MacRuby is a Ruby implementation for Mac OS X that allows Ruby code to directly interact with Cocoa and other OS X frameworks. It uses a single runtime and garbage collector to bind Ruby and Objective-C. MacRuby aims to provide the best platform for Ruby developers and a great platform for Cocoa developers. Benchmarks show that Fibonacci code runs faster in MacRuby compared to pure Ruby and Objective-C implementations, due to optimizations from the LLVM compiler.
This is a set of modified MacRuby presentation slides given at the Pittsburgh Ruby Brigade meeting on Nov 5, 2009. The original presentation was given by Patrick Thomson at C4[3] in September, 2009. Slides 68 and 69 were added by me for the PghRB talk.
Patrick's original slides are available at http://www.slideshare.net/importantshock/why-macruby-matters
This is a set of modified MacRuby presentation slides given at the Pittsburgh Ruby Brigade meeting on Nov 5, 2009. The original presentation was given by Patrick Thomson at C4[3] in September, 2009. Slides 68 and 69 were added by me for the PghRB talk.
Patrick's original slides are available at http://www.slideshare.net/importantshock/why-macruby-matters
To hit Ruby3x3, we must first figure out **what** we're going to measure, **how** we're going to measure it, in order to get what we actually want. I'll cover some standard definitions of benchmarking in dynamic languages, as well as the tradeoffs that must be made when benchmarking. I'll look at some of the possible benchmarks that could be considered for Ruby 3x3, and evaluate them for what they're good for measuring, and what they're less good for measuring, in order to help the Ruby community decide what the 3x goal is going to be measured against.
A three-part presentation on the Swift programming language:
• An introduction to Swift for Objective-C developers
• Changes in Swift 2
• What's coming in Swift 2.2 & 3.0
Pythran: Static compiler for high performance by Mehdi Amini PyData SV 2014PyData
Pythran is a an ahead of time compiler that turns modules written in a large subset of Python into C++ meta-programs that can be compiled into efficient native modules. It targets mainly compute intensive part of the code, hence it comes as no surprise that it focuses on scientific applications that makes extensive use of Numpy. Under the hood, Pythran inter-procedurally analyses the program and performs high level optimizations and parallel code generation. Parallelism can be found implicitly in Python intrinsics or Numpy operations, or explicitly specified by the programmer using OpenMP directives directly in the Python source code. Either way, the input code remains fully compatible with the Python interpreter. While the idea is similar to Parakeet or Numba, the approach differs significantly: the code generation is not performed at runtime but offline. Pythran generates C++11 heavily templated code that makes use of the NT2 meta-programming library and relies on any standard-compliant compiler to generate the binary code. We propose to walk through some examples and benchmarks, exposing the current state of what Pythran provides as well as the limit of the approach.
Using timed-release cryptography to mitigate the preservation risk of embargo...Michael Nelson
Slides for:
Rabia Haq, Michael L. Nelson: Using timed-release cryptography to mitigate the preservation risk of embargo periods. 2009 ACM/IEEE Joint Conference on Digital Libraries (JCDL), pp. 183-192.
Zero-Overhead Metaprogramming: Reflection and Metaobject Protocols Fast and w...Stefan Marr
Runtime metaprogramming enables many useful applications and is often a convenient solution to solve problems in a generic way, which makes it widely used in frameworks, middleware, and domain-specific languages. However, powerful metaobject protocols are rarely supported and even common concepts such as reflective method invocation or dynamic proxies are not optimized. Solutions proposed in literature either restrict the metaprogramming capabilities or require application or library developers to apply performance improving techniques.
For overhead-free runtime metaprogramming, we demonstrate that dispatch chains, a generalized form of polymorphic inline caches common to self-optimizing interpreters, are a simple optimization at the language-implementation level. Our evaluation with self-optimizing interpreters shows that unrestricted metaobject protocols can be realized for the first time without runtime overhead, and that this optimization is applicable for just-in-time compilation of interpreters based on meta-tracing as well as partial evaluation. In this context, we also demonstrate that optimizing common reflective operations can lead to significant performance improvements for existing applications.
My presentation will be on the topic of MacRuby. MacRuby is relevent to Ruby developers because it allows us to dive into the world of Mac OS X development using Ruby 1.9. Unlike RubyCocoa, where we would need to use both Ruby and Objective-C, MacRuby's API allows us to just use Ruby.
I will go into a brief history of MacRuby and explain just why it is important to us as Ruby developers. I will then do some live coding of a quick desktop application using MacRuby. Attendees will be able to take away from the presentation a good understanding of MacRuby and the passion to develop something of their own using it.
To hit Ruby3x3, we must first figure out **what** we're going to measure, **how** we're going to measure it, in order to get what we actually want. I'll cover some standard definitions of benchmarking in dynamic languages, as well as the tradeoffs that must be made when benchmarking. I'll look at some of the possible benchmarks that could be considered for Ruby 3x3, and evaluate them for what they're good for measuring, and what they're less good for measuring, in order to help the Ruby community decide what the 3x goal is going to be measured against.
