Storm is a distributed realtime computation system. Similar to how Hadoop provides a set of general primitives for doing batch processing, Storm provides a set of general primitives for doing realtime computation. Storm is simple, can be used with any programming language, and is a lot of fun to use!
8th TUC Meeting | Lijun Chang (University of New South Wales). Efficient Subg...LDBC council
Lijun Chang, DECRA Fellow at the University of New South Wales talked about how to make subgraph matching more efficient thanks to postponing Cartesian products.
The document discusses using Neo4j graphs to analyze Army logistics data. It outlines requirements to identify all parts, track relationships between parts, find interchangeable parts, and generate comprehensive part explosions. It then demonstrates Neo4j implementation through sample queries to identify all components and systems related to a specific part. Resources for additional Neo4j information are also listed.
Guaranteeing Consensus in Distriubuted Systems with CRDTsSun-Li Beatteay
Consensus in distributed systems has been a debated topic every since programmers discovered they could run the same program on multiple machines. Researchers have been studying consensus for decades, resulting in numerous algorithms and white papers. Unfortunately, many of these algorithms are flawed and unreliable.
However, in 2011, a team of researchers published a paper on a novel approach to distributed consensus using Conflict-free Replicated Data Types (https://hal.inria.fr/inria-00609399v1...). This paper created quite a buzz as it showed that CRDTs were mathematically proven to guarantee consensus through "Strong Eventual Consistency." They also claimed to have solved the CAP conundrum.
This presentation dives into this seminal paper in order to answer the hard questions. What are CRDTs? How do they work? And most importantly, does it actually solve CAP? By the end of this talk, everyone in the audience will have a foundational understanding of CRDTs and how they can be applied to their own work.
Best of all, I will be explaining all of this is as simple language as possible. No advanced math degree required! Sound too good to be true? You'll just have to come see for yourself!
Gabriel Stöckle presented how to deploy a parameter study using the AstroGrid-D infrastructure. The document outlined the steps to join AstroGrid-D including obtaining certificates and registering membership. It described how to connect to grid resources, copy code, create parameter files, and submit jobs either directly or using a scheduler like Gridway. The goal was to distribute computationally intensive simulations that vary parameters across multiple resources for efficient execution.
Engineering Fast Indexes for Big-Data Applications: Spark Summit East talk by...Spark Summit
Contemporary computing hardware offers massive new performance opportunities. Yet high-performance programming remains a daunting challenge.
We present some of the lessons learned while designing faster indexes, with a particular emphasis on compressed bitmap indexes. Compressed bitmap indexes accelerate queries in popular systems such as Apache Spark, Git, Elastic, Druid and Apache Kylin.
Arc: An IR for Batch and Stream ProgrammingLars Kroll
There is currently a large number of data programming models and their respective frontends such as relational tables, graphs, tensors, and streams. This has lead to a plethora of runtimes that typically focus on the efficient execution of just a single frontend. This fragmentation manifests today into highly complex pipelines that bundle multiple runtimes to support the necessary models. Hence, joint optimisation and execution of such pipelines across these frontend-bound runtimes is infeasible. We propose Arc as the first unified Intermediate Representation (IR) for data analytics that incorporates stream semantics based on a modern specification of streams, windows and stream aggregation, to combine batch and stream computation models. Arc extends Weld, an IR for batch computation, and adds stream interoperability as a natural extension to describe static computational graphs suitable for stream processing.
Developing Your Own Flux Packages by David McKay | Head of Developer Relation...InfluxData
Flux is easy to contribute to, and it is easy to share functions and libraries of Flux code with other developers. Although there are many functions in the language, the true power of Flux is its ability to be extended with custom functions. In this session, David will show you how to write your own custom function to perform some new analytics.
How to Build a Telegraf Plugin by Noah CrowleyInfluxData
Telegraf is a plugin-driven server agent for collecting & reporting metrics and there are many plugins already written to source data from a variety of services and systems. However, there may be instances where you need to write your own plugin to source data from your particular systems. In this InfluxDays NYC 2019 session, Noah Crowley will provide you with the steps on how to write your own Telegraf plugin. Writing your own Telegraf plugin will require an understanding of the Go programming language.
