A Guide to Edge Computing Technology For Business OperationsCerebrum Infotech
Edge computing services enable us to generate more data at a faster rate and distribute it to a range of networks and devices located at or near the consumer. For further details, see our website.
The Future of Cloud Computing Latest Trends and Innovations.pptxMicrosoft azure
In this article, we'll look at some of the developing trends and developments that are predicted to shape the future of Cloud Computing Training in Noida
The Future of Cloud Computing Latest Trends and Innovations.pptxMicrosoft azure
Cloud Computing can be defined as a transformative technological framework that has revolutionized the way data is stored, accessed, and processed. It has rapidly brought about a change in the areas of technology and business operation over the past decades. This virtual paradigm provides scalable resources, improved efficiency as well as better flexibility. As we move ahead into its future, fascinating innovations and trends tend to reshape industries, fuel the digital revolution, and discover new arenas of possibilities.
Internet of Things (IoT) represents a remarkable transformation of the way in which our world will soon interact. Much like the World Wide Web connected computers to networks, and the next evolution connected people to the Internet and other people, IoT looks poised to interconnect devices, people, environments, virtual objects and machines in ways that only science fiction writers could have imagined.
The Internet of Things (IoT) is one of the hottest mega-trends in technology – and for good reason , IoT deals with all the components of what we consider web 3.0 including Big Data Analytics, Cloud Computing and Mobile Computing .
Fog computing or fog networking, also known as fogging, is an architecture that uses edge devices to carry out a substantial amount of computation, storage, and communication locally and routed over the internet backbone.
Making Actionable Decisions at the Network's EdgeCognizant
With the vast analytical power unleashed by the Internet of Things (IoT) ecosystem, IT organizations must be able to apply both cloud analytics and edge analytics - cloud for strategic decision-making and edge for more instantaneous response based on local sensors and other technology.
What Is Edge Computing? Everything You Need to KnowDigital Carbon
Edge computing is transforming the way we process and utilize data in the era of 5G. This groundbreaking technology is redefining the rules for businesses by bringing computing resources closer to the data source, reducing latency, and enabling real-time decision-making.
A Guide to Edge Computing Technology For Business OperationsCerebrum Infotech
Edge computing services enable us to generate more data at a faster rate and distribute it to a range of networks and devices located at or near the consumer. For further details, see our website.
The Future of Cloud Computing Latest Trends and Innovations.pptxMicrosoft azure
In this article, we'll look at some of the developing trends and developments that are predicted to shape the future of Cloud Computing Training in Noida
The Future of Cloud Computing Latest Trends and Innovations.pptxMicrosoft azure
Cloud Computing can be defined as a transformative technological framework that has revolutionized the way data is stored, accessed, and processed. It has rapidly brought about a change in the areas of technology and business operation over the past decades. This virtual paradigm provides scalable resources, improved efficiency as well as better flexibility. As we move ahead into its future, fascinating innovations and trends tend to reshape industries, fuel the digital revolution, and discover new arenas of possibilities.
Internet of Things (IoT) represents a remarkable transformation of the way in which our world will soon interact. Much like the World Wide Web connected computers to networks, and the next evolution connected people to the Internet and other people, IoT looks poised to interconnect devices, people, environments, virtual objects and machines in ways that only science fiction writers could have imagined.
The Internet of Things (IoT) is one of the hottest mega-trends in technology – and for good reason , IoT deals with all the components of what we consider web 3.0 including Big Data Analytics, Cloud Computing and Mobile Computing .
Fog computing or fog networking, also known as fogging, is an architecture that uses edge devices to carry out a substantial amount of computation, storage, and communication locally and routed over the internet backbone.
Making Actionable Decisions at the Network's EdgeCognizant
With the vast analytical power unleashed by the Internet of Things (IoT) ecosystem, IT organizations must be able to apply both cloud analytics and edge analytics - cloud for strategic decision-making and edge for more instantaneous response based on local sensors and other technology.
