Using Microsoft ASP.NET MVC to Easily Extend a Web Site into the Mobile Space
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The document discusses the importance of mobile strategies in accessing and interacting with data, emphasizing user experience and device targeting. It mentions the ASP.NET MVC framework and provides insights on developing mobile applications. Additionally, it highlights Microsoft's role in creating mobile experiences and the necessity for continuous adaptation to market changes.
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Securing Account Lifecycles in the Age of Deepfakes.pptx
Securing Account Lifecycles in the Age of Deepfakes.pptxFIDO Alliance Securing Account Lifecycles in the Age of Deepfakes
10 Key Challenges for AI within the EU Data Protection Framework.pdf
10 Key Challenges for AI within the EU Data Protection Framework.pdfPriyanka Aash 10 Key Challenges for AI within the EU Data Protection Framework
"How to survive Black Friday: preparing e-commerce for a peak season", Yurii ...
"How to survive Black Friday: preparing e-commerce for a peak season", Yurii ...Fwdays We will explore how e-commerce projects prepare for the busiest time of the year, which key aspects to focus on, and what to expect. We’ll share our experience in setting up auto-scaling, load balancing, and discuss the loads that Silpo handles, as well as the solutions that help us navigate this season without failures.
PyCon SG 25 - Firecracker Made Easy with Python.pdf
PyCon SG 25 - Firecracker Made Easy with Python.pdfMuhammad Yuga Nugraha Explore the ease of managing Firecracker microVM with the firecracker-python. In this session, I will introduce the basics of Firecracker microVM and demonstrate how this custom SDK facilitates microVM operations easily. We will delve into the design and development process behind the SDK, providing a behind-the-scenes look at its creation and features. While traditional Firecracker SDKs were primarily available in Go, this module brings a simplicity of Python to the table.
"Scaling in space and time with Temporal", Andriy Lupa.pdf
"Scaling in space and time with Temporal", Andriy Lupa.pdfFwdays Design patterns like Event Sourcing and Event Streaming have long become standards for building real-time analytics systems. However, when the system load becomes nonlinear with fast and often unpredictable spikes, it's crucial to respond quickly in order not to lose real-time operating itself.
In this talk, I’ll share my experience implementing and using a tool like Temporal.io. We'll explore the evolution of our system for maintaining real-time report generation and discuss how we use Temporal both for short-lived pipelines and long-running background tasks.
EIS-Webinar-Engineering-Retail-Infrastructure-06-16-2025.pdf
EIS-Webinar-Engineering-Retail-Infrastructure-06-16-2025.pdfEarley Information Science As AI reshapes expectations in retail and B2B commerce, organizations are recognizing a critical reality: meaningful AI outcomes depend on well-structured, adaptable infrastructure. In this session, Seth Earley is joined by Phil Ryan - AI strategist, search technologist, and founder of Glass Leopard Technologies - for a candid conversation on what it truly means to engineer systems for scale, agility, and intelligence.
Phil draws on more than two decades of experience leading search and AI initiatives for enterprise organizations. Together, he and Seth explore the challenges businesses face when legacy architectures limit personalization, agility, and real-time decisioning - and what needs to change to support agentic technologies and next-best-action capabilities.
Key themes from the webinar include:
Composability as a prerequisite for AI - Why modular, loosely coupled systems are essential for adapting to rapid innovation and evolving business needs
Search and relevance as foundational to AI - How techniques honed-in enterprise search have laid the groundwork for more responsive and intelligent customer experiences
From MDM and CDP to agentic systems - How data platforms are evolving to support richer customer context and dynamic orchestration
Engineering for business alignment - Why successful AI programs require architectural decisions grounded in measurable outcomes
The conversation is practical and forward-looking, connecting deep technical understanding with real-world business needs. Whether you’re modernizing your commerce stack or exploring how AI can enhance product discovery, personalization, or customer journeys, this session provides a clear-eyed view of the capabilities, constraints, and priorities that matter most.
Mastering AI Workflows with FME by Mark Döring
Mastering AI Workflows with FME by Mark DöringSafe Software Harness the full potential of AI with FME: From creating high-quality training data to optimizing models and utilizing results, FME supports every step of your AI workflow. Seamlessly integrate a wide range of models, including those for data enhancement, forecasting, image and object recognition, and large language models. Customize AI models to meet your exact needs with FME’s powerful tools for training, optimization, and seamless integration
Wenn alles versagt - IBM Tape schützt, was zählt! Und besonders mit dem neust...