딥러닝 중급 - AlexNet과 VggNet (Basic of DCNN : AlexNet and VggNet)Hansol Kang
The document summarizes the basics of Deep Convolutional Neural Networks (DCNNs) including AlexNet and VGGNet. It discusses how AlexNet introduced improvements like ReLU activation and dropout to address overfitting issues. It then focuses on the VGGNet, noting that it achieved good performance through increasing depth using small 3x3 filters and adding convolutional layers. The document shares details of VGGNet configurations ranging from 11 to 19 weight layers and their performance on image classification tasks.
This document discusses analyzing network infrastructure using Neo4j. It explains that Neo4j allows for visual analysis of network data through a graph database, making relationships easier to understand. Data about firewall rules, traffic, and services is collected from hosts and loaded into Neo4j. This enables analyzing relationships between hosts, finding unused or insecure configurations, and gaining insights not possible through traditional tools. Examples of Cypher queries demonstrate how to visualize and investigate the network using the Neo4j graph database.
The document discusses graph databases and their properties. Graph databases are structured to store graph-based data by using nodes and edges to represent entities and their relationships. They are well-suited for applications with complex relationships between entities that can be modeled as graphs, such as social networks. Key graph database technologies mentioned include Neo4j, OrientDB, and TinkerPop which provides graph traversal capabilities.
The document discusses infrastructure development in India. It covers sectors like power, roadways, railways, oil and gas, and telecommunications. Some key points:
1. India plans major investments to expand infrastructure like doubling spending on infrastructure to $1 trillion under the 12th Five-Year Plan.
2. The power sector faces a large demand-supply gap and needs over 150,000 MW of additional generation capacity. Reforms are expected to boost growth across generation, transmission and distribution.
3. Road and rail projects include expanding national highways, building the Golden Quadrilateral network, developing high speed rail, and the Delhi-Mumbai Industrial Corridor project.
4. Oil and
5th in the AskTOM Office Hours series on graph database technologies. https://devgym.oracle.com/pls/apex/dg/office_hours/3084
PGQL: A Query Language for Graphs
Learn how to query graphs using PGQL, an expressive and intuitive graph query language that's a lot like SQL. With PGQL, it's easy to get going writing graph analysis queries to the database in a very short time. Albert and Oskar show what you can do with PGQL, and how to write and execute PGQL code.
The document discusses GRelC, a project that aims to design and deploy the first Grid Database Management System (Grid-DBMS) for the Globus community. It describes how GRelC allows for dynamic and transparent access to distributed, heterogeneous databases in a grid environment. Key features of GRelC include authentication, authorization, access control policies, data encryption, and support for single and multi-query operations across multiple database management systems.
Tech talk by Serena Signorelli (https://www.linkedin.com/in/serenasignorelli/) in the event ''Tensorflow and Sparklyr: Scaling Deep Learning and R to the Big Data ecosystem'', May 15, 2017 at ICTeam Grassobbio (BG). The event was part of the Data Science Milan Meetup (https://www.meetup.com/it-IT/Data-Science-Milan/).
Sparklyr: Big Data enabler for R users - Serena Signorelli, ICTEAMData Science Milan
This document provides an overview of Sparklyr, an R package that allows users to work with big data in Apache Spark from within R. It discusses Sparklyr's key features like using dplyr verbs to manipulate Spark DataFrames and access Spark ML routines. The presentation also compares Sparklyr to the native SparkR package and demonstrates how to analyze NYC taxi data with Sparklyr.
R is a programming language for statistical analysis and graphics. It is an open-source language developed by statisticians to allow for easy statistical analysis and visualization of data. The document provides an overview of R, discussing its origins, functionality, uses in data science, and popular packages and IDEs used with R. Examples are given of basic R syntax for vectors, matrices, data frames, plotting, and applying functions to data.
