Discover what exists with Ontology2

•Download as PPTX, PDF•

1 like•583 views

How it all started Photo Credit: Daniel Sparing The slides to this talk are licensed CC-BY-SA/3.0

Flickr kills the dream…

But Creative Commons Saves the Day

animalphotos.info

dbpedia & the semantic web Subject Predicate (Verb) Object <dbpedia:Albatross> <rdf:type> <dbpedia-owl:Bird> . http://dbpedia.org/ontology/Bird http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://dbpedia.org/resource/Albatross

the linked data cloud “Linking Open Data cloud diagram, by Richard Cyganiak and AnjaJentzsch. http://lod-cloud.net/”

automating the process search for candidates Identify topics filter correct images describe images dbpedia flickr

amazon mechanical turk

carpictures.cc

the business model

how many things exist? The game of 20 questions  220 = about a million…

what sort of things exist? “Everything on Earth:” Places, People, Creative Works, Life Forms, Technological Artifacts

ny-pictures.com

exploring the earth’s noösphere Noösphere, according to the thought of Vladimir Vernadsky and Teilhard de Chardin, denotes the "sphere of human thought".

ookaboo.com takes off

ookaboo semantic API http://en.wikipedia.org/wiki/Thailand API Thanks: Andyindia, Echiner1, Rene Eherhardt

Why don’t computers understand human language? The Ink is In The Pen The Pig is In The Pen Thanks: Seaniz, GiangHồThịHoàng, Claudia Scholz and

the human memome project One ring to bind them all?

Top-down? Bottom-up? Both! Merge data from a wide range of sources, continuously test against reality by performance in practical applications

Ontology2: Long Term Evolution

More Related Content

Similar to Discover what exists with Ontology2

Describing Everything - Open Web standards and classiﬁcation

Describing Everything - Open Web standards and classiﬁcation

Describing Everything - Open Web standards and classiﬁcation

RBMS LODLAM presentation

RBMS LODLAM presentation

RBMS LODLAM presentation

Web 2.0 and virtual worlds

Web 2.0 and virtual worlds

Web 2.0 and virtual worlds

Bryan Alexander

What would you do with free pictures of everything on Earth?

What would you do with free pictures of everything on Earth?

What would you do with free pictures of everything on Earth?

Understanding the Standards Gap

Understanding the Standards Gap

Understanding the Standards Gap

Preparing for the Impact of Web 3.0

Preparing for the Impact of Web 3.0

Preparing for the Impact of Web 3.0

Radically Open at the National Archives

Radically Open at the National Archives

Radically Open at the National Archives

Presented at Emerce eDay 2014 in Amsterdam. "The embrace of Big Data is generating massive pools of information about consumers in an attempt to create profiles that can be understood, sold to, advertised to, and increasingly treated like the real "us". But as we cast more data shadows, these digital portraits of us take on a life of their own, for better or for worse. Scott will examine what's happening as we go from personalization to digital duplicates to world where our data selves—shadow selves—may become more important and influential than our real personas."

SHADOW SELVES: LIVING WITH (OR WITHOUT) OUR BIG DATA DOUBLES

SHADOW SELVES: LIVING WITH (OR WITHOUT) OUR BIG DATA DOUBLES

SHADOW SELVES: LIVING WITH (OR WITHOUT) OUR BIG DATA DOUBLES

Semantic Web: an Introduction

Semantic Web: an Introduction

Semantic Web: an Introduction

Luigi De Russis

Google, IBM, Microsoft, Apple, Facebook, Baidu, Foxconn, and others have recently made multi-billion dollar investments in artificial intelligence and robotics. Some of these investments are aimed at increasing productivity and enhancing coordination and cooperation. Others are aimed at creating strategic gains in competitive interactions. This is creating "arms races" in high-frequency trading, cyber warfare, drone warfare, stealth technology, surveillance systems, and missile warfare. Recently, Stephen Hawking, Elon Musk, and others have issued strong cautionary statements about the safety of intelligent technologies. We describe the potentially antisocial "rational drives" of self-preservation, resource acquisition, replication, and self-improvement that uncontrolled autonomous systems naturally exhibit. We describe the "Safe-AI Scaffolding Strategy" for developing these systems with a high confidence of safety based on the insight that even superintelligences are constrained by mathematical proof and cryptographic complexity. It appears that we are at an inflection point in the development of intelligent technologies and that the choices we make today will have a dramatic impact on the future of humanity. Video of the talk: https://www.parc.com/event/2127/ai-and-robotics-at-an-inflection-point.html

AI and Robotics at an Inflection Point

AI and Robotics at an Inflection Point

AI and Robotics at an Inflection Point

Steve Omohundro

TFS Talk by Hackathorn 20100527 v2

TFS Talk by Hackathorn 20100527 v2

TFS Talk by Hackathorn 20100527 v2

Richard Hackathorn

SC in SL

Catherine Buck Morgan

The Empirical Turn in Knowledge Representation

The Empirical Turn in Knowledge Representation

The Empirical Turn in Knowledge Representation

Frank van Harmelen

Cet

Web 3.0

Speech acts meet tagging: NiceTag ontology (Pragmatic Web)

