Torchvista, AWS Data Processing MCP Server, Amazon Q + DLC MCP, Streamlit + MCP, ChatGPT AgentBecome an AI Generalist that makes $100K (in 16 hours)Still don’t use AI to automate your work & make big $$? You’re way behind in the AI race. But worry not:Join the World’s First 16-Hour LIVE AI Upskilling Sprint for professionals, founders, consultants & business owners like you. Register Now (Only 500 free seats)Date: Saturday and Sunday, 10 AM - 7 PM.Rated 4.9/10 by global learners – this will truly make you an AI Generalist that can build, solve & work on anything with AI.In just 16 hours & 5 sessions, you will:✅ Learn the basics of LLMs and how they work.✅ Master prompt engineering for precise AI outputs.✅ Build custom GPT bots and AI agents that save you 20+ hours weekly.✅ Create high-quality images and videos for content, marketing, and branding.✅ Automate tasks and turn your AI skills into a profitable career or business.All by global experts from companies like Amazon, Microsoft, SamurAI and more. And it’s ALL. FOR. FREE. 🤯 🚀$5100+ worth of AI tools across 2 days — Day 1: 3000+ Prompt Bible, Day 2: Roadmap to make $10K/month with AI, additional bonus: Your Personal AI Toolkit Builder.Register Now (Only 500 free seats)SponsoredSubscribe|Submit a tip|Advertise with usWelcome to DataPro #143: From Bits to Brains - The Tools Driving the Next Wave of Intelligent Systems 🧠📡What if your database could talk back with charts, or your containers built themselves when you spoke? What if your AI agent could say “I don’t know” and actually mean it?This week, we dive into a new breed of tools designed not just to build smarter systems, but to understand, reason, and scale them. These aren’t just marginal upgrades, they’re foundational shifts in how we build and interact with AI.Start with Mitra: Amazon’s tabular foundation model that ditches real-world data for synthetic priors (think causal graphs + tree ensembles) and still manages SOTA across tabular benchmarks via in-context learning.Then check out Qwen3-Coder-480B-A35B-Instruct, a Claude-class code model with 256K native context and 1M with Yarn, engineered for repository-scale agentic reasoning.Want BI that speaks SQL and your language? Wren AI is your GenBI agent, natural language in, SQL and insights out, thanks to a semantic layer, LLM integrations, and plug-and-play APIs.Visual domains aren’t left out. Cosmos DiffusionRenderer from NVIDIA reinvents video re-lighting with neural inverse rendering, 70GB models, and GPU-optimized pipelines for stunning realism.If you’re building with agents, 7 MCP Best Practices are a must-read, from schema validation to Dockerized deployments to performance tuning at scale.Meanwhile, ChatGPT Agent blurs the line between reasoning and doing, browsing, coding, and summarizing, all on its own virtual machine.But let’s not forget the human side. How Not to Mislead with Your Data is a masterclass on spotting narrative bias in data storytelling, and the ethical stakes behind our charts.And yes, Cloud SQL meets Vertex AI now means vector search and Gemini are just SQL calls away. You can embed, search, and analyze, all inside your relational DB.In the wild, Streamlit + MCP brings it all together in a sleek client interface that lets users query DeepWiki or HuggingFace-backed agents via natural language, no frontend dev required.AWS Data Processing MCP Server takes that to an enterprise level, streamlining schema discovery, query generation, and job monitoring across Glue, Athena, and EMR, all via natural language.Then, go deep with Amazon Q + DLC MCP: a system that automates PyTorch/TensorFlow container orchestration with a single prompt. Think: “Deploy PyTorch for multi-node training”, and it just happens.Finally, DeepSeek R1 on Vertex AI means no GPUs needed, just an API call. Run it on-demand, serverless, pay-as-you-go, no infrastructure stress.Still thinking of attention heads asdot products? Transformers as Addition Machines reframes attention with mechanistic interpretation, revealing layer-by-layer logic circuits.Or maybe you prefer pictures, Torchvista lets you trace PyTorch forward passes as interactive graphs inside your notebook, a dream for debugging or demystifying hidden layers.Semantic communication is making machines communicate with meaning, not bits. It’s the end of false alarms and overfitting to known categories, and it's all because of the knowledge graphs that reason over context and uncertainty.And if you’re ready to start building today, Google