Extending Twitter's Data Platform to Google CloudDataWorks Summit
Twitter's Data Platform is built using multiple complex open source and in house projects to support Data Analytics on hundreds of petabytes of data. Our platform support storage, compute, data ingestion, discovery and management and various tools and libraries to help users for both batch and realtime analytics. Our DataPlatform operates on multiple clusters across different data centers to help thousands of users discover valuable insights. As we were scaling our Data Platform to multiple clusters, we also evaluated various cloud vendors to support use cases outside of our data centers. In this talk we share our architecture and how we extend our data platform to use cloud as another datacenter. We walk through our evaluation process, challenges we faced supporting data analytics at Twitter scale on cloud and present our current solution. Extending Twitter's Data platform to cloud was complex task which we deep dive in this presentation.
The Sierra Supercomputer: Science and Technology on a Missioninside-BigData.com
In this deck from the Stanford HPC Conference, Adam Bertsch from LLNL presents: The Sierra Supercomputer: Science and Technology on a Mission.
"LLNL just celebrated its 65th anniversary. Since 1952, the laboratory has been at the forefront of high performance computing. Initially, HPC was used to accelerate the design and testing of the nation's nuclear stockpile. Since the last U.S. nuclear test in 1992, HPC has been used to validate the safety, security, and reliability of stockpile without nuclear testing.
Our next flagship HPC system at LLNL will be called Sierra. A collaboration between multiple government and industry partners, Sierra and its sister system Summit at ORNL, will pave the way towards Exascale computing architectures and predictive capability."
Watch the video: https://wp.me/p3RLHQ-i4K
Learn more: https://computation.llnl.gov/computers/sierra
and
http://hpcadvisorycouncil.com
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
This document discusses using PostgreSQL and GPU acceleration to build a machine learning platform. It describes HeteroDB, which provides database and analytics acceleration using GPUs. It outlines how PostgreSQL's foreign data wrapper Gstore_fdw manages persistent GPU device memory, allowing data to remain on the GPU between queries for faster analytics. Gstore_fdw also enables inter-process data collaboration by allowing processes to share access to GPU memory using IPC handles. This facilitates integrating PostgreSQL with external analytics code in languages like Python.
The document proposes an IT infrastructure for Shiv LLC, a company with locations in Los Angeles, Dallas, and Houston. It recommends implementing an Active Directory domain to enable communication and file sharing across the three locations. A centralized file server would store common files and applications. Each location would have its own local area network, connected to the other sites and to the internet via VPN. Firewalls, antivirus software, and regular backups would help secure the network and protect company data. The design allows for future growth and expansion as the company scales up.
Twitter's Data Platform is built using multiple complex open source and in house projects to support Data Analytics on hundreds of petabytes of data. Our platform support storage, compute, data ingestion, discovery and management and various tools and libraries to help users for both batch and realtime analytics. Our DataPlatform operates on multiple clusters across different data centers to help thousands of users discover valuable insights. As we were scaling our Data Platform to multiple clusters, we also evaluated various cloud vendors to support use cases outside of our data centers. In this talk we share our architecture and how we extend our data platform to use cloud as another datacenter. We walk through our evaluation process, challenges we faced supporting data analytics at Twitter scale on cloud and present our current solution. Extending Twitter's Data platform to cloud was complex task which we deep dive in this presentation.
Extending Twitter's Data Platform to Google Cloud lohitvijayarenu
This document summarizes Twitter's project to extend its data platform from an on-premises only model to a hybrid on-premises and cloud model called Partly Cloudy. It discusses design considerations around user experience, scalability, and onboarding. It outlines the workstreams to replicate datasets to Google Cloud Storage while maintaining authentication, authorization, and audit controls. The project has enabled Twitter data processing users to access replicated datasets, use managed Hadoop and Presto clusters in Google Cloud, and explore other Google offerings.
The document discusses approaches for building real-time applications on Hadoop systems before using Impala. It recommends using HBase to store and query data in real-time, SolrCloud for secondary indexing, and streaming tools like Storm on YARN for continuously processing data. The document provides examples of querying log data and malware information in real-time. It emphasizes clarifying use cases, computing data batches efficiently, and minimizing the gap between batches to approach real-time capabilities. The document advises that Impala is not always needed and that the same problems can occur, so the three-arrow approach of HBase, SolrCloud, and streaming often provides good real-time functionality without overengineering the solution.