Speech acts meet tagging: NiceTag ontology (Pragmatic Web)

Speech acts meet tagging: NiceTag ontology (Pragmatic Web)

Alexandre Monnin

ALIAOnline Practical Linked (Open) Data for Libraries, Archives & Museums

ALIAOnline Practical Linked (Open) Data for Libraries, Archives & Museums

ALIAOnline Practical Linked (Open) Data for Libraries, Archives & Museums

Media Web Meet-up 1: CC "Rock'n'Rebirth"

Media Web Meet-up 1: CC "Rock'n'Rebirth"

Media Web Meet-up 1: CC "Rock'n'Rebirth"

Mike Linksvayer

ieee cloud 2015 keynote talk

ieee cloud 2015 keynote talk

ieee cloud 2015 keynote talk

Microsoft Azure for Research

Jupyter notebooks are transforming the way we look at computing, coding, and problem-solving. But is this the only “data scientist experience” that this technology can provide? In this talk, Natalino will sketch how you could use Jupyter to create interactive and compelling data science web applications and provide new ways of data exploration and analysis. In the background, these apps are still powered by well understood and documented Jupyter notebooks.

Data Science Apps: Beyond Notebooks - Natalino Busa - Codemotion Amsterdam 2017

Data Science Apps: Beyond Notebooks - Natalino Busa - Codemotion Amsterdam 2017

Data Science Apps: Beyond Notebooks - Natalino Busa - Codemotion Amsterdam 2017

Similar to Discover what exists with Ontology2 (20)

Describing Everything - Open Web standards and classiﬁcation

Describing Everything - Open Web standards and classiﬁcation

Describing Everything - Open Web standards and classiﬁcation

RBMS LODLAM presentation

RBMS LODLAM presentation

RBMS LODLAM presentation

Web 2.0 and virtual worlds

Web 2.0 and virtual worlds

Web 2.0 and virtual worlds

What would you do with free pictures of everything on Earth?

What would you do with free pictures of everything on Earth?

What would you do with free pictures of everything on Earth?

Understanding the Standards Gap

Understanding the Standards Gap

Understanding the Standards Gap

Preparing for the Impact of Web 3.0

Preparing for the Impact of Web 3.0

Preparing for the Impact of Web 3.0

Radically Open at the National Archives

Radically Open at the National Archives

Radically Open at the National Archives

SHADOW SELVES: LIVING WITH (OR WITHOUT) OUR BIG DATA DOUBLES

SHADOW SELVES: LIVING WITH (OR WITHOUT) OUR BIG DATA DOUBLES

SHADOW SELVES: LIVING WITH (OR WITHOUT) OUR BIG DATA DOUBLES

Semantic Web: an Introduction

Semantic Web: an Introduction

Semantic Web: an Introduction

AI and Robotics at an Inflection Point

AI and Robotics at an Inflection Point

AI and Robotics at an Inflection Point

TFS Talk by Hackathorn 20100527 v2

TFS Talk by Hackathorn 20100527 v2

TFS Talk by Hackathorn 20100527 v2

SC in SL

The Empirical Turn in Knowledge Representation

The Empirical Turn in Knowledge Representation

The Empirical Turn in Knowledge Representation

Cet

Web 3.0

Speech acts meet tagging: NiceTag ontology (Pragmatic Web)

Speech acts meet tagging: NiceTag ontology (Pragmatic Web)

Speech acts meet tagging: NiceTag ontology (Pragmatic Web)

ALIAOnline Practical Linked (Open) Data for Libraries, Archives & Museums

ALIAOnline Practical Linked (Open) Data for Libraries, Archives & Museums

ALIAOnline Practical Linked (Open) Data for Libraries, Archives & Museums

Media Web Meet-up 1: CC "Rock'n'Rebirth"

Media Web Meet-up 1: CC "Rock'n'Rebirth"

Media Web Meet-up 1: CC "Rock'n'Rebirth"

ieee cloud 2015 keynote talk

ieee cloud 2015 keynote talk

ieee cloud 2015 keynote talk

Data Science Apps: Beyond Notebooks - Natalino Busa - Codemotion Amsterdam 2017

Data Science Apps: Beyond Notebooks - Natalino Busa - Codemotion Amsterdam 2017

Data Science Apps: Beyond Notebooks - Natalino Busa - Codemotion Amsterdam 2017

More from Paul Houle

Chatbots are growing in popularity as developers face the limitations of the mobile app. User interfaces that simulate a human conversation, the history of chatbots goes back to the late 18th century. I'll take you on a tour of that history with an eye on finding insights on what is possible today and in the near future with chatbots. Issues Covered: Amazon Alexa, Facebook Messenger Chatbots, Alan Turing, and much more.