What Is Edge Computing? Everything You Need to KnowDigital Carbon
Edge computing is transforming the way we process and utilize data in the era of 5G. This groundbreaking technology is redefining the rules for businesses by bringing computing resources closer to the data source, reducing latency, and enabling real-time decision-making.
Everything You Need to Know About Edge Computing TechnologiesCerebrum Infotech
Edge computing services deliver data more quickly to various networks and bias at or close to the user's location. The storing of data, however, is done through cloud computing. On our website, more details are available.
A Comprehensive Exploration of Fog Computing.pdfEnterprise Wired
This article delves into the intricacies of Fog computing, exploring its definition, key components, benefits, and its transformative impact on various industries.
Edge computing is redefining the cloud computing space. The growing de-emphasis on the cloud’s role in connected environments is expected to lead to smarter and faster autonomous solutions that have the potential to reshape the IoT landscape. Edge computing will transform the IoT landscape into a hyperconnected environment where the restrictions related to latency and computation capacity will be eliminated. Many companies are transforming their business models to attain edge computing capabilities necessary for offering end to end services.
The recent years have witnessed a number of mergers and acquisitions in the edge computing space for IoT services, with the increase in M&A activities representing the industry’s conundrum of cloud, edge, and hybrid architectures, and the race to achieve a considerable market share.
This report includes an analysis of approximately 60 deals, along with a detailed technology overview and the purpose of the acquisitions. The M&A analysis section offers a comprehensive view of the transactions around edge computing, covering different technology aspects including data center, AI, security, software-defined WAN (SD-WAN), analytics, interoperability, multi-access edge computing (MEC), and others.
To purchase the full report, write to us at info@netscribes.com
Edge computing, trends and drivers to enable critical use cases for the digital economy. Types of edge and scale factors are mentioned in this article.
The Future of Fog Computing and IoT: Revolutionizing Data ProcessingFredReynolds2
Sending a business e-mail, watching a YouTube video, making an online video call meeting, or playing a video game online requires considerable data flow. It necessitates such massive data flow in the direction of servers in data centers. Cloud computing prefers remote data processing and substantial storage systems to develop online apps we use daily. But we must know that other decentralized cloud computing systems exist. Fog computing technology is growing wildly in popularity. As per fog technology experts, the global fog technology market will reach nearly $2.3 billion at the end of 2032. The market for fog technology was $196.7 million at the end of 2022.
Edge computing is a distributed computing paradigm that brings computation and data storage closer to the sources of data. This ppt contains everything about Edge Computing Starting from its Definition, needs, terms involved to its merits, demerits and application use cases
Transforming Businesses With Edge Computing.pptxaitech1
Edge computing usage is accelerating with the evolution of AI, IoT, and 5G. The number of use cases deployed at the edge is augmenting as well. How is edge computing transforming the data space?
The term “fog computing” or “edge computing” means that rather than hosting and working from a centralized cloud, fog systems operate on network ends. It is a term for placing some processes and resources at the edge of the cloud, instead of establishing channels for cloud storage and utilization.
Fog computing is a model in which data, processing and applications are concentrated in devices at the network edge rather than existing almost entirely in the cloud.
Fog Computing is a paradigm that extends Cloud Computing and services to the edge of the network, similar to Cloud, Fog provides data, compute, storage, and application services to end-users.
AI Edge Computing Technology: Edge Computing and Its FutureKavika Roy
Edge Computing as a new approach has uncovered opportunities to implement fresh ways to store and process data. Edge computing has many stored-in answers for many enterprises for multiple problems and will be a real-time efficient solution.
https://www.datatobiz.com/blog/ai-edge-computing-technology/
The proliferation of Internet of Things (IoT) and the success of rich cloud services have pushed the horizon of a new computing paradigm, edge computing, which calls for processing the data at the edge of the network. Edge computing has the potential to address the concerns of response time requirement, battery life constraint, bandwidth cost saving, as well as data safety and privacy. In this paper, we introduce the definition of edge computing, followed by several case studies, ranging from cloud offloading to smart home and city, as well as collaborative edge to materialize the concept of edge computing. Finally, we present several challenges and opportunities in the field of edge computing, and hope this paper will gain attention from the community and inspire more research in this direction.