Netflix Machine Learning Infra for Recommendations - 2018Karthik Murugesan
Faisal Siddiqi presented on machine learning infrastructure for recommendations. He outlined Boson and AlgoCommons, two major ML infra components. Boson focuses on offline training for both ad-hoc exploration and production. It provides utilities for data transfer, feature schema, stratification, and feature transformers. AlgoCommons provides common abstractions and building blocks for ML like data access, feature encoders, predictors, and metrics. It aims for composability, portability, and avoiding training-serving skew.
ML Infra for Netflix Recommendations - AI NEXTCon talkFaisal Siddiqi
Faisal Siddiqi presented on machine learning infrastructure for recommendations. He outlined Boson and AlgoCommons, two major ML infra components. Boson focuses on offline training for both ad-hoc exploration and production. It provides utilities for data preparation, feature engineering, training, metrics, and visualization. AlgoCommons provides common abstractions and building blocks for ML like data access, feature encoders, predictors, and metrics. It aims for composability, portability, and avoiding training-serving skew.
Golden Gate - How to start such a project?Trivadis
This document provides information about starting a GoldenGate replication project. It discusses establishing a project plan, running a proof of concept, designing a topology, defining rules and processes, and preparing documentation and scripts. It emphasizes keeping the setup simple, configuring databases correctly to avoid unnecessary overhead, implementing critical components like patching, a repository to generate scripts, heartbeat monitoring, and multiple types of monitoring. It also stresses being prepared to verify replicated data between source and destination.
Unlock cassandra data for application developers using graphQLCédrick Lunven
This document discusses how Stargate provides a data gateway for unlocking Cassandra data for application developers through REST and GraphQL APIs. It introduces Stargate as an open source API framework that adds plugin support for new APIs, data types, and access methods to make it easy to use Cassandra for any application workload. It then covers the REST and GraphQL APIs provided by Stargate, how Stargate supports document and schemaless data through a document API, and how GraphQL queries can be mapped to CQL through both schema-first and CQL-first approaches.
The document discusses grid computing and the speaker's background in the topic. It provides key takeaways about understanding the evolution of technologies like grid computing and envisioning upcoming trends. It then discusses what a grid is, including early definitions, and elements of grid computing like resource sharing, coordinated problem solving, and dynamic virtual organizations. The document also outlines attributes of grid computing related to virtualization, dynamic provisioning, resource pooling, and self-adaptive software. It provides examples of how grids are used and lists common grid components.
GIS 5103 – Fundamentals of GISLecture 83D GIS.docxshericehewat
GIS 5103 – Fundamentals of GIS
Lecture 8
3D GIS
Dimensionality
A dimension is the minimum amount of coordinates needed to define the mathematical space of an object.
Lecture 8 – 3D GIS
2DA figure that has only length & height as its dimensions. 2D shapes lie on a flat surface; known as plane figures or plane shapes. While they have areas, 2D shapes have no volume.2D figures are plotted on two axes, the x- and y-axes.
Lecture 8 – 3D GIS
3DLength + Height + WidthX + Y + Z Volume + Surface AreaExamples include: 3D multi-patch building, roof, interior floors, and foundation would all contain different z-values for the same 2D coordinate. Aircraft's 3D position or a walking trail up a mountain, would only have a single z-value for each X,Y location.
Lecture 8 – 3D GIS
2.5DHighly used in GIS to represent Z data that is not continuous = 3DZ data does not need to be elevation. Pollution, # of cases, etc.
Lecture 8 – 3D GIS
3D file types .3dd.sxdWhen you import an ArcGlobe or ArcScene document:First the .3dd file opens by default in global mode Secondly the .sxd file opens in local mode. Any new blank scene view defaults to global mode.
Lecture 8 – 3D GIS
Data TypesVector FeaturesPoint / Line / Polygon Surface typesTIN (Triangular Irregular Networks)DEM’s (Digital Elevation Models)Raster SurfaceLAS Dataset
Lecture 8 – 3D GIS
3D StylesPointsGeometric ShapesModelsMarkersImportedLinesTextured SymbolsGeometric ShapesPolygonsTexture FillBasic Colors
Lecture 8 – 3D GIS
Lecture 8 – 3D GIS
Perspective ViewPerspective drawing is the most common drawing mode in 3D, where features in the foreground are shown larger than those off in the distance. This matches the way we see the world in our day-to-day lives, and the result is a realistic representation of 3D content. All scenes open in perspective viewing mode. You can switch between Perspective Perspective View and Parallel Isometric View viewing modes using the Drawing Mode drop-down menu in the Scene group on the View tab.