Chatbots in 2017 -- Ithaca Talk Dec 6

Chatbots in 2017 -- Ithaca Talk Dec 6

Chatbots in 2017 -- Ithaca Talk Dec 6

Nowadays software companies are facing a fierce competition to deliver better products but offering a higher value to the customer. In this context, software product value has becoming a major concern in software industry, leading for improving the knowledge and better understanding about how to estimate the software value in early development phases. Other way, software companies encounter problems such as releasing products that were developed with high expectations, but they gradually fall into the category of a mediocre product when they are released to the market. These high expectations are tightly related to the expected and offered software value to the customer. This paper presents an approach for estimating the software product value, focusing on the development phases. We propose a value indicators approach to quantify the real value of the development products. The aim is early identifying potential deviations in the real software value, by comparing the estimated versus the expected. We present an internal validation to show the feasibility of this approach to produce benefits in industry projects.

Estimating the Software Product Value during the Development Process

Estimating the Software Product Value during the Development Process

Estimating the Software Product Value during the Development Process

Individual Records are supposed be updated yearly, but more than 25% of records have lapsed LEI records must be updated sooner in response to corporate actions if the GLEIS is to be useful as golden copy reference data inside financial institutions Needed: real-time, streaming analytics to monitor SIFI, trading and the buildup of systemic risk LOUs publish records daily, which are concatenated by the LOUS: however, the data on organization types (Corporation, Fund, Trust, etc.), Geographic Regions, Business Registry Numbers, Hierarchy and other fields are often missing or inconsistently represented Implementing Reference Dataand Corporate Actions in a Blockchain

Universal Standards for LEI and other Corporate Reference Data: Enabling risk...

Universal Standards for LEI and other Corporate Reference Data: Enabling risk...

Universal Standards for LEI and other Corporate Reference Data: Enabling risk...

We apply bitemporal analysis to more than 500 daily data files supplied by the Global Legal Entity Identifier Foundation to show that churn dominates the dynamics of growth, such that the number of paid up records in full standing has been flat over the last year. Our analysis reveals occasional daily glitches in the past that affected thousands of records. These appear to be in better control now, but a high lapse rate is the primary challenge to the Global LEI System right now

Fixing a leaky bucket; Observations on the Global LEI System

Fixing a leaky bucket; Observations on the Global LEI System

Fixing a leaky bucket; Observations on the Global LEI System

Cisco Fog Strategy For Big and Smart Data

Cisco Fog Strategy For Big and Smart Data

Cisco Fog Strategy For Big and Smart Data

Although animals do not use language, they are capable of many of the same kinds of cognition as us; much of our experience is at a non-verbal level. Semantics is the bridge between surface forms used in language and what we do and experience. Language understanding depends on world knowledge (i.e. “the pig is in the pen” vs. “the ink is in the pen”) We might not be ready for executives to specify policies themselves, but we can make the process from specification to behavior more automated, linked to precise vocabulary, and more traceable. Advances such as SVBR and an English serialization for ISO Common Logic means that executives and line workers can understand why the system does certain things, or verify that policies and regulations are implemented

Making the semantic web work

Making the semantic web work

Making the semantic web work

Ontology2 platform

Ontology2 platform

Ontology2 platform

I got started with relational databases with mysql, so I’m in the habit of making database changes with SQL scripts, rather than using a GUI. Microsoft SQL Server requires that we specify the name of a unique constraint when we want to drop it. If you’re thinking ahead, you can specify a name when you create the constraint; if you don’t, SQL Server will make up an unpredictable name, so you can’t write a simple script to drop the constraint.

Dropping unique constraints in sql server

Dropping unique constraints in sql server

Dropping unique constraints in sql server

This is a story of two types: GenericType and SpecificType, where GenericType is a superclass of SpecificType. There are two types of explicit cast in C#: The Prefix cast: [01] GenericType g=...; [02] SpecificType t=(SpecificType) g; The as cast: [03] GenericType g=...; [04] SpecificType t=g as SpecificType; Most programmers have a habit of using one or the other — this isn’t usually a conscious decision, but more of a function of which form a programmer saw first. I, for instance, programmed in Java before I learned C#, so I was already in the prefix cast habit. People with a Visual Basic background often do the opposite. There are real differences between the two casting operators

Prefix casting versus as-casting in c#

Prefix casting versus as-casting in c#

Prefix casting versus as-casting in c#

I'm an expert on building commerical large scale systems based on Linked Data sources such as Freebase and DBpedia. I'm the creator of :BaseKB, which was the first correct conversion of Freebase to RDF and of Infovore, the open source I do consulting on the following areas: * Data processing with Hadoop and the design and construction of systems using Amazon Web Services * Architecture and construction of systems that consume and produce Linked Data * Construction and evaluation of intelligent systems that make subjective decisions (text search, text classification, machine learning, etc.) I'm not at all interested in doing maintenance work on other people's code, but I am interested in helping you align your process, structure, and tools to speed up your development cycle, improve your products, and prevent developer burnout. I am not free to relocate at this time, but I collaborate all of the time with workers around the world and I can travel to your location, understand your needs and transfer skills to your workforce.

