Presentation slides for our first OpenCog Developer Workshop. To stay tuned with updates about our SingularityNET Developer Program, subscribe to the newsletter via singularitynet.io.
An overview of the inner-workings of OpenJDK - with emphasis on...
- what triggers the just-in-time compiler (JIT)
- types of speculative optimizations performed by the JIT
- aspects of the Java language & ecosystem that make ahead-of-time (AOT) compilation challenging
Twitter Author Prediction from Tweets using Bayesian NetworkHendy Irawan
Can We Predict the Author from a Tweet?
Most authors have a distinct writing style
... And unique topics to talk about
... And signature distribution of words used to tweet
Can we train Bayesian Network so that occurrence of words in a tweet can be used to infer the author of that tweet?
In summary: YES!
Disclaimer: Accuracy varies
In a test suite with @dakwatuna vs @farhatabbaslaw (very different tweet topics) – 100% prediction accuracy is achieved
This talk is a look into some of the surprising performance cases in Java -- with the goal of illustrating a few simple truths about the nature of compilers.
An overview of the inner-workings of OpenJDK - with emphasis on...
- what triggers the just-in-time compiler (JIT)
- types of speculative optimizations performed by the JIT
- aspects of the Java language & ecosystem that make ahead-of-time (AOT) compilation challenging
Twitter Author Prediction from Tweets using Bayesian NetworkHendy Irawan
Can We Predict the Author from a Tweet?
Most authors have a distinct writing style
... And unique topics to talk about
... And signature distribution of words used to tweet
Can we train Bayesian Network so that occurrence of words in a tweet can be used to infer the author of that tweet?
In summary: YES!
Disclaimer: Accuracy varies
In a test suite with @dakwatuna vs @farhatabbaslaw (very different tweet topics) – 100% prediction accuracy is achieved
This talk is a look into some of the surprising performance cases in Java -- with the goal of illustrating a few simple truths about the nature of compilers.
JVM Mechanics: Understanding the JIT's TricksDoug Hawkins
In this talk, we'll walkthrough how the JIT optimizes a piece Java code step-by-step. In doing so, you'll learn some of the amazing feats of optimization that JVMs can perform, but also some surprisingly simple things that prevent your code from running fast.
OracleCode One 2018: Java 5, 6, 7, 8, 9, 10, 11: What Did You Miss?Henri Tremblay
Those are the slides for my presentation at OracleCode One 2018.
Java is moving faster and faster. A lot of features are not as known as they should be.
Let's review together the ones I think you've missed in old versions.
Then I will kickstart you on 9, 10 and 11 features that you never had time to look at.
Our disks and networks can load gigabytes of data per second; we feel strongly that our software should follow suit. Thus we wrote what might be the fastest JSON parser in the world, simdjson. It can parse typical JSON files at speeds of over 2 GB/s on single commodity Intel core with full validation; it is several times faster than conventional parsers.
How did we go so fast? We started with the insight that we should make full use of the SIMD instructions available on commodity processors. These instructions are everywhere, from the ARM chip in your smartphone all to way to server processors. SIMD instructions work on wide registers (e.g., spanning 32 bytes): they are faster because they process more data using fewer instructions. To our knowledge, nobody had ever attempted to produce a full parser for something as complex as JSON by relying primarily on SIMD instructions. And many people were skeptical that a full parser could be done fruitfully with SIMD instructions. We had to develop interesting new strategies that are generally applicable. In the end, we learned several lessons. Maybe one of the most important lesson is the importance of a nearly obsessive focus on performance metrics. We constantly measure the impact of the choices we make.
Azul Virtual Machine Engineer Douglas Hawkins describes how decisions made by the JVM affect how your code is compiled and run. Learn how this affects application performance and what steps you can take to optimize how the JVM acts on your code.
Wolltest du schon immer die Vorteile und Ideen von Scala in deinen Java oder Kotlin Projekten nutzen? Dann ist Vavr (ehemals Javaslang) genau die richtige Bibliothek für dich.
Anhand echter Projektbeispiele schauen wir uns den Nutzen an, den Vavr mit seinen syntaktischen Erweiterungen und Features bei der täglichen Arbeit bietet. Wir schauen uns Value Types, echte funktionale Datentypen an und werden lernen, wie wir Exceptions sinnvoller behandeln können. Alles für besser wartbaren und sauberen Code!
Vavr bietet die Möglichkeit, die Vorteile objekt-funktionaler Programmierung zu nutzen, ohne Java den Rücken kehren zu müssen.
