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On October 3 at Velocity EU, Strangeloop president Joshua Bixby unveiled the findings from the first study ever conducted of mobile performance over cellular networks. In July and September 2012, Strangeloop conducted an industry first: a mobile performance survey of top ecommerce sites. The "2012 State of Mobile Ecommerce Performance" documents how Strangeloop tested top Alexa-ranked retail sites on a variety of mobile devices to find answers to questions like: - How long does the median site take to load in mobile browsers? - Which sites were fastest? - Do some mobile OS/browsers/devices offer a consistently faster user experience than others? - How much faster are pages served over LTE than over 3G? - How do all of these findings compare to similar research conducted for desktop performance, published in Strangeloop’s annual Page Speed and Website Performance State of the Union reports? The report is available for download at http://www.strangeloopnetworks.com/.

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One approach to performance is to accelerate the network; another is to optimize the application by reducing how much the network is needed and pushing content out towards the user. In this session, Hooman Beheshti reveals how technologies like Front-End Optimization and Content Delivery Networks work alongside the rest of the cloud computing stack to improve performance and increase user productivity.

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Performance matters. And in the cloud, performance matters more than ever—layers of complexity and third-party, shared environments separate users from applications. Services are elastic, which means you can have any SLA you want, as long as you're willing to design it yourself. And you can have a fast application, too—if you're willing to deal with the bill at the end of the month. So how should you think about cloud performance? In this in-depth workshop on the performance of cloud computing, three cloud computing and Internet performance experts—Steve Riley (Riverbed, Amazon), Hooman Beheshti (Strangeloop, Radware) and Alistair Croll (Coradiant, CloudOps)—take you on a tour of the challenges on-demand computing poses to reliable, fast user experiences. What you'll learn: - The new models of delay, capacity, and uptime that on-demand computing requires - What and how to measure when it comes to performance, and how to think about metrics - Where delay happens across the cloud environment - How shared computing and back-end contention affect user experience - What the WAN and the Application Delivery Network mean in a cloudy compute model - How to spread load and optimize application front-ends to speed up applications

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Strangeloop VP Technology Hooman Beheshti demonstrates – in real time – the impact of advanced mobile optimization techniques on another unsuspecting website. Over the course of the workshop, witness the mobile optimization life cycle, from start to finish: - Taking the “Before” shot: Choosing a guinea pig site and benchmarking its current performance, focusing on load time, start render time and round trips. - Iterating through core best practices, including: Keep-Alive, Compression, Far Future Expiry, and Use a CDN. - Applying a set of advanced, automated, mobile-specific FEO techniques. - Taking the “After” shot: Analyzing results using different browsers.

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Slide deck from Strangeloop president Joshua Bixby's presentation at the 2012 Content Delivery Summit. Many content owners are already using a content delivery network (CDN) to cache content closer to their visitors, but CDNs don't reduce the number of requests required to render each page, and they have no impact on browser efficiency. Front-end optimization (FEO) picks up where CDNs leave off, transforming the content itself so that it renders as quickly as possible in the browser. In this presentation, attendees will see real-world examples of how leading e-commerce sites have combined CDN and FEO forces to reach new levels of performance for content-rich pages. Get real numbers on how quickly content-rich sites loaded pre-acceleration, then with just a CDN, then with a combined CDN/FEO solution.

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From Hooman's presentation at the Cloud Performance Summit at Cloud Connect 2012: Accelerating applications can mean different things to different people. In web applications, performance is impacted by everything from infrastructure to code to back-end processing to browser capabilities. This can get even more complicated in cloud environments. In this discussion, we'll focus on the issues surrounding the "front-end" performance of the application which includes all interactions between the browser and the app after the dynamic content (the base HTML) has been generated and delivered to the browser. We will discuss the major front-end performance pain points and some strategies for mitigating them (including hidden complications and gotchas), ultimately leading to a better perceived user experience.

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You know that performance is crucial to your company's success, but do the people in the corner office know this? You need to get the message across using the language they speak and targeting the goals they care about. This session -- presented by Strangeloop president Joshua Bixby at the 2011 Web Performance Summit -- summarizes the benefits of a faster website or web app, then delves into a series of how-tos for creating a business case for web performance in your organization.

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Last year at Velocity, Strangeloop's VP Product, Hooman Beheshti, presented the findings from phase one of Strangeloop’s long-term research into the relationship between web performance and business benefits. The results were also published in Watching Websites. Since then, we’ve received a barrage of questions from the web performance community, which fueled phase two of our study. In this presentation, Strangeloop president Joshua Bixby offers our most recent findings. Some of the community’s questions were: * Who were the clients? * How fast were the pages? * What acceleration techniques were implemented? * What happened to the key page components (such as JS size, payload and roundtrips) of the websites? * How did changing key variables (page load time, payload, number of roundtrips, etc.) affect the outcome? We’ve been collecting and analyzing data to help us answer these questions, as well as some new ones we’ve thought up along the way. Join us as we present our findings, and help us consider what areas deserve further study.

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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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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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