Jabox presentation

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Jabox Open Source A.L.M. Build Your Own Entreprise Java Development Ecosystem Dimitris Kapanidis [email_address]

Jabox Open Source ALM platform ,[object Object]

An out-of-the-box solution: ,[object Object]

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Code Quality Management ,[object Object]

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State of the Jenkins Automation

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Arquillian is an innovative and highly extensible testing platform for the JVM that enables developers to easily create automated integration, functional and acceptance tests for Java middleware, from Java EE and beyond. For years we’ve been exploring how to layer and separate our code to test in isolation on the unit level. We’ve kept integration and functional testing as a big ball of mud; jumping straight from unit to full system testing. But can we apply some of the same lessons learned from unit to integration testing? Speaker Bio: Arquillian project lead, Aslak Knutsen, is a Senior Software Engineer at Red Hat where he is working on projects such as Arquillian and ShrinkWrap, one of the founders of the JBoss Testing initiative and a speaker at major industry conferences including JavaOne, Devoxx, Jazoon, JFokus, Geecon, JUDCon and JBoss World.

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Jenkins is a Continuous Integration tool to manage your environment that fires off jobs like cron or when a button is pushed. This talk will walk you through setting up a Jenkins site, complete with slave nodes on the servers doing the real work, and some simple jobs to get a feel for what it can do for you. Real life examples included based on an actual migration between data centers requiring Jenkins had to be installed fresh. This talk has been presented at: 2016-08-20 in Philadelphia - https://fosscon.us/ 2016-08-26 in Cluj-Napoca, Romania - http://act.yapc.eu/ye2016/talk/6751 - https://youtu.be/Nj84bBCssps

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The presentation explores the development and application of artificial intelligence (AI) from its inception to its current status in the modern world. The term "artificial intelligence" was first coined by John McCarthy in 1956 to describe efforts to develop computer programs capable of performing tasks that typically require human intelligence. This concept was first introduced at a conference held at Dartmouth College, where programs demonstrated capabilities such as playing chess, proving theorems, and interpreting texts. In the early stages, Alan Turing contributed to the field by defining intelligence as the ability of a being to respond to certain questions intelligently, proposing what is now known as the Turing Test to evaluate the presence of intelligent behavior in machines. As the decades progressed, AI evolved significantly. The 1980s focused on machine learning, teaching computers to learn from data, leading to the development of models that could improve their performance based on their experiences. The 1990s and 2000s saw further advances in algorithms and computational power, which allowed for more sophisticated data analysis techniques, including data mining. By the 2010s, the proliferation of big data and the refinement of deep learning techniques enabled AI to become mainstream. Notable milestones included the success of Google's AlphaGo and advancements in autonomous vehicles by companies like Tesla and Waymo. A major theme of the presentation is the application of generative AI, which has been used for tasks such as natural language text generation, translation, and question answering. Generative AI uses large datasets to train models that can then produce new, coherent pieces of text or other media. The presentation also discusses the ethical implications and the need for regulation in AI, highlighting issues such as privacy, bias, and the potential for misuse. These concerns have prompted calls for comprehensive regulations to ensure the safe and equitable use of AI technologies. Artificial intelligence has also played a significant role in healthcare, particularly highlighted during the COVID-19 pandemic, where it was used in drug discovery, vaccine development, and analyzing the spread of the virus. The capabilities of AI in healthcare are vast, ranging from medical diagnostics to personalized medicine, demonstrating the technology's potential to revolutionize fields beyond just technical or consumer applications. In conclusion, AI continues to be a rapidly evolving field with significant implications for various aspects of society. The development from theoretical concepts to real-world applications illustrates both the potential benefits and the challenges that come with integrating advanced technologies into everyday life. The ongoing discussion about AI ethics and regulation underscores the importance of managing these technologies responsibly to maximize their their benefits while minimizing potential harms.

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Abhishek Deb(1), Mr Abdul Kalam(2) M. Des (UX) , School of Design, DIT University , Dehradun. This paper explores the future potential of AI-enabled smartphone processors, aiming to investigate the advancements, capabilities, and implications of integrating artificial intelligence (AI) into smartphone technology. The research study goals consist of evaluating the development of AI in mobile phone processors, analyzing the existing state as well as abilities of AI-enabled cpus determining future patterns as well as chances together with reviewing obstacles as well as factors to consider for more growth.

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Building Digital Trust in a Digital Economy Veronica Tan, Director - Cyber Security Agency of Singapore Apidays Singapore 2024: Connecting Customers, Business and Technology (April 17 & 18, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/

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