From Zero to Application Delivery with NixOSSusan Potter
Managing configurations for different kinds of nodes and cloud resources in a microservice architecture can be an operational nightmare, especially if not managed with the application codebase. CI and CD job environments often tend to stray from production configuration yielding their results unpredictable at best, or producing false positives in the worst case. Code pushes to staging and production can have unintended consequences which often can’t be inspected fully on a dry run.
This session will show you a toolchain and immutable infrastructure principles that will allow you to define your infrastructure in code versioned alongside your application code that will give you repeatable configuration, ephemeral testing environments, consistent CI/CD environments, and diffable dependency transparency all before pushing changes to production.
Poche chiacchiere e tanto codice per cercare rendere la nostra vita di
sviluppatori più divertente.
Parleremo di JAX-RS, le annotazioni, l'MVC che mette a disposizione e
l'integrazione di Jersey con Guice.
Useremo AOP per gestire log, transazioni e con l'aiuto di Infinispan
limiteremo le chamate concorrenti sul nostro cluster.
1. Basic Java class
class Ex1
{
public static void main(String args[])
{
int width;
int length;
int height;
width=5;
length=12;
height=3;
int v;
v=width*length*height;
System.out.println("Volume is :"+v);
}
}
Volume is :180
Introduces the use of JSON-Like data structures within DivConq. Includes how to create and access the structures within Java, as well as how to declare structures in dcSchema for data validation.
JVM Mechanics: Understanding the JIT's TricksDoug Hawkins
In this talk, we'll walkthrough how the JIT optimizes a piece Java code step-by-step. In doing so, you'll learn some of the amazing feats of optimization that JVMs can perform, but also some surprisingly simple things that prevent your code from running fast.
OracleCode One 2018: Java 5, 6, 7, 8, 9, 10, 11: What Did You Miss?Henri Tremblay
Those are the slides for my presentation at OracleCode One 2018.
Java is moving faster and faster. A lot of features are not as known as they should be.
Let's review together the ones I think you've missed in old versions.
Then I will kickstart you on 9, 10 and 11 features that you never had time to look at.
Our disks and networks can load gigabytes of data per second; we feel strongly that our software should follow suit. Thus we wrote what might be the fastest JSON parser in the world, simdjson. It can parse typical JSON files at speeds of over 2 GB/s on single commodity Intel core with full validation; it is several times faster than conventional parsers.
How did we go so fast? We started with the insight that we should make full use of the SIMD instructions available on commodity processors. These instructions are everywhere, from the ARM chip in your smartphone all to way to server processors. SIMD instructions work on wide registers (e.g., spanning 32 bytes): they are faster because they process more data using fewer instructions. To our knowledge, nobody had ever attempted to produce a full parser for something as complex as JSON by relying primarily on SIMD instructions. And many people were skeptical that a full parser could be done fruitfully with SIMD instructions. We had to develop interesting new strategies that are generally applicable. In the end, we learned several lessons. Maybe one of the most important lesson is the importance of a nearly obsessive focus on performance metrics. We constantly measure the impact of the choices we make.
Azul Virtual Machine Engineer Douglas Hawkins describes how decisions made by the JVM affect how your code is compiled and run. Learn how this affects application performance and what steps you can take to optimize how the JVM acts on your code.
Wolltest du schon immer die Vorteile und Ideen von Scala in deinen Java oder Kotlin Projekten nutzen? Dann ist Vavr (ehemals Javaslang) genau die richtige Bibliothek für dich.
Anhand echter Projektbeispiele schauen wir uns den Nutzen an, den Vavr mit seinen syntaktischen Erweiterungen und Features bei der täglichen Arbeit bietet. Wir schauen uns Value Types, echte funktionale Datentypen an und werden lernen, wie wir Exceptions sinnvoller behandeln können. Alles für besser wartbaren und sauberen Code!
Vavr bietet die Möglichkeit, die Vorteile objekt-funktionaler Programmierung zu nutzen, ohne Java den Rücken kehren zu müssen.
From Zero to Application Delivery with NixOSSusan Potter
Managing configurations for different kinds of nodes and cloud resources in a microservice architecture can be an operational nightmare, especially if not managed with the application codebase. CI and CD job environments often tend to stray from production configuration yielding their results unpredictable at best, or producing false positives in the worst case. Code pushes to staging and production can have unintended consequences which often can’t be inspected fully on a dry run.
This session will show you a toolchain and immutable infrastructure principles that will allow you to define your infrastructure in code versioned alongside your application code that will give you repeatable configuration, ephemeral testing environments, consistent CI/CD environments, and diffable dependency transparency all before pushing changes to production.
Poche chiacchiere e tanto codice per cercare rendere la nostra vita di
sviluppatori più divertente.
