Скачать с ютуб Enabling Distributed Applications with Online Machine Learning в хорошем качестве

Enabling Distributed Applications with Online Machine Learning

With the recent proliferation of the Internet of Things (IoT), more and more devices now have computing capabilities and Internet connections. While these newfound capabilities have enabled a multitude of emerging applications, e.g., large-scale machine learning that takes as input data collected by many IoT sensors, they also raise new challenges for ensuring that such applications receive the data, computing, and communication resources that they need. Some data analytics tasks, for example, may require significantly more processing capabilities than others, and these capabilities may not always be available depending on the status of devices in the network. Optimizing such resource allocations across heterogeneous applications is in general NP-hard and becomes even more challenging in a dynamic and uncertain environment in which user demands and resource availability may change in unknown ways over time. In this talk, I will present our recent work using online and reinforcement learning techniques to provision both computing and communication resources for heterogeneous applications. By incorporating prior knowledge of the problem structure and application requirements, we can significantly accelerate our ability to learn how to allocate resources without requiring prior models of the environment. Our experiments on distributed machine learning and autonomous vehicle applications indicate that we can improve application performance and utilize fewer resources compared to static and naive learning-based baselines. Speakers: Carlee Joe-Wong Associate Professor Carnegie Mellon University Moderators: Jiaying Meng Junior Programme Officer International Telecommunication Union (ITU) Vishnu Ram OV Independent Research Consultant Consultant The AI for Good Global Summit is the leading action-oriented United Nations platform promoting AI to advance health, climate, gender, inclusive prosperity, sustainable infrastructure, and other global development priorities. AI for Good is organized by the International Telecommunication Union (ITU) – the UN specialized agency for information and communication technology – in partnership with 40 UN sister agencies and co-convened with the government of Switzerland. Join the Neural Network! 👉https://aiforgood.itu.int/neural-netw... The AI for Good networking community platform powered by AI. Designed to help users build connections with innovators and experts, link innovative ideas with social impact opportunities, and bring the community together to advance the SDGs using AI. 🔴 Watch the latest #AIforGood videos!    / aiforgood   📩 Stay updated and join our weekly AI for Good newsletter: http://eepurl.com/gI2kJ5 🗞Check out the latest AI for Good news: https://aiforgood.itu.int/newsroom/ 📱Explore the AI for Good blog: https://aiforgood.itu.int/ai-for-good... 🌎 Connect on our social media: Website: https://aiforgood.itu.int/ Twitter:   / aiforgood   LinkedIn Page:   / 26511907   LinkedIn Group:   / 8567748   Instagram:   / aiforgood   Facebook:   / aiforgood   Disclaimer: The views and opinions expressed are those of the panelists and do not reflect the official policy of the ITU.