Cloud’s top 25 guides are a treasure trove: from RAG, RLHF, and agent orchestration to CI/CD pipelines and multi-agent chat apps, code included, no excuses.We’re in the midst of a shift: From models that classify to systems that reason. From dashboards to agents. From pixels to meaning.This issue is your map. Dive in, experiment, build.Sponsored: Your data, built your way with Twilio Segment — a customer data platform designed to cut through the chaos, unify your stack, and free you to focus on innovation over integration. Learn more.Cheers,Merlyn ShelleyGrowth Lead, PacktTop Tools Driving New Research 🔧📊⏩ Mitra: Mixed synthetic priors for enhancing tabular foundation models. Amazon’s Mitra is a tabular foundation model (TFM) that uses in-context learning to generalize across tabular tasks without retraining. Pretrained on synthetic data from causal models and tree-based methods, rather than real-world data, Mitra achieves state-of-the-art results across benchmarks like TabRepo and TabArena. It’s open source via AutoGluon 1.4.⏩ Qwen/Qwen3-Coder-480B-A35B-Instruct · Qwen3-Coder-480B-A35B-Instruct is Qwen’s most advanced code model, delivering Claude Sonnet-level performance on agentic coding and browser-use tasks. It supports 256K token context (extendable to 1M), tool calling, and repository-scale understanding. Built with 480B parameters (35B active), it uses in-context prompting and excels at function-call reasoning, agent frameworks, and long-horizon completions.⏩ Wren AI is your GenBI Agent: Wren AI is a GenBI agent that lets you query databases in natural language to generate SQL, charts, and AI-driven insights instantly. It features a semantic layer for governed accuracy, integrates with top LLMs, supports embedding via API, and connects to major data sources. Fast setup, cloud and open-source options included.⏩ nv-tlabs/cosmos1-diffusion-renderer: Cosmos DiffusionRenderer is NVIDIA’s latest video diffusion framework for high-quality image and video de-lighting and re-lighting. Built on DiffusionRenderer and powered by Cosmos, it features neural inverse and forward rendering with significant improvements in realism and control. It supports GPU-efficient inference, 70GB models, and full relighting pipelines for both static images and dynamic videos.Topics Catching Fire in Data Circles 🔥💬⏩ 7 MCP Server Best Practices for Scalable AI Integrations in 2025: Model Context Protocol (MCP) servers are becoming essential for secure, scalable, and agentic AI integrations. This guide outlines 7 best practices, toolset design, proactive security, schema validation, local/remote testing, Docker packaging, performance tuning, and documentation, that reduce errors, boost developer adoption, and power industry-wide AI success across finance, healthcare, e-commerce, and more.⏩ ChatGPT Agent: Bridging Research and Action: ChatGPT Agent introduces a powerful leap in agentic AI: it can now think and act on your behalf using its own virtual computer, navigating websites, running code, analyzing data, and producing editable outputs like slides and spreadsheets. It integrates browsing, terminals, APIs, and tool access to complete complex real-world tasks autonomously.⏩ How Not to Mislead with Your Data-Driven Story? Data storytelling helps us understand the world, but it can also mislead. This piece explores how persuasive narratives, even with accurate data, can distort truth. It highlights narrative bias risks like selection, framing, and interpretation, and urges data professionals to balance emotional storytelling with clarity, ethics, and rigorous data literacy.⏩ Integrate your Cloud SQL for MySQL instance with Vertex AI and vector search: Google Cloud’s Cloud SQL for MySQL now supports vector embeddings and Vertex AI integration, empowering developers to run AI-powered search and analysis directly in SQL. You can generate, store, and search vector embeddings with native SQL functions, perform ANN search, and invoke Gemini or custom Vertex AI models to assess customer sentiment or predict behavior, all within your database.New Case Studies from the Tech Titans 🚀💡⏩ MCP Client Development with Streamlit: Build Your AI-Powered Web App. This tutorial walks you through building a Streamlit-based MCP client interface that connects to remote MCP servers like DeepWiki and HuggingFace. The client lets users input topics and receive AI-generated summaries or recommendations via OpenAI’s API. It covers setup, secure key handling, MCP tool integration, and UI design, enabling rapid, modular deployment of AI-powered web tools.