Parleremo di JAX-RS, le annotazioni, l'MVC che mette a disposizione e
l'integrazione di Jersey con Guice.
Useremo AOP per gestire log, transazioni e con l'aiuto di Infinispan
limiteremo le chamate concorrenti sul nostro cluster.
1. Basic Java class
class Ex1
{
public static void main(String args[])
{
int width;
int length;
int height;
width=5;
length=12;
height=3;
int v;
v=width*length*height;
System.out.println("Volume is :"+v);
}
}
Volume is :180
Introduces the use of JSON-Like data structures within DivConq. Includes how to create and access the structures within Java, as well as how to declare structures in dcSchema for data validation.
source{d} is building the open-source components to enable large-scale code analysis and machine learning on source code. Their powerful tools can ingest all of the world’s public git repositories turning code into ASTs ready for machine learning and other analyses, all exposed through a flexible and friendly API. Francesc will show you how to run machine learning on source code with a series of live demos.
Utah Code Camp, Spring 2016. http://utahcodecamp.com In this presentation I describe modern C++. Modern C++ assumes features introduced in the C++11/14 standard. An overview of the new features is presented and some idioms for mdoern C++ based on those features are presented.
A long time ago in a galaxy far, far away...
Java open source developers managed to the see the previously secret plans to the Empire's ultimate weapon, the JAVA™ COLLECTIONS FRAMEWORK.
Evading the dreaded Imperial Starfleet, a group of freedom fighters investigate the performance of the Empire’s most popular weapons: LinkedList, ArrayList and HashMap. In addition, they investigate common developer errors and bugs to help protect their vital software. With this new found knowledge they strike back!
Pursued by the Empire's sinister agents, JDuchess races home aboard her JVM, investigating proposed future changes to the Java Collections and other options such as Immutable Collections which could save her people and restore freedom to the galaxy....
Natural Language Processing with CNTK and Apache Spark with Ali ZaidiDatabricks
Apache Spark provides an elegant API for developing machine learning pipelines that can be deployed seamlessly in production. However, one of the most intriguing and performant family of algorithms – deep learning – remains difficult for many groups to deploy in production, both because of the need for tremendous compute resources and also because of the inherent difficulty in tuning and configuring.
In this session, you’ll discover how to deploy the Microsoft Cognitive Toolkit (CNTK) inside of Spark clusters on the Azure cloud platform. Learn about the key considerations for administering GPU-enabled Spark clusters, configuring such workloads for maximum performance, and techniques for distributed hyperparameter optimization. You’ll also see a real-world example of training distributed deep learning learning algorithms for speech recognition and natural language processing.Microsoft Cognitive Toolkit (CNTK) inside of Spark clusters on the Azure cloud platform. We’ll discuss the key considerations for administering GPU-enabled Spark clusters, configuring such workloads for maximum performance, and techniques for distributed hyperparameter optimization. We’ll illustrate a real-world example of training distributed deep learning learning algorithms for speech recognition and natural language processing.
BarcelonaJUG2016: walkmod: how to run and design code transformationswalkmod
walkmod is an open source tool to apply and share code conventions. Code conventions are internally designed as code transformations. In this sessions we will se how to run walkmod in a real project and how to contribute designing automatic quick fixes for existing PMD, Checkstyle or Sonar rules
Measuring maintainability; software metrics explainedDennis de Greef
In a world of ever-changing business requirements, how can you keep your software moving at the same pace?
If you keep adding lines of code around the previous iteration to add new functionality, things can become complex quite fast.
By measuring complexity, you can resolve and prevent bugs, while measuring class responsibility can make refactoring easier, for example.
In this talk Dennis will go through certain concepts of analysing software with automated tools to spit out numbers which tell a story about your code.
안드로이드 앱의 빌드 툴인 Gradle은 빌드 스크립트로 Groovy DSL을 사용합니다. DSL은 큰 학습 없이 사용할 수 있다는 장점이 있지만, 각 구문의 역할이나 의미를 정확히 알기는 어렵습니다. 이에 대한 기본적인 이해가 생긴다면, 직접 코드를 추가하거나 기존 기능을 개선시키는 등 적극적으로 빌드 과정을 조절하는데 도움이 될 것입니다. 이 세션에서는 Groovy 문법을 간단하게 소개하고, Gradle 파일들을 구문별로 의미하는 바를 짚어보며 gradle 파일을 읽는 법을 알아봅니다. 그리고 원하는 기능을 찾기 위해서 어떤 레퍼런스를 찾아야 하는지에 대한 팁을 공유합니다.
