describes these modules that help our Data Scientists on a daily basis.
Spark (Structured) Streaming vs. Kafka StreamsGuido Schmutz
Independent of the source of data, the integration and analysis of event streams gets more important in the world of sensors, social media streams and Internet of Things. Events have to be accepted quickly and reliably, they have to be distributed and analyzed, often with many consumers or systems interested in all or part of the events. In this session we compare two popular Streaming Analytics solutions: Spark Streaming and Kafka Streams.
Spark is fast and general engine for large-scale data processing and has been designed to provide a more efficient alternative to Hadoop MapReduce. Spark Streaming brings Spark's language-integrated API to stream processing, letting you write streaming applications the same way you write batch jobs. It supports both Java and Scala.
Kafka Streams is the stream processing solution which is part of Kafka. It is provided as a Java library and by that can be easily integrated with any Java application.
This presentation shows how you can implement stream processing solutions with each of the two frameworks, discusses how they compare and highlights the differences and similarities.
Working with JSON Data in PostgreSQL vs. MongoDBScaleGrid.io
In this post, we are going to show you tips and techniques on how to effectively store and index JSON data in PostgreSQL vs. MongoDB. Learn more in the blog post: https://scalegrid.io/blog/using-jsonb-in-postgresql-how-to-effectively-store-index-json-data-in-postgresql
"Json Web Token with digital signature. Modern authentication or authorization. Cookies are bad. Avoid Man-in-the-middle-attack. No need to protect against CSRF. Stateless.
Presentation of the paper "Creating 3rd Generation Web APIs with Hydra" at the 22nd Internation World Wide Web Conference (WWW2013) in Rio de Janeiro, Brazil
My presentation at SMX Milan 2015. New ways to compile and offer structured data to search engines for improved online visibility. Real life examples ready to use for websites and blogs.
Best Practices for Middleware and Integration Architecture Modernization with...Claus Ibsen
What are important considerations when modernizing middleware and moving towards serverless and/or cloud native integration architectures? How can we make the most of flexible technologies such as Camel K, Kafka, Quarkus and OpenShift. Claus is working as project lead on Apache Camel and has extensive experience from open source product development.
The talk was recorded and runs for 30 minutes and published on youtube at: https://www.youtube.com/watch?v=d1Hr78a7Lww
This presentation will demonstrate how you can use the aggregation pipeline with MongoDB similar to how you would use GROUP BY in SQL and the new stage operators coming 3.4. MongoDB’s Aggregation Framework has many operators that give you the ability to get more value out of your data, discover usage patterns within your data, or use the Aggregation Framework to power your application. Considerations regarding version, indexing, operators, and saving the output will be reviewed.
Mark and Wes will talk about Cypher optimization techniques based on real queries as well as the theoretical underlying processes. They'll start from the basics of "what not to do", and how to take advantage of indexes, and continue to the subtle ways of ordering MATCH/WHERE/WITH clauses for optimal performance as of the 2.0.0 release.
This talk is focused on tuning analysing and optimizing MongoDB query and index with the use of Database Profiler and "explain()" function.
Also, performance of database can also be impacted by configuring the underline ( Linux ) OS with some recommended settings which do not come by default.
An online training course run by the FIWARE Foundation in conjunction with the i4Trust project and IShare Foundation. The core part of this virtual training camp (27 Jun - 01 Jul 2022) covered all the necessary skills to develop smart solutions powered by FIWARE. It introduces the basis of Digital Twin programming using NGSI-LD (the simple yet powerful open standard API enabling to publish and access digital twin data) combined with common smart data models
In addition, it covers the supplementary FIWARE technologies used to implement the rest of functions typically required when architecting a complete smart solution: Identity and Access Management (IAM) functions to secure access to digital twin data, and functions enabling the interface with IoT and 3rd systems, or the connection with different tools for processing and monitoring current and historic big data.
Extending this core part, the training camp also cover how you can easily integrate FIWARE systems with blockchain networks to create audit-proof logs of processes and ensure transparency.
It is a basic presentation which can help you understand the basic concepts about Graphql and how it can be used to resolve the frontend integration of projects and help in reducing the data fetching time
This presentation also explains the core features of Graphql and why It is a great alternative for REST APIs along with the procedure with which we can integrate it into our projects
Modularized ETL Writing with Apache SparkDatabricks
Apache Spark has been an integral part of Stitch Fix’s compute infrastructure. Over the past five years, it has become our de facto standard for most ETL and heavy data processing needs and expanded our capabilities in the Data Warehouse.
Since all our writes to the Data Warehouse are through Apache Spark, we took advantage of that to add more modules that supplement ETL writing. Config driven and purposeful, these modules perform tasks onto a Spark Dataframe meant for a destination Hive table.
These are organized as a sequence of transformations on the Apache Spark dataframe prior to being written to the table.These include a process of journalizing. It is a process which helps maintain a non-duplicated historical record of mutable data associated with different parts of our business.
Data quality, another such module, is enabled on the fly using Apache Spark. Using Apache Spark we calculate metrics and have an adjacent service to help run quality tests for a table on the incoming data.