Paul houle resume

Paul houle resume

Paul houle resume

There’s a lot of confusion about how asynchronous communication works in RIA’s such as Silverlight, GWT and Javascript. When I start talking about the problems of concurrency control, many people tell me that there aren’t any concurrency problems since everything runs in a single thread. [1] It’s important to understand the basics of what is going on when you’re writing asynchronous code, so I’ve put together a simple example to show how execution works in RIA’s and how race conditions are possible. This example applies to Javascript, Silverlight, GWT and Flex, as well as a number of other environments based on Javascript. This example doesn’t represent best practices, but rather what can happen when you’re not using a proactive strategy that eliminates concurrency problems

Keeping track of state in asynchronous callbacks

Keeping track of state in asynchronous callbacks

Keeping track of state in asynchronous callbacks

Mat Byrne recently posted source code for a dynamic domain object in PHP which takes advantage of the dynamic nature of PHP. It’s a good example of how programmers can take advantage of the unique characteristics of a programming language. Statically typed languages such as C# and Java have some advantages: they run faster and IDE’s can understand the code enough to save typing (with your fingers), help you refactor your code, and help you fix errors. Although there’s a lot of things I like symfony, it feels like a Java framework that’s invaded the PHP world. Eclipse would help you deal with the endless getters and setters and domain object methods with 40-character names in Java, Eclipse. The limits of polymorphism are a serious weakness of today’s statically typed languages. C# and Java apps that I work with are filled with if-then-else or case ladders when they need to initialize a dynamically chosen instance of one of a set of classes that subclass a particular base class or that implement a particular interface. Sure, you can make a HashMap or Dictionary that’s filled with Factory objects, but any answer for that is cumbersome. I

Embrace dynamic PHP

Embrace dynamic PHP

Embrace dynamic PHP

articles on asynchronous communications with a focus on Javascript. Minimizing Code Paths In Asynchronous Code, a recent post of his, is about a lesson that I learned the hard way with GWT that applies to all RIA systems that use asynchronous calls. His example is the same case I encountered, where a function might return a value from a cache or might query the server to get the value: an obvious way to do this in psuedocode is: function getData(...arguments...,callback) { if (... data in cache...) { callback(...cached data...); } cacheCallback=anonymousFunction(...return value...) { ... store value in cache... callback(...cached data...); } getDataFromServer(...arguments...,cacheCallback) } At first glance this code looks innocuous, but there’s a major difference between what happens in the cached and uncached case. In the cached case, the callback() function gets called before getData() returns — in the uncached case, the opposite happens. What happens in this function has a global impact on the execution of the program, opening up two code paths that complicate concurrency control and introduce bugs that can be frustrating to debug. This function can be made more reliable if it schedules callback() to run after the thread it is running in completes. In Javascript, this can be done with setTimeout(). In Silverlight use System.Windows.Threading.Dispatcher. to schedule the callback

Once asynchronous, always asynchronous

Once asynchronous, always asynchronous

Once asynchronous, always asynchronous

This article is a follow up to “Don’t Catch Exceptions“, which advocates that exceptions should (in general) be passed up to a “unit of work”, that is, a fairly coarse-grained activity which can reasonably be failed, retried or ignored. A unit of work could be: an entire program, for a command-line script, a single web request in a web application, the delivery of an e-mail message the handling of a single input record in a batch loading application, rendering a single frame in a media player or a video game, or an event handler in a GUI program The code around the unit of work may look something like [01] try { [02] DoUnitOfWork() [03] } catch(Exception e) { [04] ... examine exception and decide what to do ... [05] } For the most part, the code inside DoUnitOfWork() and the functions it calls tries to throw exceptions upward rather than catch them. To handle errors correctly, you need to answer a few questions, such as Was this error caused by a corrupted application state? Did this error cause the application state to be corrupted? Was this error caused by invalid input? What do we tell the user, the developers and the system administrator? Could this operation succeed if it was retried? Is there something else we could do? Although it’s good to depend on existing exception

What do you do when you’ve caught an exception?

What do you do when you’ve caught an exception?

What do you do when you’ve caught an exception?

Extension methods are the most controversial feature that Microsoft has introduced in C# 3.0. Introduced to support the LINQ query framework, extension methods make it possible to define new methods for existing classes. Although extension methods can greatly simplify code that uses them, many are concerned that they could transform C# into something that programmers find unrecognizable, or that C#’s namespace mechanisms are inadequate for managing large systems that use extension methods. Adoption of the LINQ framework, however, means that extension methods are here to stay, and that .net programmers need to understand how to use them effectively, and, in particular, how extension methods are different from regular methods.

Extension methods, nulls, namespaces and precedence in c#

Extension methods, nulls, namespaces and precedence in c#

Extension methods, nulls, namespaces and precedence in c#

ProAlign Web is sold on a “Software as a Service” basis, which eliminates the burden and costs of software installation, maintenance, and any server requirements. Upgrades happen seamlessly without your involvement. Users have permission levels for manipulating and viewing data — the system will show only those geographic areas authorized for each user. It's easy to create, share, modify and approve alignments online — visualization tools allow immediate understanding of key account metrics by territory Built in communication — allows integrated notes, requests and approval processes. Every installation of ProAlign Web is fully integrated with and includes ProAlign Desktop. Built on ESRI ArcGIS ® mapping technology, the world’s number one mapping software. ProAlign Desktop offers an additional robust portfolio of analytical, database and mapping features for the sales manager or sales operations analyst.