Lecture 8 – 3D GIS
Parallel / Isometric ViewParallel drawing renders the 3D view using a parallel projection, where features of the same physical size are rendered on-screen identically, regardless of their distance from the viewing camera. Parallel drawing is useful for architectural drawings, as well as for representing statistical data in a 3D view, such as extruded shapes symbolizing numeric values.
Lecture 8 – 3D GIS
3D Analyst ToolsData Conversion/PreparationTxt / Binary / Feature class / Raster / TINSurface CreationInterpolation / LASD CreationSurface AnalysisAspect / Slope / Contour / Feature Interpolation3D Operator & VisibilitySkyline / Inter-visibility / Sun Shadow Analysis
Lecture 8 – 3D GIS
There are five exploratory analysis tools:The Line of Sight tool creates sight lines to determine if one or more targets are visible from a given observer location.The View Dome tool determines the parts of a sphere that are visible from an observer locate ...
Pivotal Data Labs - Technology and Tools in our Data Scientist's Arsenal Srivatsan Ramanujam
These slides give an overview of the technology and the tools used by Data Scientists at Pivotal Data Labs. This includes Procedural Languages like PL/Python, PL/R, PL/Java, PL/Perl and the parallel, in-database machine learning library MADlib. The slides also highlight the power and flexibility of the Pivotal platform from embracing open source libraries in Python, R or Java to using new computing paradigms such as Spark on Pivotal HD.
Get the most out of Oracle Data Guard - OOW versionLudovico Caldara
If you use Oracle Data Guard feature just for data protection, you are using less than half of its potential. You already pay for it, so why not getting the most out of it? In this session I will show how you can use Oracle Data Guard capabilities for common tasks such as database cloning, database migration and reporting, with the help of other features included in Oracle Database Enterprise Edition
Similar to Graphing Enterprise IT – Representing IT Infrastructure and Business Processes as a Graph - Alan Robertson @ GraphConnect SF 2013 (20)
BT & Neo4j: Knowledge Graphs for Critical Enterprise Systems.pptx.pdfNeo4j
Presented at Gartner Data & Analytics, London Maty 2024. BT Group has used the Neo4j Graph Database to enable impressive digital transformation programs over the last 6 years. By re-imagining their operational support systems to adopt self-serve and data lead principles they have substantially reduced the number of applications and complexity of their operations. The result has been a substantial reduction in risk and costs while improving time to value, innovation, and process automation. Join this session to hear their story, the lessons they learned along the way and how their future innovation plans include the exploration of uses of EKG + Generative AI.
Atelier - Architecture d’applications de Graphes - GraphSummit ParisNeo4j
Atelier - Architecture d’applications de Graphes
Participez à cet atelier pratique animé par des experts de Neo4j qui vous guideront pour découvrir l’intelligence contextuelle. En utilisant un jeu de données réel, nous construirons étape par étape une solution de graphes ; de la construction du modèle de données de graphes à l’exécution de requêtes et à la visualisation des données. L’approche sera applicable à de multiples cas d’usages et industries.
Atelier - Innover avec l’IA Générative et les graphes de connaissancesNeo4j
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Allez au-delà du battage médiatique autour de l’IA et découvrez des techniques pratiques pour utiliser l’IA de manière responsable à travers les données de votre organisation. Explorez comment utiliser les graphes de connaissances pour augmenter la précision, la transparence et la capacité d’explication dans les systèmes d’IA générative. Vous partirez avec une expérience pratique combinant les relations entre les données et les LLM pour apporter du contexte spécifique à votre domaine et améliorer votre raisonnement.
Amenez votre ordinateur portable et nous vous guiderons sur la mise en place de votre propre pile d’IA générative, en vous fournissant des exemples pratiques et codés pour démarrer en quelques minutes.