Wenn alles versagt - IBM Tape schützt, was zählt! Und besonders mit dem neust...Josef Weingand IBM LTO10
Salesforce Summer '25 Release Frenchgathering.pptx.pdf
Salesforce Summer '25 Release Frenchgathering.pptx.pdfyosra Saidani Salesforce Summer '25 Release Frenchgathering.pptx.pdf
Agentic AI for Developers and Data Scientists Build an AI Agent in 10 Lines o...
Agentic AI for Developers and Data Scientists Build an AI Agent in 10 Lines o...All Things Open Presented at All Things Open RTP Meetup
Presented by William Hill - Developer Advocate, NVIDIA
Title: Agentic AI for Developers and Data Scientists
Build an AI Agent in 10 Lines of Code and the Concepts Behind the Code
Abstract: In this talk we will demonstrate building a working data science AI agent in 10 lines of basic Python code in a Colab notebook. Our AI Agent will perform LLM prompt-driven visual analysis using open-source libraries. In this session we will show how to develop an AI Agent using GPUs through NVIDIA’s developer program and Google Colab notebooks. After coding our AI Agent, we will break down the 10 lines of code. We will show the key components and open source library integrations that enable the agent's functionality, focusing on practical implementation details and then the theoretical concepts. The presentation concludes with a survey of current LLM technologies and the latest trends in developing AI applications for enthusiasts and enterprises
"Database isolation: how we deal with hundreds of direct connections to the d...
"Database isolation: how we deal with hundreds of direct connections to the d...Fwdays What can go wrong if you allow each service to access the database directly? In a startup, this seems like a quick and easy solution, but as the system scales, problems appear that no one could have guessed.
In my talk, I'll share Solidgate's experience in transforming its architecture: from the chaos of direct connections to a service-based data access model. I will talk about the transition stages, bottlenecks, and how isolation affected infrastructure support. I will honestly show what worked and what didn't. In short, we will analyze the controversy of this talk.
2025_06_18 - OpenMetadata Community Meeting.pdf
2025_06_18 - OpenMetadata Community Meeting.pdfOpenMetadata The community meetup was held Wednesday June 18, 2025 @ 9:00 AM PST.
Catch the next OpenMetadata Community Meetup @ https://www.meetup.com/openmetadata-meetup-group/
In this month's OpenMetadata Community Meetup, "Enforcing Quality & SLAs with OpenMetadata Data Contracts," we covered data contracts, why they matter, and how to implement them in OpenMetadata to increase the quality of your data assets!
Agenda Highlights:
👋 Introducing Data Contracts: An agreement between data producers and consumers
📝 Data Contracts key components: Understanding a contract and its purpose
🧑🎨 Writing your first contract: How to create your own contracts in OpenMetadata
🦾 An OpenMetadata MCP Server update!
➕ And More!
From Manual to Auto Searching- FME in the Driver's Seat
From Manual to Auto Searching- FME in the Driver's SeatSafe Software Finding a specific car online can be a time-consuming task, especially when checking multiple dealer websites. A few years ago, I faced this exact problem while searching for a particular vehicle in New Zealand. The local classified platform, Trade Me (similar to eBay), wasn’t yielding any results, so I expanded my search to second-hand dealer sites—only to realise that periodically checking each one was going to be tedious. That’s when I noticed something interesting: many of these websites used the same platform to manage their inventories. Recognising this, I reverse-engineered the platform’s structure and built an FME workspace that automated the search process for me. By integrating API calls and setting up periodic checks, I received real-time email alerts when matching cars were listed. In this presentation, I’ll walk through how I used FME to save hours of manual searching by creating a custom car-finding automation system. While FME can’t buy a car for you—yet—it can certainly help you find the one you’re after!
OpenACC and Open Hackathons Monthly Highlights June 2025
OpenACC and Open Hackathons Monthly Highlights June 2025OpenACC The OpenACC organization focuses on enhancing parallel computing skills and advancing interoperability in scientific applications through hackathons and training. The upcoming 2025 Open Accelerated Computing Summit (OACS) aims to explore the convergence of AI and HPC in scientific computing and foster knowledge sharing. This year's OACS welcomes talk submissions from a variety of topics, from Using Standard Language Parallelism to Computer Vision Applications. The document also highlights several open hackathons, a call to apply for NVIDIA Academic Grant Program and resources for optimizing scientific applications using OpenACC directives.
" How to survive with 1 billion vectors and not sell a kidney: our low-cost c...
" How to survive with 1 billion vectors and not sell a kidney: our low-cost c...Fwdays Let's talk about our history. How we started the project with a small vector database of less than 2 million records. Later, we received a request for +100 million records, then another +100... And so gradually we reached almost 1 billion. Standard tools were quickly running out of steam - we were running into performance, index size, and very limited resources. After a long series of trials and errors, we built our own low-cost cluster, which today stably processes thousands of queries to more than 1B vectors.
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