Pro align snap 2

Pro align snap 2

Pro align snap 2

Companies with large, decentralized sales forces, multiple layers of sales management, and a collaborative approach to managing sales territories are a perfect fit for ProAlign Web sales territory alignment software. You can cooperatively create, modify and share territory alignments online, gaining input from sales managers anywhere in your organization who have the local account and customer knowledge critical to designing optimal territories. Sometimes getting field and local sales personnel involved can be a logistics challenge and lead to delays in completing new territory assignments. Not anymore. ProAlign Web provides secure online access for authorized sales management to view and propose changes to territory alignments. You’ll save weeks on complex sales territory projects.

Proalign Snapshot 1

Proalign Snapshot 1

Proalign Snapshot 1

TextWise has recently developed Semantic Gist® to provide intuitive semantic modeling on a large number of samples, particularly vertical text documents that often do not have classification schemes associated with them. These semantic models will automatically adapt to rapidly changing content, ensuring a high level of accuracy over time. Semantic Gist® represents a significant advance in the use of machine learning, image and speech characterization, and neural networks to attack unsupervised semantic modeling. Our patent-pending approach generates a compact representation of any text by using advanced statistical language models to identify the significant features of a document. An auto-encoder neural network encodes the features into a low-dimensionality semantic representation, and then reconstructs an approximation of the original feature vector from the semantic representation. The software highlights keywords that may be underrepresented by the semantic representation and encodes these separately as a complementary feature vector. Finally, the complementary feature vector is combined with the semantic representation to produce a Semantic Gist® that can be easily used for document indexing, matching and other applications.

Text wise technology textwise company, llc

Text wise technology textwise company, llc

Text wise technology textwise company, llc

User management is essential for community and interactive web systems. User management is often an afterthought in a project; although it is critical to the usability (a user that can't register log in can't use the service) and managability of a site, developers often build ad hoc solutions that are unreliable, insecure and hard to use. Tapir User Manager is a user management system that's been used to support large traffic sites. This presentation introduces TUM and explains how it's been used for projects at CUL and elsewhere.

Tapir user manager

Tapir user manager

Tapir user manager

The Global Performing Arts Database

The Global Performing Arts Database

The Global Performing Arts Database

More from Paul Houle (20)

Chatbots in 2017 -- Ithaca Talk Dec 6

Chatbots in 2017 -- Ithaca Talk Dec 6

Chatbots in 2017 -- Ithaca Talk Dec 6

Estimating the Software Product Value during the Development Process

Estimating the Software Product Value during the Development Process

Estimating the Software Product Value during the Development Process

Universal Standards for LEI and other Corporate Reference Data: Enabling risk...

Universal Standards for LEI and other Corporate Reference Data: Enabling risk...

Universal Standards for LEI and other Corporate Reference Data: Enabling risk...

Fixing a leaky bucket; Observations on the Global LEI System

Fixing a leaky bucket; Observations on the Global LEI System

Fixing a leaky bucket; Observations on the Global LEI System

Cisco Fog Strategy For Big and Smart Data

Cisco Fog Strategy For Big and Smart Data

Cisco Fog Strategy For Big and Smart Data

Making the semantic web work

Making the semantic web work

Making the semantic web work

Ontology2 platform

Ontology2 platform

Ontology2 platform

Dropping unique constraints in sql server

Dropping unique constraints in sql server

Dropping unique constraints in sql server

Prefix casting versus as-casting in c#

Prefix casting versus as-casting in c#

Prefix casting versus as-casting in c#

Paul houle resume

Paul houle resume

Paul houle resume

Keeping track of state in asynchronous callbacks

Keeping track of state in asynchronous callbacks

Keeping track of state in asynchronous callbacks

Embrace dynamic PHP

Embrace dynamic PHP

Embrace dynamic PHP

Once asynchronous, always asynchronous

Once asynchronous, always asynchronous

Once asynchronous, always asynchronous

What do you do when you’ve caught an exception?

What do you do when you’ve caught an exception?

What do you do when you’ve caught an exception?

Extension methods, nulls, namespaces and precedence in c#

Extension methods, nulls, namespaces and precedence in c#

Extension methods, nulls, namespaces and precedence in c#

Pro align snap 2

Pro align snap 2

Pro align snap 2

Proalign Snapshot 1

Proalign Snapshot 1

Proalign Snapshot 1

Text wise technology textwise company, llc

Text wise technology textwise company, llc

Text wise technology textwise company, llc

Tapir user manager

Tapir user manager

Tapir user manager

The Global Performing Arts Database

The Global Performing Arts Database

The Global Performing Arts Database

Recently uploaded

In this session, we will showcase how to revolutionize automated testing for your software, automation, and QA teams with UiPath Test Suite. In part 1 of UiPath test automation using UiPath Test Suite – developer series, we will cover, Software testing overview What is software testing Why software testing is required Typical test types and levels Continuous testing and challenges Introduction to UiPath Test Suite UiPath Test Suite family of products Speaker: Atul Trikha, Chief Technologist & Solutions Architect, Peraton and UiPath MVP Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP

UiPath Test Automation using UiPath Test Suite series, part 1

UiPath Test Automation using UiPath Test Suite series, part 1

UiPath Test Automation using UiPath Test Suite series, part 1

IESVE for Early Stage Design and Planning

IESVE for Early Stage Design and Planning

IESVE for Early Stage Design and Planning

New customer? New industry? New cloud? New team? A lot to handle! How to ensure the success of the project? Start it well! I've created the 3 areas of focus at the beginning of the project that helped me in multiple roles (BA, PO, and Consultant). Learn from real-world experiences and discover how these insights can empower you to deliver unparalleled value to your customers right from the project's start.