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j
Dr. Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Découvrez les dernières innovations de Neo4j, et notamment les dernières intégrations cloud et les améliorations produits qui font de Neo4j un choix essentiel pour les développeurs qui créent des applications avec des données interconnectées et de l’IA générative.
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j
Dr. Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Découvrez les dernières innovations de Neo4j, et notamment les dernières intégrations cloud et les améliorations produits qui font de Neo4j un choix essentiel pour les développeurs qui créent des applications avec des données interconnectées et de l’IA générative.
SOPRA STERIA - GraphRAG : repousser les limitations du RAG via l’utilisation ...Neo4j
Romain CAMPOURCY – Architecte Solution, Sopra Steria
Patrick MEYER – Architecte IA Groupe, Sopra Steria
La Génération de Récupération Augmentée (RAG) permet la réponse à des questions d’utilisateur sur un domaine métier à l’aide de grands modèles de langage. Cette technique fonctionne correctement lorsque la documentation est simple mais trouve des limitations dès que les sources sont complexes. Au travers d’un projet que nous avons réalisé, nous vous présenterons l’approche GraphRAG, une nouvelle approche qui utilise une base Neo4j générée pour améliorer la compréhension des documents et la synthèse d’informations. Cette méthode surpasse l’approche RAG en fournissant des réponses plus holistiques et précises.
ADEO - Knowledge Graph pour le e-commerce, entre challenges et opportunités ...Neo4j
Charles Gouwy, Business Product Leader, Adeo Services (Groupe Leroy Merlin)
Alors que leur Knowledge Graph est déjà intégré sur l’ensemble des expériences d’achat de leur plateforme e-commerce depuis plus de 3 ans, nous verrons quelles sont les nouvelles opportunités et challenges qui s’ouvrent encore à eux grâce à leur utilisation d’une base de donnée de graphes et l’émergence de l’IA.
GraphSummit Paris - The art of the possible with Graph TechnologyNeo4j
Sudhir Hasbe, Chief Product Officer, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
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.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
GraphAware - Transforming policing with graph-based intelligence analysisNeo4j
Petr Matuska, Sales & Sales Engineering Lead, GraphAware
Western Australia Police Force’s adoption of Neo4j and the GraphAware Hume graph analytics platform marks a significant advancement in data-driven policing. Facing the challenges of growing volumes of valuable data scattered in disconnected silos, the organisation successfully implemented Neo4j database and Hume, consolidating data from various sources into a dynamic knowledge graph. The result was a connected view of intelligence, making it easier for analysts to solve crime faster. The partnership between Neo4j and GraphAware in this project demonstrates the transformative impact of graph technology on law enforcement’s ability to leverage growing volumes of valuable data to prevent crime and protect communities.
GraphSummit Stockholm - Neo4j - Knowledge Graphs and Product UpdatesNeo4j
David Pond, Lead Product Manager, 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.
Implementations of Fused Deposition Modeling in real worldEmerging Tech
The presentation showcases the diverse real-world applications of Fused Deposition Modeling (FDM) across multiple industries:
1. **Manufacturing**: FDM is utilized in manufacturing for rapid prototyping, creating custom tools and fixtures, and producing functional end-use parts. Companies leverage its cost-effectiveness and flexibility to streamline production processes.
2. **Medical**: In the medical field, FDM is used to create patient-specific anatomical models, surgical guides, and prosthetics. Its ability to produce precise and biocompatible parts supports advancements in personalized healthcare solutions.
3. **Education**: FDM plays a crucial role in education by enabling students to learn about design and engineering through hands-on 3D printing projects. It promotes innovation and practical skill development in STEM disciplines.
4. **Science**: Researchers use FDM to prototype equipment for scientific experiments, build custom laboratory tools, and create models for visualization and testing purposes. It facilitates rapid iteration and customization in scientific endeavors.
5. **Automotive**: Automotive manufacturers employ FDM for prototyping vehicle components, tooling for assembly lines, and customized parts. It speeds up the design validation process and enhances efficiency in automotive engineering.
6. **Consumer Electronics**: FDM is utilized in consumer electronics for designing and prototyping product enclosures, casings, and internal components. It enables rapid iteration and customization to meet evolving consumer demands.