And finally, we cleanse data based on provided configurations, validate and write data into the warehouse. We have an internal versioning strategy in the Data Warehouse that allows us to know the difference between new and old data for a table.
Having these modules at the time of writing data allows cleaning, validation and testing of data prior to entering the Data Warehouse thus relieving us, programmatically, of most of the data problems. This talk focuses on ETL writing in Stitch Fix and describes these modules that help our Data Scientists on a daily basis.
Spark (Structured) Streaming vs. Kafka StreamsGuido Schmutz
Independent of the source of data, the integration and analysis of event streams gets more important in the world of sensors, social media streams and Internet of Things. Events have to be accepted quickly and reliably, they have to be distributed and analyzed, often with many consumers or systems interested in all or part of the events. In this session we compare two popular Streaming Analytics solutions: Spark Streaming and Kafka Streams.
Spark is fast and general engine for large-scale data processing and has been designed to provide a more efficient alternative to Hadoop MapReduce. Spark Streaming brings Spark's language-integrated API to stream processing, letting you write streaming applications the same way you write batch jobs. It supports both Java and Scala.
Kafka Streams is the stream processing solution which is part of Kafka. It is provided as a Java library and by that can be easily integrated with any Java application.
This presentation shows how you can implement stream processing solutions with each of the two frameworks, discusses how they compare and highlights the differences and similarities.
Working with JSON Data in PostgreSQL vs. MongoDBScaleGrid.io
In this post, we are going to show you tips and techniques on how to effectively store and index JSON data in PostgreSQL vs. MongoDB. Learn more in the blog post: https://scalegrid.io/blog/using-jsonb-in-postgresql-how-to-effectively-store-index-json-data-in-postgresql
"Json Web Token with digital signature. Modern authentication or authorization. Cookies are bad. Avoid Man-in-the-middle-attack. No need to protect against CSRF. Stateless.
Presentation of the paper "Creating 3rd Generation Web APIs with Hydra" at the 22nd Internation World Wide Web Conference (WWW2013) in Rio de Janeiro, Brazil
My presentation at SMX Milan 2015. New ways to compile and offer structured data to search engines for improved online visibility. Real life examples ready to use for websites and blogs.
This presentation was given at the Balisage 2017 conference, and provides an overview of three key RDF standards for constraint modeling, annotation and the use of data frames and cubes in RDF.
Manage and monitor your Oracle Database securely with Oracle REST Data Services and our Database API. These slides will show how to configure the feature and demonstrate a simple report and kicking off a Data Pump export job.
RESTful Web APIs – Mike Amundsen, Principal API Architect, Layer 7CA API Management
Based on the upcoming O'Reilly book "RESTful Web APIs" by Leonard Richardson and Mike Amundsen, this 1/2 day workshop covers the basics of Fielding's REST style, HTTP standards, and common practices for APIs for Web. Key topics such as how how use hypermedia to increase API flexibility and how application profiles can improve API interoperability are also covered. In addition, a wide range of existing message formats and semantic vocabularies are reviewed along with a procedure for selecting and applying these existing standards to your own implementations. Other subjects will be covered such as caching, versioning, and supporting RESTful APIs on protocols other an HTTP.Throughout the workshop, attendees will be able to apply step-by-step guidance on how to create their own RESTful Web API and share these designs with the group at the end of the session.
Cdm mil-18 - hypermedia ap is for headless platforms and data integrationDavid Gómez García
Slides from my talk at Codemotion Milan 2018. Speaking about how Headess and Hypermedia REST APIs can leverage the way . we integrate different platforms and share date between them
David Gómez G. - Hypermedia APIs for headless platforms and Data Integration ...Codemotion
We live in a interconnected world, were every day new devices, systems, and applications are connected to share information or interact between them. Thus, the importance of designing systems prepared to offer their services and data to a wide range of customers, that could discover, navigate and use their API in a standard and easy way to be consumed. But designing a headless platform to be used easily through their services is not straightforward. In this talk we will go over the challenges that we've found in adding headless nature to our platform and the foundations and tools that we have
Modern architectures are moving away from a "one size fits all" approach. We are well aware that we need to use the best tools for the job. Given the large selection of options available today, chances are that you will end up managing data in MongoDB for your operational workload and with Spark for your high speed data processing needs.
Description: When we model documents or data structures there are some key aspects that need to be examined not only for functional and architectural purposes but also to take into consideration the distribution of data nodes, streaming capabilities, aggregation and queryability options and how we can integrate the different data processing software, like Spark, that can benefit from subtle but substantial model changes. A clear example is when embedding or referencing documents and their implications on high speed processing.
Over the course of this talk we will detail the benefits of a good document model for the operational workload. As well as what type of transformations we should incorporate in our document model to adjust for the high speed processing capabilities of Spark.
We will look into the different options that we have to connect these two different systems, how to model according to different workloads, what kind of operators we need to be aware of for top performance and what kind of design and architectures we should put in place to make sure that all of these systems work well together.