Edge computing refers to the enabling technologies allowing computation to be performed at the edge of the network, on downstream data on behalf of cloud services and upstream data on behalf of IoT services. Here we define “edge” as any computing and network resources along the path between data sources and cloud data centers. For example, a smart phone is the edge between body things and cloud, a gateway in a smart home is the edge between home things and cloud, a micro data center and a cloudlet is the edge between a mobile device and cloud. The rationale of edge computing is that computing should happen at the proximity of data sources. From our point of view, edge computing is interchangeable with fog computing, but edge computing focus more toward the things side, while fog computing focus more on the infrastructure side. Edge computing could have as big an impact on our society as has the cloud computing.
Extends cloud computing services to the edge of the network.
Similar to cloud, Fog provides:
Data
Computation
Storage
Application Services to end users.
Motivations for Fog Computing:
Smart Grid, Smart Traffic Lights in vehicular networks and Software Defined Networks.
Deep Learning Approaches for Information Centric Network and Internet of Thingsijtsrd
Technologies are rapidly increasing with additions to them every single day. Cloud Computing and the Internet of Things IoT have become two very closely associated with future internet technologies. One provides a platform to the other for success, the benefits of which could be from computing to processing and analyzing the information to reduce latency for real time applications. However, there are a few IoT devices that do not support on device processing. An alternate solution of this is Edge Computing, where the consumers can witness a close call with the computation and services. In this work, we will be to studying and discussing the application of combining Deep Learning with IoT and Information Centric Networking. A Convolutional Neural Network CNN model, a Deep Learning model, can make the most reliable data available from the complex IoT environment. Additionally, some Deep Learning models such as Recurrent Neural Network RNN and Reinforcement Learning have also integrated with IoT, which can also collect the information from real time applications. Aashay Pawar "Deep Learning Approaches for Information - Centric Network and Internet of Things" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-6 , October 2020, URL: https://www.ijtsrd.com/papers/ijtsrd33346.pdf Paper Url: https://www.ijtsrd.com/engineering/computer-engineering/33346/deep-learning-approaches-for-information--centric-network-and-internet-of-things/aashay-pawar
Microsoft Telecommunications Industry Newsletter | December 2019Rick Lievano
The Microsoft Worldwide Telecommunications Industry team is pleased to share with you the December 2019 Telecommunications Industry Newsletter, available to both internal and external audiences. We encourage you to share it with your colleagues and distribute it to your customers and partners as appropriate. As always, we welcome your input, feedback, and suggestions!
Constellation’s technology will enable the advancement of the digital revolution by creating an ecosystem facilitating decentralized applications throughout a scalable distributed network. Constellation acts as a centerpiece framework that other applications can integrate with, without giving away data security and application dependency. Furthermore, our goal is to leverage existing technologies in distributed computing, big data and machine learning that are widely used among developer communities, and apply them to a decentralized distributed network.
https://runfrictionless.com/b2b-white-paper-service/
Everything You Need to Know About Edge Computing TechnologiesCerebrum Infotech
Edge computing services deliver data more quickly to various networks and bias at or close to the user's location. The storing of data, however, is done through cloud computing. On our website, more details are available.
A Comprehensive Exploration of Fog Computing.pdfEnterprise Wired
This article delves into the intricacies of Fog computing, exploring its definition, key components, benefits, and its transformative impact on various industries.
Edge computing is redefining the cloud computing space. The growing de-emphasis on the cloud’s role in connected environments is expected to lead to smarter and faster autonomous solutions that have the potential to reshape the IoT landscape. Edge computing will transform the IoT landscape into a hyperconnected environment where the restrictions related to latency and computation capacity will be eliminated. Many companies are transforming their business models to attain edge computing capabilities necessary for offering end to end services.