⏩ Accelerating development with the AWS Data Processing MCP Server and Agent: The AWS Data Processing MCP Server simplifies complex analytics workflows by enabling AI-driven natural language interactions with services like AWS Glue, Athena, and EMR. Built on the Model Context Protocol (MCP), it abstracts multi-service orchestration, automating tasks like schema discovery, query generation, reporting, and monitoring. Developers can integrate it via Amazon Q CLI or Claude Desktop to streamline onboarding, accelerate insight generation, and enhance observability.⏩ Streamline deep learning environments with Amazon Q Developer and MCP: Amazon Q + the DLC MCP Server radically simplifies how AI/ML teams manage Deep Learning Containers. Instead of manually customizing, testing, and deploying DLCs for PyTorch or TensorFlow, developers can now use natural language via Amazon Q CLI to automate everything, from image selection to ECR deployment, distributed training, and environment troubleshooting. It turns container operations into secure, conversational workflows.⏩ Deepseek R1 is available for everyone in Vertex AI Model Garden: DeepSeek R1 is now available on Vertex AI’s Model-as-a-Service (MaaS) platform, enabling businesses to access this powerful open model without managing GPU infrastructure. With just a few clicks or API calls, teams can test and deploy DeepSeek via a serverless, pay-as-you-go model. Vertex AI handles security, scalability, and compliance, accelerating AI innovation with zero infrastructure overhead.Blog Pulse: What’s Moving Minds 🧠✨⏩ Transformers (and Attention) are Just Fancy Addition Machines: Mechanistic interpretation is a novel AI interpretability approach that goes beyond tools like SHAP and LIME by uncovering how neural networks compute, not just what features influence outputs. It traces how features are encoded and transformed across layers, especially in transformers. By reimagining multi-head attention as additive rather than concatenative, it enables circuit-level analysis of neuron behavior. This method reveals the internal logic of models, opening doors to deeper understanding, debugging, and trust in complex AI systems.⏩ Torchvista: Building an Interactive Pytorch Visualization Package for Notebooks. Torchvista is an open-source tool for interactively visualizing the forward pass of PyTorch models inside web-based notebooks like Colab or Jupyter. Unlike static tools, it offers zoomable, modular graph views, supports error-tolerant partial visualizations, and requires just a one-line trace_model() call. It traces tensor flows and module hierarchies during forward execution and renders them as interactive, nested graphs using JS libraries like D3 and Graphviz, making complex models understandable, debuggable, and more accessible for iterative development and exploration.⏩ From Rules to Relationships: How Machines Are Learning to Understand EachOther? Semantic communication shifts focus from transmitting raw bits to conveying meaning, crucial in modern, machine-heavy networks. Traditional SKB systems compress messages via fixed categories, but fail in unfamiliar scenarios. Knowledge graph-based semantic communication fixes this by modeling relationships between entities, enabling contextual reasoning. This allows systems to intelligently handle edge cases (e.g., maintenance workers during off-hours) by inferring intent and suggesting verification over false alarms. Though graph systems require more compute and expertise, they vastly improve real-world accuracy, adaptability, and decision-making in noisy, dynamic environments.⏩ 25 top how-to guides for Google Cloud: The best way to learn AI is to build it, and Google Cloud now offers a curated collection of 25+ hands-on how-to guides to help you do just that. From deploying large models like Llama 3 and DeepSeek on high-performance infrastructure, to creating advanced gen AI apps, fine-tuning with RAG and RLHF, and integrating agents with real-world systems, this living resource accelerates your AI journey. Each guide includes code, tools, and best practices, ready to help you build smarter, faster, and at scale.See you next time!*{box-sizing:border-box}body{margin:0;padding:0}a[x-apple-data-detectors]{color:inherit!important;text-decoration:inherit!important}#MessageViewBody a{color:inherit;text-decoration:none}p{line-height:inherit}.desktop_hide,.desktop_hide table{mso-hide:all;display:none;max-height:0;overflow:hidden}.image_block img+div{display:none}sub,sup{font-size:75%;line-height:0} @media (max-width: 100%;display:block}.mobile_hide{min-height:0;max-height:0;max-width: 100%;overflow:hidden;font-size:0}.desktop_hide,.desktop_hide table{display:table!important;max-height:none!important}}