Powerful Start- the Key to Project Success, Barbara Laskowska

Powerful Start- the Key to Project Success, Barbara Laskowska

Powerful Start- the Key to Project Success, Barbara Laskowska

Welcome to UiPath Test Automation using UiPath Test Suite series part 2. In this session, we will cover API test automation along with a web automation demo. Topics covered: Test Automation introduction API Example of API automation Web automation demonstration Speaker Pathrudu Chintakayala, Associate Technical Architect @Yash and UiPath MVP Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP

UiPath Test Automation using UiPath Test Suite series, part 2

UiPath Test Automation using UiPath Test Suite series, part 2

UiPath Test Automation using UiPath Test Suite series, part 2

This presentation dives into the practical applications of machine learning within Google's operations, providing a comprehensive overview of how to leverage AI technologies to solve real-world business challenges. Key Points Covered: - Introduction to Machine Learning at Google: Discussion on the role of ML and its evolution in enhancing Google's operational efficiency. - Experience Sharing: Insights into the team's long-term engagement with machine learning projects and the impacts on Google’s operational strategies. - Practical Applications: Real-world examples of ML applications within Google’s daily operations, providing a blueprint to adapt similar strategies. - Challenges and Solutions: Discussion on the challenges faced during the implementation of ML projects and the strategic solutions employed to overcome them. - Future of ML at Google: Insights into future trends in machine learning at Google and how they plan to continue integrating AI into their ecosystem.

Strategic AI Integration in Engineering Teams

Strategic AI Integration in Engineering Teams

Strategic AI Integration in Engineering Teams

ScyllaDB has the potential to deliver impressive performance and scalability. The better you understand how it works, the more you can squeeze out of it. But before you squeeze, make sure you know what to monitor! Watch our experienced Postgres developer work through monitoring and performance strategies that help him understand what mistakes he’s made moving to NoSQL. And learn with him as our database performance expert offers friendly guidance on how to use monitoring and performance tuning to get his sample Rust application on the right track. This webinar focuses on using monitoring and performance tuning to discover and correct mistakes that commonly occur when developers move from SQL to NoSQL. For example: - Common issues getting up and running with the monitoring stack - Using the CQL optimizations dashboard - Common issues causing high latency in a node - Common issues causing replica imbalance - What a healthy system looks like in terms of memory - Key metrics to keep an eye on This isn’t “Death-by-Powerpoint.” We’ll walk through problems encountered while migrating a real application from Postgres to ScyllaDB – and try to fix them live as well.

Optimizing NoSQL Performance Through Observability

Optimizing NoSQL Performance Through Observability

Optimizing NoSQL Performance Through Observability

Explore the core of Salesforce success in 'Salesforce Adoption – Metrics, Methods, and Motivation.' We will discuss essential metrics, effective methods to drive adoption, and the driving force behind user engagement and explore strategies for onboarding, training, and continuous support that empower users to navigate the platform seamlessly. By leveraging these tools, you can effectively measure adoption against your company’s goals and create an environment where users not only adopt Salesforce but actively contribute to its ongoing success.

Salesforce Adoption – Metrics, Methods, and Motivation, Antone Kom

Salesforce Adoption – Metrics, Methods, and Motivation, Antone Kom

Salesforce Adoption – Metrics, Methods, and Motivation, Antone Kom

Unlock the mysteries of successful Salesforce interviews in this insightful session hosted by Hugo Rosario (Salesforce Customer), a seasoned hiring manager that leads the Salesforce Department of multinational company with over 100 interviews under their belt. Step into the manager's chair and gain exclusive behind-the-scenes insights into what makes a Salesforce consultant stand out during the interview process. From deciphering the unspoken cues to mastering key strategies, we'll explore the intricacies of the interview process and provide practical tips for consultants looking to not only pass interviews but also thrive in their roles. Whether you're a seasoned professional or just starting your Salesforce journey, this session is your backstage pass to the secrets that hiring managers wish you knew.

Behind the Scenes From the Manager's Chair: Decoding the Secrets of Successfu...

Behind the Scenes From the Manager's Chair: Decoding the Secrets of Successfu...

Behind the Scenes From the Manager's Chair: Decoding the Secrets of Successfu...

FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...

FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...

FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...

The Metaverse: Are We There Yet?

The Metaverse: Are We There Yet?

The Metaverse: Are We There Yet?