The recent years have witnessed a number of mergers and acquisitions in the edge computing space for IoT services, with the increase in M&A activities representing the industry’s conundrum of cloud, edge, and hybrid architectures, and the race to achieve a considerable market share.
This report includes an analysis of approximately 60 deals, along with a detailed technology overview and the purpose of the acquisitions. The M&A analysis section offers a comprehensive view of the transactions around edge computing, covering different technology aspects including data center, AI, security, software-defined WAN (SD-WAN), analytics, interoperability, multi-access edge computing (MEC), and others.
To purchase the full report, write to us at info@netscribes.com
Edge computing, trends and drivers to enable critical use cases for the digital economy. Types of edge and scale factors are mentioned in this article.
The Future of Fog Computing and IoT: Revolutionizing Data ProcessingFredReynolds2
Sending a business e-mail, watching a YouTube video, making an online video call meeting, or playing a video game online requires considerable data flow. It necessitates such massive data flow in the direction of servers in data centers. Cloud computing prefers remote data processing and substantial storage systems to develop online apps we use daily. But we must know that other decentralized cloud computing systems exist. Fog computing technology is growing wildly in popularity. As per fog technology experts, the global fog technology market will reach nearly $2.3 billion at the end of 2032. The market for fog technology was $196.7 million at the end of 2022.
Edge computing is a distributed computing paradigm that brings computation and data storage closer to the sources of data. This ppt contains everything about Edge Computing Starting from its Definition, needs, terms involved to its merits, demerits and application use cases
Transforming Businesses With Edge Computing.pptxaitech1
Edge computing usage is accelerating with the evolution of AI, IoT, and 5G. The number of use cases deployed at the edge is augmenting as well. How is edge computing transforming the data space?
The term “fog computing” or “edge computing” means that rather than hosting and working from a centralized cloud, fog systems operate on network ends. It is a term for placing some processes and resources at the edge of the cloud, instead of establishing channels for cloud storage and utilization.
Fog computing is a model in which data, processing and applications are concentrated in devices at the network edge rather than existing almost entirely in the cloud.
Fog Computing is a paradigm that extends Cloud Computing and services to the edge of the network, similar to Cloud, Fog provides data, compute, storage, and application services to end-users.
AI Edge Computing Technology: Edge Computing and Its FutureKavika Roy
Edge Computing as a new approach has uncovered opportunities to implement fresh ways to store and process data. Edge computing has many stored-in answers for many enterprises for multiple problems and will be a real-time efficient solution.
https://www.datatobiz.com/blog/ai-edge-computing-technology/
The proliferation of Internet of Things (IoT) and the success of rich cloud services have pushed the horizon of a new computing paradigm, edge computing, which calls for processing the data at the edge of the network. Edge computing has the potential to address the concerns of response time requirement, battery life constraint, bandwidth cost saving, as well as data safety and privacy. In this paper, we introduce the definition of edge computing, followed by several case studies, ranging from cloud offloading to smart home and city, as well as collaborative edge to materialize the concept of edge computing. Finally, we present several challenges and opportunities in the field of edge computing, and hope this paper will gain attention from the community and inspire more research in this direction.
Edge computing refers to the enabling technologies allowing computation to be performed at the edge of the network, on downstream data on behalf of cloud services and upstream data on behalf of IoT services. Here we define “edge” as any computing and network resources along the path between data sources and cloud data centers. For example, a smart phone is the edge between body things and cloud, a gateway in a smart home is the edge between home things and cloud, a micro data center and a cloudlet is the edge between a mobile device and cloud. The rationale of edge computing is that computing should happen at the proximity of data sources. From our point of view, edge computing is interchangeable with fog computing, but edge computing focus more toward the things side, while fog computing focus more on the infrastructure side. Edge computing could have as big an impact on our society as has the cloud computing.
Extends cloud computing services to the edge of the network.