7. **Robotics**: Robotics engineers leverage FDM to prototype robot parts, create lightweight and durable components, and customize robot designs for specific applications. It supports innovation and optimization in robotic systems.
8. **Aerospace**: In aerospace, FDM is used to manufacture lightweight parts, complex geometries, and prototypes of aircraft components. It contributes to cost reduction, faster production cycles, and weight savings in aerospace engineering.
9. **Architecture**: Architects utilize FDM for creating detailed architectural models, prototypes of building components, and intricate designs. It aids in visualizing concepts, testing structural integrity, and communicating design ideas effectively.
Each industry example demonstrates how FDM enhances innovation, accelerates product development, and addresses specific challenges through advanced manufacturing capabilities.
Measuring the Impact of Network Latency at TwitterScyllaDB
Widya Salim and Victor Ma will outline the causal impact analysis, framework, and key learnings used to quantify the impact of reducing Twitter's network latency.
RPA In Healthcare Benefits, Use Case, Trend And Challenges 2024.pptxSynapseIndia
Your comprehensive guide to RPA in healthcare for 2024. Explore the benefits, use cases, and emerging trends of robotic process automation. Understand the challenges and prepare for the future of healthcare automation
TrustArc Webinar - 2024 Data Privacy Trends: A Mid-Year Check-InTrustArc
Six months into 2024, and it is clear the privacy ecosystem takes no days off!! Regulators continue to implement and enforce new regulations, businesses strive to meet requirements, and technology advances like AI have privacy professionals scratching their heads about managing risk.
What can we learn about the first six months of data privacy trends and events in 2024? How should this inform your privacy program management for the rest of the year?
Join TrustArc, Goodwin, and Snyk privacy experts as they discuss the changes we’ve seen in the first half of 2024 and gain insight into the concrete, actionable steps you can take to up-level your privacy program in the second half of the year.
This webinar will review:
- Key changes to privacy regulations in 2024
- Key themes in privacy and data governance in 2024
- How to maximize your privacy program in the second half of 2024
Are you interested in dipping your toes in the cloud native observability waters, but as an engineer you are not sure where to get started with tracing problems through your microservices and application landscapes on Kubernetes? Then this is the session for you, where we take you on your first steps in an active open-source project that offers a buffet of languages, challenges, and opportunities for getting started with telemetry data.
The project is called openTelemetry, but before diving into the specifics, we’ll start with de-mystifying key concepts and terms such as observability, telemetry, instrumentation, cardinality, percentile to lay a foundation. After understanding the nuts and bolts of observability and distributed traces, we’ll explore the openTelemetry community; its Special Interest Groups (SIGs), repositories, and how to become not only an end-user, but possibly a contributor.We will wrap up with an overview of the components in this project, such as the Collector, the OpenTelemetry protocol (OTLP), its APIs, and its SDKs.
Attendees will leave with an understanding of key observability concepts, become grounded in distributed tracing terminology, be aware of the components of openTelemetry, and know how to take their first steps to an open-source contribution!
Key Takeaways: Open source, vendor neutral instrumentation is an exciting new reality as the industry standardizes on openTelemetry for observability. OpenTelemetry is on a mission to enable effective observability by making high-quality, portable telemetry ubiquitous. The world of observability and monitoring today has a steep learning curve and in order to achieve ubiquity, the project would benefit from growing our contributor community.
Choose our Linux Web Hosting for a seamless and successful online presencerajancomputerfbd
Our Linux Web Hosting plans offer unbeatable performance, security, and scalability, ensuring your website runs smoothly and efficiently.
Visit- https://onliveserver.com/linux-web-hosting/
Details of description part II: Describing images in practice - Tech Forum 2024BookNet Canada
This presentation explores the practical application of image description techniques. Familiar guidelines will be demonstrated in practice, and descriptions will be developed “live”! If you have learned a lot about the theory of image description techniques but want to feel more confident putting them into practice, this is the presentation for you. There will be useful, actionable information for everyone, whether you are working with authors, colleagues, alone, or leveraging AI as a collaborator.