Mark Billinghurst

Intro in Product Management - Коротко про професію продакт менеджера

Intro in Product Management - Коротко про професію продакт менеджера

Intro in Product Management - Коротко про професію продакт менеджера

Syngulon’s technology expands the capacity for selection of microorganisms. The ability to select individual microbes with a behavior of interest is essential, whether for simple cloning at the bench, or for industry-scale production. Synthetic biology uses the concept of “bioengineering” to improve or modify existing genetic systems to create microbes with desired behaviors, and Syngulon uses this approach to develop its selection technologies. This selection technology is based on bacteriocins, ribosomally-produced peptides naturally made by most bacteria to kill competitive microbial species. These bacteriocins can have a limited or wide target range against other microbial species. This technology offers advantageous over antibiotic selection for several reasons: it avoids the use of antibiotics in the first place, helping to reduce the spread of antibiotic resistant microbes. The technology also increases product yield; as bacteriocins are generally smaller peptides, they do not impose a heavy metabolic burden on the producing cell. They can have a wide target specificity, helping to avoid genetic drift. Finally, our system is 100% plasmid-based (e.g. without chromosomal mutations), making it applicable for use in any E. coli strains.

Syngulon - Selection technology May 2024.pdf

Syngulon - Selection technology May 2024.pdf

Syngulon - Selection technology May 2024.pdf

Ever caught yourself nodding along when someone mentions "delivering value" in Agile, but secretly wondering what the heck they actually mean? You're not alone! Join us for an eye-opening session where we'll strip away the buzzwords and dive into the heart of Agile—value delivery. But what is "value"? Is it a mythical unicorn in the world of software development, or is there more to this overused term? This isn't going to be a sit-and-get lecture. We're talking about a face-to-face, interactive meetup where YOU play a crucial role. Come along to: Define It: What does "value" really mean? We’ll build a definition that’s not just words, but a compass for your Agile journey. Contextualise It: Discover what value means specifically to you, your team, your company, and your industry. Because one size does not fit all. Deliver It: Share strategies and gather new ones for uncovering and delivering true value—no more shooting in the dark!

Unpacking Value Delivery - Agile Oxford Meetup - May 2024.pptx

Unpacking Value Delivery - Agile Oxford Meetup - May 2024.pptx

Unpacking Value Delivery - Agile Oxford Meetup - May 2024.pptx

Heather Hedden, Senior Consultant at Enterprise Knowledge, presented “Enterprise Knowledge Graphs: The Importance of Semantics” on May 9, 2024, at the annual Data Summit in Boston. In her presentation, Hedden describes the components of an enterprise knowledge graph and provides further insight into the semantic layer – or knowledge model – component, which includes an ontology and controlled vocabularies, such as taxonomies, for controlled metadata. While data experts tend to focus on the graph database components (RDF triple store or a label property graph), Hedden emphasizes they should not overlook the importance of the semantic layer.

Enterprise Knowledge Graphs - Data Summit 2024

Enterprise Knowledge Graphs - Data Summit 2024

Enterprise Knowledge Graphs - Data Summit 2024

Enterprise Knowledge

We're living the AI revolution and Salesforce is adapting and bring new value to their customers. Einstein products are evolving rapidly and navigating their limitations, language support, and use cases can be challenging. Let's make review of what Einstein product are available currently, what are the capabilities and what can be used for in CEE region and how Rossie.ai can help to learn Salesforce speak Czech. We will explore the Einstein roadmap and I will make a short live demo (based on your vote) of some Einstein feature.

AI revolution and Salesforce, Jiří Karpíšek

AI revolution and Salesforce, Jiří Karpíšek

AI revolution and Salesforce, Jiří Karpíšek

When you think of a highly secure meeting environment, do you instantly think 'Microsoft Teams'!? Or do you think about some unknown application, troublesome UI and daunting login process...? If you think the latter - let's change that! In this session Femke will show you how using Teams Premium features can create secure, but also good looking meetings! PRETTY. Make sure your company's brand is represented before, during and after the meeting with Customization policies in place. SECURE. Lets utilize Meeting templates and Sensitivity Labels to protect your meeting and data to prevent sensitive information from being leaked. After this session, you will have a clear understanding of the capabilities of Teams Premium features and how to set up the perfect meeting that suits your organizational requirements!

ECS 2024 Teams Premium - Pretty Secure

ECS 2024 Teams Premium - Pretty Secure

ECS 2024 Teams Premium - Pretty Secure

Femke de Vroome

Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...

Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...

Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...

Where to Learn More About FDO _ Richard at FIDO Alliance.pdf

Where to Learn More About FDO _ Richard at FIDO Alliance.pdf

Where to Learn More About FDO _ Richard at FIDO Alliance.pdf

Screen flow is a powerful automation tool that is commonly designed for internal and external users. However, what about the guest users? We will dive into various methods of launching screen flows and understand how to make them publicly accessible, extending their usability to a broader audience. The presentation will also cover the implementation of security layers and highlight best practices for a smooth and protected user experience. Discover the potential of screen flows beyond conventional use and learn how to leverage them effectively.