Similar to cloud, Fog provides:
Data
Computation
Storage
Application Services to end users.
Motivations for Fog Computing:
Smart Grid, Smart Traffic Lights in vehicular networks and Software Defined Networks.
Deep Learning Approaches for Information Centric Network and Internet of Thingsijtsrd
Technologies are rapidly increasing with additions to them every single day. Cloud Computing and the Internet of Things IoT have become two very closely associated with future internet technologies. One provides a platform to the other for success, the benefits of which could be from computing to processing and analyzing the information to reduce latency for real time applications. However, there are a few IoT devices that do not support on device processing. An alternate solution of this is Edge Computing, where the consumers can witness a close call with the computation and services. In this work, we will be to studying and discussing the application of combining Deep Learning with IoT and Information Centric Networking. A Convolutional Neural Network CNN model, a Deep Learning model, can make the most reliable data available from the complex IoT environment. Additionally, some Deep Learning models such as Recurrent Neural Network RNN and Reinforcement Learning have also integrated with IoT, which can also collect the information from real time applications. Aashay Pawar "Deep Learning Approaches for Information - Centric Network and Internet of Things" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-6 , October 2020, URL: https://www.ijtsrd.com/papers/ijtsrd33346.pdf Paper Url: https://www.ijtsrd.com/engineering/computer-engineering/33346/deep-learning-approaches-for-information--centric-network-and-internet-of-things/aashay-pawar
Microsoft Telecommunications Industry Newsletter | December 2019Rick Lievano
The Microsoft Worldwide Telecommunications Industry team is pleased to share with you the December 2019 Telecommunications Industry Newsletter, available to both internal and external audiences. We encourage you to share it with your colleagues and distribute it to your customers and partners as appropriate. As always, we welcome your input, feedback, and suggestions!
Constellation’s technology will enable the advancement of the digital revolution by creating an ecosystem facilitating decentralized applications throughout a scalable distributed network. Constellation acts as a centerpiece framework that other applications can integrate with, without giving away data security and application dependency. Furthermore, our goal is to leverage existing technologies in distributed computing, big data and machine learning that are widely used among developer communities, and apply them to a decentralized distributed network.
https://runfrictionless.com/b2b-white-paper-service/
Future Trends in the Modern Data Stack LandscapeCiente
As we embrace the future, staying abreast of emerging technologies will be crucial for organizations seeking to harness the full potential of their data.
Exploring Different Funding and Investment Strategies for SaaS Growth.pdfCiente
In the competitive landscape of SaaS, securing adequate funding and implementing effective investment strategies are essential for driving growth, scalability, and long-term success.
Embracing autonomous testing is no longer merely an option but emerges as a strategic necessity for organizations committed to delivering superior software solutions within the dynamic contours of the contemporary tech landscape.
Securing Solutions Amid The Journey To Digital Transformation.pdfCiente
Innovation thrives on openness and accessibility, and security requires caution and control. Learn to navigate these challenges for successful digital transformation.
CRM Best Practices For Optimal Success In 2024.pdfCiente
CRM in 2024 is much more than just managing contacts. Read along to know how it is impacting businesses today and how to best implement it to achieve great success.
In this blog, we’ll delve into the importance of cybersecurity incident response planning and provide a guide for building a resilient response strategy.
PostHog is an open-source product analytics platform designed to help businesses understand user behavior on their websites or applications.
Read this Article here: https://medium.com/@ciente/what-is-posthog-and-its-pros-and-cons-05d8dff13194
Learn more: https://ciente.io/blog/
Explore more: https://ciente.io/
Top Technology Trends Businesses Should Invest In This Year.pdfCiente
As we enter 2024, it brings to light a platform ready for more innovation and progress.
Read this Article here: https://ciente.io/blogs/top-technology-trends-businesses-should-invest-in-2024/
Learn more: https://ciente.io/blog/
Explore more: https://ciente.io/
In the fast-paced realm of software development, the integration of security measures is paramount to safeguarding applications and data against an ever-expanding landscape of cyber threats.