Link to presentation recording and transcript: https://bnctechforum.ca/sessions/details-of-description-part-ii-describing-images-in-practice/
Presented by BookNet Canada on June 25, 2024, with support from the Department of Canadian Heritage.
Support en anglais diffusé lors de l'événement 100% IA organisé dans les locaux parisiens d'Iguane Solutions, le mardi 2 juillet 2024 :
- Présentation de notre plateforme IA plug and play : ses fonctionnalités avancées, telles que son interface utilisateur intuitive, son copilot puissant et des outils de monitoring performants.
- REX client : Cyril Janssens, CTO d’ easybourse, partage son expérience d’utilisation de notre plateforme IA plug & play.
Quality Patents: Patents That Stand the Test of TimeAurora Consulting
Is your patent a vanity piece of paper for your office wall? Or is it a reliable, defendable, assertable, property right? The difference is often quality.
Is your patent simply a transactional cost and a large pile of legal bills for your startup? Or is it a leverageable asset worthy of attracting precious investment dollars, worth its cost in multiples of valuation? The difference is often quality.
Is your patent application only good enough to get through the examination process? Or has it been crafted to stand the tests of time and varied audiences if you later need to assert that document against an infringer, find yourself litigating with it in an Article 3 Court at the hands of a judge and jury, God forbid, end up having to defend its validity at the PTAB, or even needing to use it to block pirated imports at the International Trade Commission? The difference is often quality.
Quality will be our focus for a good chunk of the remainder of this season. What goes into a quality patent, and where possible, how do you get it without breaking the bank?
** Episode Overview **
In this first episode of our quality series, Kristen Hansen and the panel discuss:
⦿ What do we mean when we say patent quality?
⦿ Why is patent quality important?
⦿ How to balance quality and budget
⦿ The importance of searching, continuations, and draftsperson domain expertise
⦿ Very practical tips, tricks, examples, and Kristen’s Musts for drafting quality applications
https://www.aurorapatents.com/patently-strategic-podcast.html
Blockchain technology is transforming industries and reshaping the way we conduct business, manage data, and secure transactions. Whether you're new to blockchain or looking to deepen your knowledge, our guidebook, "Blockchain for Dummies", is your ultimate resource.
The DealBook is our annual overview of the Ukrainian tech investment industry. This edition comprehensively covers the full year 2023 and the first deals of 2024.
論文紹介:A Systematic Survey of Prompt Engineering on Vision-Language Foundation ...Toru Tamaki
Jindong Gu, Zhen Han, Shuo Chen, Ahmad Beirami, Bailan He, Gengyuan Zhang, Ruotong Liao, Yao Qin, Volker Tresp, Philip Torr "A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models" arXiv2023
https://arxiv.org/abs/2307.12980
Advanced Techniques for Cyber Security Analysis and Anomaly DetectionBert Blevins
Cybersecurity is a major concern in today's connected digital world. Threats to organizations are constantly evolving and have the potential to compromise sensitive information, disrupt operations, and lead to significant financial losses. Traditional cybersecurity techniques often fall short against modern attackers. Therefore, advanced techniques for cyber security analysis and anomaly detection are essential for protecting digital assets. This blog explores these cutting-edge methods, providing a comprehensive overview of their application and importance.
Understanding Insider Security Threats: Types, Examples, Effects, and Mitigat...Bert Blevins
Today’s digitally connected world presents a wide range of security challenges for enterprises. Insider security threats are particularly noteworthy because they have the potential to cause significant harm. Unlike external threats, insider risks originate from within the company, making them more subtle and challenging to identify. This blog aims to provide a comprehensive understanding of insider security threats, including their types, examples, effects, and mitigation techniques.
Understanding Insider Security Threats: Types, Examples, Effects, and Mitigat...
Graphing Enterprise IT – Representing IT Infrastructure and Business Processes as a Graph - Alan Robertson @ GraphConnect SF 2013
1. Modeling IT Infrastucture
using
The Assimilation Project
#AssimProj
@OSSAlanR
http://assimproj.org/
http://bit.ly/AssimGC2013
Alan Robertson <alanr@unix.sh>
Assimilation Systems Limited
http://assimilationsystems.com
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