RubyならMacでしょう
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Vincent Isambart introduced MacRuby, a Ruby implementation for Mac OS X. MacRuby aims to provide the best Ruby experience for desktop development on Mac. It is based on Ruby 1.9 to leverage improvements and be the future of Ruby. MacRuby 0.5 focused on solving problems of the previous 0.4 version like speed and threading by creating a new virtual machine. However, 0.5 still has weaknesses around memory allocation speed and only working on 64-bit systems. The community is encouraged to help with testing, tutorials, and pure Ruby libraries.
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Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Generative AI Deep Dive: Advancing from Proof of Concept to Production
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.
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Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...
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.
Full-RAG: A modern architecture for hyper-personalization
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Mind map of terminologies used in context of Generative AI
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Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
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Microsoft - Power Platform_G.Aspiotis.pdf
Revolutionizing Application Development
with AI-powered low-code, presentation by George Aspiotis, Sr. Partner Development Manager, Microsoft
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AI
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentationszkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex Proofs
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
ここ3000字までしか入らないけどタイトルの方がたくさん文字入ると思います。
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みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
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RubyならMacでしょう
- 1. Ruby Mac Ruby, on your Mac of course Vincent Isambart
- 2. Ruby Mac Ruby, on your Mac of course / Self-introduction MacRuby / MacRuby’s story MacRuby / In development Q&A
- 3. Self-introduction Vincent Isambart (IRC: scritch) @vincentisambart 2003: Ruby / Discovered Ruby 2006: RHG / RHG translation 2008-2009: MacRuby
- 4. Mac Ruby Ruby on Mac % ruby -v ruby 1.8.6 (2008-08-11 patchlevel 287)
- 5. RubyCocoa
- 6. RubyCocoa RubyCocoa’s problems Threading Method names Speed Type conversion
- 7. 2008: MacRuby MacRuby starts (Mac) Ruby Goal: Best Ruby implementation for the (Mac) desktop
- 8. Ruby 1.9 Why based on Ruby 1.9? 1.9 1.9 was unstable 1.9 Some features Few people knew 1.9 were not finished
- 9. Ruby 1.9 Why based on Ruby 1.9? Starting from scratch is too much work 1.9 Ruby 1.9 1.8 1.9 is Ruby’s future 1.9 is better than 1.8 Open-source
- 10. 1.9 MacRuby 0.4 Diff between 1.9 and MR 0.4 Ruby GC Obj-C GC Ruby object Obj-C object Ruby core class Obj-C core class
- 11. ( ) What did not change (much) / Parser YARV Ruby Ruby standard library
- 12. Cocoa more Ruby-like HotCocoa
- 13. MacRuby 0.4 MacRuby 0.4’s problems Incompatibilities Threading with 1.9 Merging 1.9 Speed
- 14. 12 : 0.5 Dec 2009: 0.5 dev started 0.4 Goal: Solving all 0.4’s problems
- 15. How? VM By creating a new VM rm vm*.c # bye bye YARV
- 16. Speed and threads Calculations are super-fast You can use multiple cores
- 17. Testing test-vm.rb RubySpec
- 18. AOT compiling Fast start time Hide the code
- 19. C Stop creating C libraries ruby-ffi
- 20. MacRuby 0.5 MacRuby 0.5’s weak points Memory allocation is slow Not very portable 32 Does not work in 32 bits Hard to compile C JIT C extensions don’t work JIT takes time Rake does not work properly
- 21. MacRuby 0.5 MacRuby 0.5’s weak points In development
- 22. MacRuby 0.5 MacRuby 0.5’s weak points Memory allocation is slow Not very portable 32 Does not work in 32 bits Hard to compile C JIT C extensions don’t work JIT takes time Rake does not work properly
- 23. Cocoa Creating a Cocoa application : RubyCocoa : MacRuby 0.4 : MacRuby 0.5
- 24. If you want to help 1.9 / Learn 1.9 RubySpec / Help RubySpec Ruby / Make pure Ruby libs / Make tutorials
- 25. Q&A http://www.macruby.org twitter: @macruby IRC: #ruby-osx (freenode)
- 26. FAQ iPhone... CPU The CPU is different Investigating JIT Can’t use the JIT ObjC GC Can’t use the ObjC GC