Exploring the Applications of GenAI in Supply Chain Management.pdfCiente
Stay ahead of the curve with GenAI's capacity to learn, adapt, and generate insights, revolutionizing traditional supply chain processes for enhanced efficiency and innovation.
Benefits of implementing CI & CD for Machine LearningCiente
Implementing CI & CD in Machine Learning is a strategic move toward optimizing development workflows, enhancing collaboration, and accelerating the deployment of robust and reliable ML models
7 Elements for a Successful Hybrid Cloud Migration Strategy.pdfCiente
The world of IT infrastructure is evolving rapidly, and businesses are increasingly turning to hybrid cloud solutions to strike the perfect balance between on-premises and cloud-based environments.
Read this Article here: https://medium.com/@ciente/7-elements-for-a-successful-hybrid-cloud-migration-strategy-0b2a9dfbff85
Learn more: https://ciente.io/blog/
Follow for more Articles here: https://ciente.io/
In this blog post, we will explore what Ethical Technology is, why it is important, the benefits it brings, and its potential role in shaping our future.
Top Social Selling Tools For Your Business In 2024.pdfCiente
Brands tap into Gen-Z’s world by leveraging social media. But it’s the social selling tools that transform this digital engagement into real-world revenue.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
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/
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
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.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
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.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...
Edge Computing.pdf
1. Edge Computing: The Digital Revolution Driving
the Future and the Top 7 Trends of 2023
Edge computing, a concept that was once just a blip on the radar of
tech enthusiasts, has evolved into a significant player in the ever-
evolving landscape of computer organization and architecture. As we
journey further into 2023, we see this evolution accelerating, firmly
establishing edge computing as a cornerstone in the IT strategy of
businesses and organizations worldwide.
But first things first, why is edge computing the future? To answer
this, we must first take a glimpse at the fundamentals of computing.
Traditionally, cloud computing centralized data processing by
pushing data to a centralized cloud infrastructure for analysis and
decision-making. However, the increasing volume of data generated
2. and the demand for low-latency, high-bandwidth applications have
strained the cloud’s capabilities.
Enter edge computing — an innovative solution that moves data
processing from the cloud to the edge of the network, closer to the
source of data. This model decentralizes data processing, alleviating
the load on the central servers, reducing latency, and leading to
quicker, more efficient decision-making. Imagine a smart traffic
system that can adapt in real-time based on the traffic volume and
conditions or a healthcare monitoring device providing instant
critical health data to doctors. The possibilities with edge computing
are endless. Moreover, in today’s rapidly evolving digital landscape,
the exponential growth of data and the widespread adoption of
connected devices are driving increased demand for storage,
computing, and network capabilities. Consequently, edge computing
has emerged as a pivotal solution, bringing these vital resources
closer to the endpoints. As per a recent report, with the volume of
global data projected to surge to unprecedented levels, reaching 97
zettabytes (ZB) in 2022 and a staggering 181 ZB by 2025, the surge
is largely attributed to the ever-expanding ecosystem of the Internet
of Things (IoT) connected devices. By 2030, the number of IoT
devices is expected to soar to 24.1 billion.
3. The Rise of Edge Computing
The rise of edge computing can be linked to its symbiotic
relationship with cloud computing. Traditional cloud computing
architecture leverages centralized servers — physically remote and
separate from the end-user — to process data. This cloud
infrastructure plays a crucial role in delivering services across the
globe. However, as the digital world continues to grow, a new
approach to cloud strategy has emerged, one that revolves around
edge computing.
Edge computing redefines the standard cloud computing
infrastructure by processing data closer to the source — the edge of
the network — minimizing latency and enhancing the user
4. experience. As such, it enables the migration of computing from the
cloud to the edge, a concept aptly referred to as ‘cloud to the edge.’