Free and Effective: Making Flows Publicly Accessible, Yumi Ibrahimzade

Free and Effective: Making Flows Publicly Accessible, Yumi Ibrahimzade

Free and Effective: Making Flows Publicly Accessible, Yumi Ibrahimzade

What's New in Teams Calling, Meetings and Devices April 2024

What's New in Teams Calling, Meetings and Devices April 2024

What's New in Teams Calling, Meetings and Devices April 2024

Stephanie Beckett

Recently uploaded (20)

UiPath Test Automation using UiPath Test Suite series, part 1

UiPath Test Automation using UiPath Test Suite series, part 1

UiPath Test Automation using UiPath Test Suite series, part 1

IESVE for Early Stage Design and Planning

IESVE for Early Stage Design and Planning

IESVE for Early Stage Design and Planning

Powerful Start- the Key to Project Success, Barbara Laskowska

Powerful Start- the Key to Project Success, Barbara Laskowska

Powerful Start- the Key to Project Success, Barbara Laskowska

UiPath Test Automation using UiPath Test Suite series, part 2

UiPath Test Automation using UiPath Test Suite series, part 2

UiPath Test Automation using UiPath Test Suite series, part 2

Strategic AI Integration in Engineering Teams

Strategic AI Integration in Engineering Teams

Strategic AI Integration in Engineering Teams

Optimizing NoSQL Performance Through Observability

Optimizing NoSQL Performance Through Observability

Optimizing NoSQL Performance Through Observability

Salesforce Adoption – Metrics, Methods, and Motivation, Antone Kom

Salesforce Adoption – Metrics, Methods, and Motivation, Antone Kom

Salesforce Adoption – Metrics, Methods, and Motivation, Antone Kom

Behind the Scenes From the Manager's Chair: Decoding the Secrets of Successfu...

Behind the Scenes From the Manager's Chair: Decoding the Secrets of Successfu...

Behind the Scenes From the Manager's Chair: Decoding the Secrets of Successfu...

FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...

FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...

FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...

The Metaverse: Are We There Yet?

The Metaverse: Are We There Yet?

The Metaverse: Are We There Yet?

Intro in Product Management - Коротко про професію продакт менеджера

Intro in Product Management - Коротко про професію продакт менеджера

Intro in Product Management - Коротко про професію продакт менеджера

Syngulon - Selection technology May 2024.pdf

Syngulon - Selection technology May 2024.pdf

Syngulon - Selection technology May 2024.pdf

Unpacking Value Delivery - Agile Oxford Meetup - May 2024.pptx

Unpacking Value Delivery - Agile Oxford Meetup - May 2024.pptx

Unpacking Value Delivery - Agile Oxford Meetup - May 2024.pptx

Enterprise Knowledge Graphs - Data Summit 2024

Enterprise Knowledge Graphs - Data Summit 2024

Enterprise Knowledge Graphs - Data Summit 2024

AI revolution and Salesforce, Jiří Karpíšek

AI revolution and Salesforce, Jiří Karpíšek

AI revolution and Salesforce, Jiří Karpíšek

ECS 2024 Teams Premium - Pretty Secure

ECS 2024 Teams Premium - Pretty Secure

ECS 2024 Teams Premium - Pretty Secure

Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...

Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...

Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...

Where to Learn More About FDO _ Richard at FIDO Alliance.pdf

Where to Learn More About FDO _ Richard at FIDO Alliance.pdf

Where to Learn More About FDO _ Richard at FIDO Alliance.pdf

Free and Effective: Making Flows Publicly Accessible, Yumi Ibrahimzade

Free and Effective: Making Flows Publicly Accessible, Yumi Ibrahimzade

Free and Effective: Making Flows Publicly Accessible, Yumi Ibrahimzade

What's New in Teams Calling, Meetings and Devices April 2024

What's New in Teams Calling, Meetings and Devices April 2024

What's New in Teams Calling, Meetings and Devices April 2024

Discover what exists with Ontology2

1. How it all started Photo Credit: Daniel Sparing The slides to this talk are licensed CC-BY-SA/3.0

2. Flickr kills the dream…

3. But Creative Commons Saves the Day

4. animalphotos.info

5. dbpedia & the semantic web Subject Predicate (Verb) Object <dbpedia:Albatross> <rdf:type> <dbpedia-owl:Bird> . http://dbpedia.org/ontology/Bird http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://dbpedia.org/resource/Albatross

6. the linked data cloud “Linking Open Data cloud diagram, by Richard Cyganiak and AnjaJentzsch. http://lod-cloud.net/”

7. automating the process search for candidates Identify topics filter correct images describe images dbpedia flickr

8. amazon mechanical turk

9. carpictures.cc

10. the business model

11. how many things exist? The game of 20 questions  220 = about a million…

12. what sort of things exist? “Everything on Earth:” Places, People, Creative Works, Life Forms, Technological Artifacts

13. ny-pictures.com

14. exploring the earth’s noösphere Noösphere, according to the thought of Vladimir Vernadsky and Teilhard de Chardin, denotes the "sphere of human thought".

15. ookaboo.com takes off

16. ookaboo semantic API http://en.wikipedia.org/wiki/Thailand API Thanks: Andyindia, Echiner1, Rene Eherhardt

17. Why don’t computers understand human language? The Ink is In The Pen The Pig is In The Pen Thanks: Seaniz, GiangHồThịHoàng, Claudia Scholz and

18. the human memome project One ring to bind them all?

19. Top-down? Bottom-up? Both! Merge data from a wide range of sources, continuously test against reality by performance in practical applications

20. Ontology2: Long Term Evolution