Mobile development blogs, tutorials and resources inside!Latest Mobile Dev Insights: iOS, Android, Cross-PlatformAdvertise with Us|Sign Up to the NewsletterMobilePro #181: Launch Your App on a Real iOS Device Like a ProHi ,Welcome to the 181st edition of MobilePro! This week we bring you something different.This edition walks through a pragmatic setup for iOS development, the kind that makes device testing feel less like a hurdle and more like a launchpad. It’s drawn from hands-on workflows and reframed here for the everyday developer looking to get builds onto real devices—quickly, reliably, and without surprises.If you’ve ever hit a wall trying to run your app outside the simulator, this feature that borrows from Ahmad Sahar's iOS 18 for Programming for Beginners is for you.You will learn the following from this article:How to connect your iOS device to Mac?How to enable developer mode?How to set up Xcode for device deployment?How to add a developer account to Xcode?How to trust the developer app certificate?Take the Survey!Know The AuthorAhmad Sahar is a trainer, presenter, and consultant at Tomafuwi Productions, specializing in conducting training courses for macOS and iOS, macOS Support Essentials certification courses, and iOS Development courses. He is a member of the DevCon iOS and MyCocoaHeads online communities in Malaysia and has conducted presentations and talks for both groups. In his spare time, he likes building and programming LEGO Mindstorms robots.📱 How to run your app on an iOS deviceDeveloping apps with Xcode and the iOS Simulator is a great way to get started, but if you want to truly understand how your app behaves in the real world, there’s no substitute for testing it on an actual device. Physical devices offer access to real sensors, hardware features, and network environments that simply can’t be replicated in the Simulator. Whether you’re building your first app or refining a production-ready project, deploying to a real iPhone or iPad helps you catch bugs, optimize performance, and deliver a better experience to your users. In this article, we’ll walk you through the entire process—from connecting your device and setting up Developer Mode to configuring and signing certificates.While Apple's Simulator allows you to run and test your app during development, there's no substitute for using a real device. Some hardware components and software APIs simply can’t be simulated, which is why testing on a physical iOS device is crucial for a complete development experience.NoteTo explore the nuances between running your app on a simulator versus a real device, Apple provides a detailed comparison here.Step 1: Connecting your iOS deviceBefore running your app on a physical iOS device, make sure you have:Your iOS deviceAn Apple ID (a free or paid developer account)A Mac with Xcode installedTo connect your iOS device, follow these steps:Use the cable that came with your iOS device to connect your device to your Mac, and make sure the iOS device is unlocked.Your Mac will display an Allow Accessory to Connect alert. Click Allow.Your iOS device will display a Trust This Computer alert. Tap Trust and key in your device passcode when prompted. Your iOS device is now connected to your Mac and will appear in Xcode's Destination menu.Step 2: Enabling the developer mode (iOS 16+)Developer Mode was introduced by Apple during their Worldwide Developers Conference in 2022 (WWDC 2022) and is required to install, run, and debugyour apps on devices running iOS 16 or greater.To watch a WWDC 2022 video on Developer Mode, click here.Follow these steps to enable Developer mode:Choose Window | Devices and Simulators in the Xcode menu bar. You will see a window displaying a message saying Developer Mode disabled.To enable Developer Mode on your iOS device, go to Settings | Privacy & Security, scroll down to the Developer Mode item, and tap it.Turn the Developer Mode switch on.An alert will appear to warn you that Developer Mode reduces the security of your iOS device. Tap the alert's Restart button.After your iOS device restarts and you unlock it, confirm that you want to enable Developer Mode by tapping Enable and entering your iOS device's