As per the latest findings of a comprehensive report from Statista,
the global market for edge computing is anticipated to witness an
impressive surge, with estimated revenues expected to soar to a
staggering 274 billion U.S. dollars by the year 2025. This remarkable
projection highlights the immense growth potential and increasing
significance of edge computing solutions across various industries
and sectors.
The collaboration of edge computing and cloud computing will
redefine the future scope of edge computing, bolstering its adoption
in diverse sectors. How so? The synergistic ‘cloud to edge’ approach
retains the cloud as the orchestrating platform, while the edge
devices, furnished with edge computing software, perform real-time
data processing. This unison amplifies the strengths of both cloud
5. and edge computing, creating a new landscape of ‘cloud edge
computing’.
Top Trends of 2023
As we peer into the future, let’s explore the top 7 trends that are
making waves in edge computing in 2023.
1. AI-Powered Edge Computing: With AI capabilities at the edge,
devices can independently execute complex tasks. For instance, an
AI-enabled security camera at the edge could analyze and recognize
suspicious activities in real-time, triggering an alarm instantly
without needing to send the data back to the cloud. This trend
implies a shift towards smarter, autonomous edge devices that can
learn, adapt, and make decisions.
2. 5G and Edge Computing: 5G technology, with its low latency and
high bandwidth, will enable real-time applications at the edge. For
example, autonomous vehicles can leverage 5G-enabled edge
computing to process massive amounts of data in real-time,
ensuring safe and efficient operations. This convergence will unlock
unprecedented applications, disrupting sectors from transportation
to healthcare, manufacturing, and beyond.
3. Security at the Edge: As we distribute data processing to various
edge devices, each device becomes a potential target for
cyberattacks. Thus, innovative solutions to ensure data privacy and
security will be paramount. This may include advanced encryption,
6. authentication methods, and decentralized security protocols
specifically designed for edge environments.
4. Edge in IoT: With IoT devices generating voluminous data, it’s
more practical to process data at the edge. For instance, an edge-
enabled smart factory could process data from numerous sensors
on-site, enabling real-time monitoring, predictive maintenance, and
streamlined production processes. This trend signifies a move
towards more efficient and powerful IoT systems.
5. Fog Computing: As an extension of edge computing architecture,
fog computing involves a network of edge devices collectively
processing and analyzing data. This distributed approach reduces
the load on individual devices and the cloud, allowing for efficient
data processing and decision-making across the network. It
essentially creates a cooperative environment between edge devices.
6. Industry-Specific Edge Solutions: Different industries have
unique needs and challenges, and as such, bespoke edge computing
solutions will emerge. For example, in the healthcare sector, edge
computing could enable real-time patient monitoring and rapid
diagnostic processes. In retail, edge-enabled systems could provide
real-time inventory tracking and personalized customer experiences.
This trend underscores the versatility and adaptability of edge
computing.
7. Greener Edge: As sustainability becomes more crucial, energy-
efficient edge computing solutions will emerge. Edge devices that
consume less power or that can operate on renewable energy
7. sources will become increasingly popular. Plus, processing data at
the edge reduces the energy spent in transmitting data to the cloud,
contributing to a greener tech ecosystem.
Edge computing undeniably presents a new horizon of
opportunities. Its potential is vast, from improving daily processes
like traffic control to revolutionary applications in healthcare,
manufacturing, and more. As we forge ahead into a data-rich future,
edge computing is destined to be a game-changer, ushering in an era
of smarter, faster, and more efficient digital solutions.
As edge computing continues to mature, it’s important to stay
curious, open, and adaptable. Like any technological revolution, the
transition from a traditional cloud computing infrastructure to an
edge-focused model will present challenges, but the potential
benefits are significant.
In conclusion, edge computing is more than just a trend — it’s an
evolving paradigm that’s reshaping our digital world. It’s a
testament to how far we’ve come in computer organization and
architecture, and an indication of the exciting developments still to
come. As edge computing continues to rise, we can’t help but
wonder: What does the future hold, and how will we shape it?
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