Ruby plays to many programming paradigms. It's an object-oriented language that can be used in a functional or an imperative/procedural way. But Ruby does not often get used as a logic programming language. In this talk I'll explore logic programming using Ruby. What is it, and is it a tool you want to add to your toolbox? We'll touch on several libraries, we'll primary look at an implementation of minikanren (http://minikanren.org/) for Ruby.
Echtzeitapplikationen mit Elixir und GraphQLMoritz Flucht
Wir stellen unsere Erfahrung vor, die wir in 15 Monaten Einsatz von Elixir und GraphQL in Produktion nach Relaunch eines großen
Jobanzeigenportals gesammelt haben.
Elixir bietet uns die Möglichkeit, ein hoch verfügbares Backend mit extrem geringen Antwortzeiten zu entwickeln. Dieses wird über eine GraphQL Schnittstelle von mehreren Frontends genutzt.
Elixir ist eine junge, funktionale Programmiersprache, die 2011 vorgestellt wurde. Jedoch setzt sie auf dem Erlang Ökosystem auf, welches in über 32 Jahren eine extrem stabile Basis zur Entwicklung von Anwendungen geworden ist.
Ein häufiger Anwendungsfall von Elixir sind Echtzeitapplikationen, zum Beispiel Chatanwendungen, Bots und IoT-Anwendungen. In Verbindung mit GraphQL Subscriptions ist es einfach möglich, Clients über Statusaktualisierungen vom Server zu Informieren. Wir zeigen, wofür man Elixir einsetzen kann, wie GraphQL einen leichten Einstieg in Datenexploration anbietet und wieso beide zusammen eine Überlegung wert sind.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
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.
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.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
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.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
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.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
5. 5
Use cases
• Chatbots
• Bioinformatics
• Unsupervised language learning
• Visual Question Answering VQA
• …
6. 6
Atomspace - graph database
Hypergraph database designed to be primarily used as a
storage of explicit, declarative knowledge
Hypergraph defines programming language - Atomese
Has a number of associated mechanisms:
pattern matching, unified rule engine, moses
11. 11
Loading and storing
Load scheme file from scheme or python:
>> scheme_eval(atomspace, '(load-from-path “atomspace.scm")')
Indexed by atom type and name
Use PostgreSQL as backend storage
26. 26
Unified Rule Engine
Inference engine based on graph rewriting rules.
Allows to perform declarative inference.
Rules and data defined in the same language - atomese
Can do backward and forward chaining
36. 36
Deduction rule example
premise
A -> B
B -> C
Ergo: A -> C
condition = AndLink(BA, CB)
BA = InheritanceLink(var_b, var_a)
CB = InheritanceLink(var_c, var_b)
rewrite = ExecutionOutputLink(
GroundedSchemaNode("scm: deduction-formula"),
ListLink(CA, CB, BA))
deduction_link = BindLink(condition, rewrite)
47. 47
Building VQA with OpenCog
Building blocks:
Atomspace for storing facts about world
Link-Grammar + RelEx for text processing
Faster-RCNN for bounding box and feature extraction
Our neural network models for classification
Unified rule engine and pattern matcher for computing answers
48. 48
VQA pipeline overview
How many animals are there?
PatternMatcherVQA
(python)
atomspace
Relex + link-grammar
(java)
Pattern matcher
51. 51
Taking a look at link-grammar
linkparser> How many zebras are there?
Found 22 linkages (6 had no P.P. violations)
Linkage 1, cost vector = (UNUSED=0 DIS=
2.00 LEN=8)
+------------------Xp-----------------+
+----------->WV---------->+ |
+->Ws--+--H-+--Dmc-+--Spx-+--Pp--+ |
| | | | | | |
LEFT-WALL how many zebras.n are.v there.r ?
(S how many zebras.n
(VP are.v
(PP there.r))
?)
52. 52
How link-grammar works?
Link-grammar has predefined dictionary or words associated with allowed link types.
(word: link types) pairs define what type of links can be attached to which word and
from which side.
Also number of global rules for example that links cannot cross each other.
Check the rules:
github.com/opencog/link-grammar/blob/master/data/en/4.0.dict
53. 53
RelEx
Dependency parser that built on graph rewriting rules
Operates on graph built from link-grammar parse
Adds new semantic links between words
Relex parse for “How many zebras are there?”:
_predadj(zebra, there)
_quantity(zebra, _$qVar)
59. 59
Use of URE and pattern matcher for queries
•URE allows to use declarative approach for computing answers
•We use fuzzy logic rules to compute truth value of queries
61. 61
Integrating opencog with neural networks
Stay tuned!
Passing arbitrary python objects between ExecutionOutputLinks
Allows to express computation graph as pytorch expression
Allows to integrate and update ontologies