passcode.The Devices and Simulators window will display a Preparing iPhone message. Wait a few minutes, then verify that the Devices and Simulators window no longer displays the Developer Mode disabled text.Your iOS device is now ready to install and run apps from Xcode.Step 3: Setting up Xcode for device deploymentTo set up Xcode, follow these steps:In Xcode, choose your iOS device from the Destination menu.Run the project by clicking the Run button (or use Command + R). You will get the following error in Xcode's Signing & Capabilities pane, Signing for "JRNL" requires a development team.This is because a digital certificate is required to run the app on an iOS device, and you need to add a free or paid Apple developer account to Xcode so the digital certificate can be generated.NoteUsing an Apple ID to create a free developer account will allow you to test your app on an iOS device, but it will only be valid for 7 days. Also, you will need a paid Apple developer account to distribute apps on the App Store.Certificates ensure that the only apps that run on your device are the ones you authorize. This helps to protect against malware. You can also learn more about them here.Step 4: Adding a developer account to XcodeHere are the steps to add Developer account to Xcode:Click the Add Account... button.The Xcode Settings window appears with the Accounts pane selected. Enter your Apple ID and click Next.Note that you can create a different Apple ID if you wish using the Create Apple ID button.TipYou can also access the Xcode settings by choosing Settings in the Xcode menu.Enter your password when prompted. After a few minutes, the Accounts pane will display your account settings.Close the Settings window when you're done by clicking the red close button in the top-left corner.In Xcode's Editor area, click Signing & Capabilities. Make sure Automatically manage signing is ticked and Personal Team is selected from the Team pop-up menu.If you still see errors on this screen, try changing your Bundle Identifier by typing some random characters into it, for example, myname6712.JRNL.Build and run your app. If you are prompted for a password, enter your Mac’s login password and click Always Allow.Your app will be installed on your iOS device. However, it will not launch, and you will see the following message:This means you need to trust the certificate that has been installed on your device. You'll learn how to do this in the next section.Step 5: Trusting the developer app certificate on your iOS deviceA Developer App certificate is a special file that gets installed on your iOS device along with your app. Before your app can run, you need to trust it. Follow these steps:On your iOS device, tap Settings | General | VPN & Device Management.Tap your Apple ID:Tap Trust:Tap Allow:Youshould see the followingtext, which shows the app is now trusted:Click the Run button in Xcode to build and run again. You'll see your app launch and run on your iOS device.Success!Your app is now running on an actual iOS device! This milestone brings you one step closer to shipping your app to real users.If you want to read more and turn your app idea into reality, then Ahmad Sahar's iOS 18 Programming for Beginners is for you!🏗️ Experience iOS 18 and Swift 6 through hands-on projects🛠️ Build your first iOS apps, complete with user-friendly interfaces using UIKit💡 Learn best practices from an experienced developer for robust app designiOS 18 Programming for BeginnersBuy now at $44.99!👋 And that’s a wrap. We hope you enjoyed this new format of MobilePro.P.S.: If you have any suggestions or feedback, help us improve by sharing your thoughts. Click on the survey below.Take the Survey!Cheers,Runcil Rebello,Editor-in-Chief, MobilePro*{box-sizing:border-box}body{margin:0;padding:0}a[x-apple-data-detectors]{color:inherit!important;text-decoration:inherit!important}#MessageViewBody a{color:inherit;text-decoration:none}p{line-height:inherit}.desktop_hide,.desktop_hide table{mso-hide:all;display:none;max-height:0;overflow:hidden}.image_block img+div{display:none}sub,sup{font-size:75%;line-height:0}#converted-body .list_block ol,#converted-body .list_block ul,.body [class~=x_list_block] ol,.body [class~=x_list_block] ul,u+.body .list_block ol,u+.body .list_block ul{padding-left:20px} @media (max-width: 100%;display:block}.mobile_hide{min-height:0;max-height:0;max-width: 100%;overflow:hidden;font-size:0}.desktop_hide,.desktop_hide table{display:table!important;max-height:none!important}}