A three-part presentation on the Swift programming language:
• An introduction to Swift for Objective-C developers
• Changes in Swift 2
• What's coming in Swift 2.2 & 3.0
Pythran: Static compiler for high performance by Mehdi Amini PyData SV 2014PyData
Pythran is a an ahead of time compiler that turns modules written in a large subset of Python into C++ meta-programs that can be compiled into efficient native modules. It targets mainly compute intensive part of the code, hence it comes as no surprise that it focuses on scientific applications that makes extensive use of Numpy. Under the hood, Pythran inter-procedurally analyses the program and performs high level optimizations and parallel code generation. Parallelism can be found implicitly in Python intrinsics or Numpy operations, or explicitly specified by the programmer using OpenMP directives directly in the Python source code. Either way, the input code remains fully compatible with the Python interpreter. While the idea is similar to Parakeet or Numba, the approach differs significantly: the code generation is not performed at runtime but offline. Pythran generates C++11 heavily templated code that makes use of the NT2 meta-programming library and relies on any standard-compliant compiler to generate the binary code. We propose to walk through some examples and benchmarks, exposing the current state of what Pythran provides as well as the limit of the approach.
Using timed-release cryptography to mitigate the preservation risk of embargo...Michael Nelson
Slides for:
Rabia Haq, Michael L. Nelson: Using timed-release cryptography to mitigate the preservation risk of embargo periods. 2009 ACM/IEEE Joint Conference on Digital Libraries (JCDL), pp. 183-192.
Zero-Overhead Metaprogramming: Reflection and Metaobject Protocols Fast and w...Stefan Marr
Runtime metaprogramming enables many useful applications and is often a convenient solution to solve problems in a generic way, which makes it widely used in frameworks, middleware, and domain-specific languages. However, powerful metaobject protocols are rarely supported and even common concepts such as reflective method invocation or dynamic proxies are not optimized. Solutions proposed in literature either restrict the metaprogramming capabilities or require application or library developers to apply performance improving techniques.
For overhead-free runtime metaprogramming, we demonstrate that dispatch chains, a generalized form of polymorphic inline caches common to self-optimizing interpreters, are a simple optimization at the language-implementation level. Our evaluation with self-optimizing interpreters shows that unrestricted metaobject protocols can be realized for the first time without runtime overhead, and that this optimization is applicable for just-in-time compilation of interpreters based on meta-tracing as well as partial evaluation. In this context, we also demonstrate that optimizing common reflective operations can lead to significant performance improvements for existing applications.
My presentation will be on the topic of MacRuby. MacRuby is relevent to Ruby developers because it allows us to dive into the world of Mac OS X development using Ruby 1.9. Unlike RubyCocoa, where we would need to use both Ruby and Objective-C, MacRuby's API allows us to just use Ruby.
I will go into a brief history of MacRuby and explain just why it is important to us as Ruby developers. I will then do some live coding of a quick desktop application using MacRuby. Attendees will be able to take away from the presentation a good understanding of MacRuby and the passion to develop something of their own using it.
The talk focuses on the processes and requirements to ship a software, which was written with MacRuby, to the end user. I present libraries and tools, that are helpful for this purpose and show how to use them.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
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.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
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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.
7. Mac OS X Stack
Applications
Application
Frameworks
Cocoa, WebKit, ...
Core Technologies CoreGraphics, CoreFoundation, ...
Darwin Kernel, userland, libdispatch, ...
8. Ruby on OS X
2002 Mac OS X 10.2 Ruby 1.6.7
2005 Mac OS X 10.4 Ruby 1.8.2
2007 Mac OS X 10.5 Ruby 1.8.6
RubyCocoa, gems, Rails
2009 Mac OS X 10.6 Ruby 1.8.7
RubyCocoa, gems, Rails
20xx ? Sky is the limit
9. Ruby on OS X
• Ruby, just on another unix platform
• With some small improvements...
e.g. mongrel_rails_persists on OS X Server
launchd / bonjour integration
• What about Cocoa ?
19. MacRuby
• One GC to release them all
• One runtime to bind them
• In the land of Cocoa where Obj-C lie
20. MacRuby
Laurent Sansonetti
(Apple)
Vincent Isambart
Kich Kilmer
Eloy Duran
Ben Stiglitz
Matt Aimonetti
...
http://www.macruby.org
http://twitter.com/macruby
21. Modest goals
• The best platform for Ruby developers
• A great platform for Cocoa developers
39. Grand Central
# A GCD-based implementation of the sleeping barber problem:
# http://en.wikipedia.org/wiki/Sleeping_barber_problem
# http://www.madebysofa.com/#blog/the_sleeping_barber
waiting_chairs = Dispatch::Queue.new('com.apple.waiting_chairs')
semaphore = Dispatch::Semaphore.new(3)
index = -1
while true
index += 1
success = semaphore.wait(Dispatch::TIME_NOW)
if success != 0
puts "Customer turned away #{index}"
next
end
waiting_chairs.dispatch do
semaphore.signal
puts "Shave and a haircut #{index}"
end
end
41. Why MacRuby ?
• Ruby for “mac-like” desktop applications
• A wonderful experimentation playground
• ... Interesting perspectives
42. Q&A
• Ruby 1.9 compatibility
• Right now, ≈ 80% on rubyspec
• Other platforms, portability
• No closed-source dependancies, no
definitive technical blocker
• ... Any takers ?