Over the course of the talk we will showcase different libraries that enable the integration between spark and MongoDB, such as MongoDB Hadoop Connector, Stratio Connector and MongoDB Spark Native Connector.
By the end of the talk I expect the attendees to have an understanding of:
How they connect their MongoDB clusters with Spark
Which use cases show a net benefit for connecting these two systems
What kind of architecture design should be considered for making the most of Spark + MongoDB
How documents can be modeled for better performance and operational process, while processing these data sets stored in MongoDB.
The talk is suitable for:
Developers that want to understand how to leverage Spark
Architects that want to integrate their existing MongoDB cluster and have real time high speed processing needs
Data scientists that know about Spark, are playing with Spark and want to integrate with MongoDB for their persistency layer
Web APIs have revolutionized all kinds of products and services, and still continue to do so. Nowadays the most relevant architecture is REST along with the JSON media type. Furthermore, lots of specifications to serialize those media types are appearing. JSON API has released its first version last May.
OData: Universal Data Solvent or Clunky Enterprise Goo? (GlueCon 2015)Pat Patterson
Why would anyone but the most pedestrian enterprise developer be interested in a data access protocol originally designed by Microsoft, implemented in XML and handed to OASIS for standardization? The Open Data Protocol, or OData for short, has evolved into a clean, RESTful interface for CRUD operations against data services. Alongside the usual enterprise suspects such as Microsoft, Salesforce and IBM, OData has been adopted by government and non-profit agencies to open up their data and make it accessible to the public. For developers wanting to consume data, or create their own OData services, there's no shortage of open source options, from Apache Olingo in Java to node-odata and ODataCpp. Whether you're accessing customer orders in SAP or the Whitehouse visitor book, you're going to need some OData smarts.
Solutions for bi-directional integration between Oracle RDBMS & Apache KafkaGuido Schmutz
Apache Kafka is a popular distributed streaming data platform. A Kafka cluster stores streams of records (messages) in categories called topics. It is the architectural backbone for integrating streaming data with a Data Lake, Microservices and Stream Processing. Data sources flowing into Kafka are often native data streams such as social media streams, telemetry data, financial transactions and many others. But these data stream only contain part of the information. A lot of data necessary in stream processing is stored in traditional systems backed by relational databases. To implement new and modern, real-time solutions, an up-to-date view of that information is needed. So how do we make sure that information can flow between the RDBMS and Kafka, so that changes are available in Kafka as soon as possible in near-real-time? This session will present different approaches for integrating relational databases with Kafka, such as Kafka Connect, Oracle GoldenGate and bridging Kafka with Oracle Advanced Queuing (AQ).
LinkML Intro July 2022.pptx PLEASE VIEW THIS ON ZENODOChris Mungall
NOTE THAT I HAVE MOVED AWAY FROM SLIDESHARE TO ZENODO
The identical presentation is now here:
https://doi.org/10.5281/zenodo.7778641
General introduction to LinkML, The Linked Data Modeling Language.
Adapter from presentation given to NIH May 2022
https://linkml.io/linkml
Similar to Hydra: A Vocabulary for Hypermedia-Driven Web APIs (20)
Presentation of the paper "A Web of Things to Reduce Energy Wastage" at the 10th IEEE International Conference on Industrial Informatics (INDIN 2012) in Beijing, China
Aligning Web Services with the Semantic Web to Create a Global Read-Write Gra...Markus Lanthaler
Presentation of the paper "Aligning Web Services with the Semantic Web to Create a Global Read-Write Graph of Data" gave at the 9th IEEE European Conference on Web Services (ECOWS 2011) in Lugano, Switzerland.
Despite significant research and development efforts, the vision of the Semantic Web yielding to a Web of Data has not yet become reality. Even though initiatives such as Linking Open Data gained traction recently, the Web of Data is still clearly outpaced by the growth of the traditional, document-based Web. Instead of releasing data in the form of RDF, many publishers choose to publish their data in the form of Web services. The reasons for this are manifold. Given that RESTful Web services closely resemble the document-based Web, they are not only perceived as less complex and disruptive, but also provide read-write interfaces to the underlying data. In contrast, the current Semantic Web is essentially read-only which clearly inhibits net-working effects and engagement of the crowd. On the other hand, the prevalent use of proprietary schemas to represent the data published by Web services inhibits generic browsers or crawlers to access and understand this data; the consequence are islands of data instead of a global graph of data forming the envisioned Semantic Web. We thus propose a novel approach to integrate Web services into the Web of Data by introducing an algorithm to translate SPARQL queries to HTTP requests. The aim is to create a global read-write graph of data and to standardize the mashup development process. We try to keep the approach as familiar and simple as possible to lower the entry barrier and foster the adoption of our approach. Thus, we based our proposal on SEREDASj, a semantic description language for RESTful data services, for making proprietary JSON service schemas accessible.
Presentation of SAPS at the 1st International Workshop on the Information-Centric Web (IC-Web 2011) at the 11th IEEE/IPSJ International Symposium on Applications and the Internet (SAINT 2011) in Munich, Germany
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
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.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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/
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.