How to use Agent and Copilot? We encourage you to try this learning path, which includes insights in the supply chain space.

🚨 The Accuracy Mirage: Why AI Models Break in the Real World 🌍 We often celebrate when a model hits 99% accuracy in training… but reality has other plans. Once deployed, the same model might struggle — predictions go off, performance drops, and confidence evaporates. Why does this happen? Let’s uncover a few hidden reasons 👇 🔹 1️⃣ Data Drift The data your model sees in production slowly changes over time — user behavior, environment, or even market trends evolve. The model doesn’t. 🔹 2️⃣ Bias in Training Data If your training data isn’t truly representative, your model learns a narrow “worldview.” It performs great on test data, but poorly in the real world. 🔹 3️⃣ Missing Monitoring Many deployments stop at “model ready.” But just like software, models need continuous monitoring — tracking metrics, latency, and prediction quality. 🔹 4️⃣ Lack of Feedback Loop Without real-world feedback and periodic retraining, even the best model becomes outdated. 🧠 The real success in AI isn’t just building models — it’s about maintaining, monitoring, and improving them continuously. 💡 Tip: Tools like Amazon SageMaker Model Monitor and Evidently AI can help detect drift and automate retraining. #ArtificialIntelligence #MachineLearning #DataScience #MLOps #ModelDrift #AIDeployment #AIMonitoring #TechInsights

Excited to share how AI is transforming procurement today. Amazon Business shows how intelligent automation and predictive insights help organizations boost efficiency and agility. Share this with your network to highlight what is possible right now: https://amzn.to/3Wnx9Z1

Imagine a world where computers 𝗱𝗼𝗻’𝘁 𝗷𝘂𝘀𝘁 𝗳𝗼𝗹𝗹𝗼𝘄 𝗶𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝗶𝗼𝗻𝘀 they 𝗹𝗲𝗮𝗿𝗻 𝗳𝗿𝗼𝗺 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲. From predicting what movie you’ll love next to detecting diseases before symptoms even appear, 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 (𝗠𝗟) quietly powers much of the technology that shapes our daily lives. But 𝐰𝐡𝐚𝐭 𝐞𝐱𝐚𝐜𝐭𝐥𝐲 𝐢𝐬 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠?,Why has it become such a game-changer across industries? And how does it manage to turn raw data into intelligent decisions? In this blog, we’ll break down the 𝗳𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀 𝗼𝗳 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 — 𝘄𝗵𝗮𝘁 𝗶𝘁 𝗶𝘀, 𝘁𝗵𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺𝘀 𝗶𝘁 𝘀𝗼𝗹𝘃𝗲𝘀, 𝗶𝘁𝘀 𝗱𝗲𝗳𝗶𝗻𝗶𝗻𝗴 𝗳𝗲𝗮𝘁𝘂𝗿𝗲𝘀, 𝗸𝗲𝘆 𝗯𝗲𝗻𝗲𝗳𝗶𝘁𝘀, 𝗮𝗻𝗱 𝗿𝗲𝗮𝗹-𝘄𝗼𝗿𝗹𝗱 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝘁𝗵𝗮𝘁 𝗽𝗿𝗼𝘃𝗲 𝗶𝘁’𝘀 𝗳𝗮𝗿 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝗷𝘂𝘀𝘁 𝗮 𝘁𝗲𝗰𝗵 𝘁𝗿𝗲𝗻𝗱. Whether you’re a curious beginner or looking to sharpen your understanding, this guide will help you see why ML is transforming the way we live, work, and innovate. To read more about 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 (𝐌𝐋) 𝐅𝐮𝐧𝐝𝐚𝐦𝐞𝐧𝐭𝐚𝐥𝐬, Click on the link below. #AWS #Amazonwebservices #CloudComputing #AWSCommunity #AWSCloud #AWSBlog #AWSUpdates #AWSLearning #CloudEngineering #MachineLearning #AI #TechBlog #LearnAWS #TechCommunity #CloudCareer #Cloud

Learning from others’ experiences is powerful, and sometimes, paper makes it even more magical. 😉 Yes, I’m reading the September–October edition of Harvard Business Review in print. Despite being a huge fan of screen reading (my Kobo helped me hit the 50-books mark in just over a year!), there’s something special about flipping through pages and receiving this magazine at home. But back to the topic! We all know the core challenge of GenAI: it’s powerful, but prone to hallucinations, omissions, and inconsistent outputs. These issues can seriously hinder adoption, especially in high-volume, customer-facing applications. 🔍 Amazon’s Catalog AI, a GenAI-based system designed to tackle the complexity of its massive product catalog. It detects and blocks unreliable data, produces ideas for new product pages and tests their effectiveness and improves itself automatically using feedback, quality checks, and experiments. 💡 What’s fascinating is how Amazon replaced traditional ML models with LLMs trained on large datasets across product categories. This simplified their tech infrastructure (fewer models), streamlined the organization (fewer functional specialists), and reduced costs. 🛠️ The system is built on a four-step quality control framework: 1️⃣ Audit the system 2️⃣ Deploy guardrails – using simple rules, statistical profiles, and even AI to check AI 3️⃣ Test effectiveness 4️⃣ Create a learning system – with customer models, multivariate experiments, and concept checks 🔁 And here’s the strategic insight: once these quality systems are in place, they do more than manage GenAI output—they help direct resources to the AI projects with the highest ROI. This is a great example of how product teams can use AI as a strategic capability, not just a feature. Scaling intelligently while keeping quality in check. Do you want to hear more? Online version in this link https://lnkd.in/dY9rY6ei #GenAI #AIstrategy #ProductManagement #LearningMindset #HBR #Amazon #CatalogAI #AIQuality #TechAndBooks #LLMs #InnovationAtScale

In today’s tech-driven world, understanding AI isn’t optional, it’s essential. The AI-900 Microsoft Certification gives engineers like us a solid foundation in AI concepts, machine learning, and Azure services. Whether you're in support, development, or operations, this certification helps you: ✅ Speak the language of AI. ✅ Collaborate across intelligent systems. ✅ Stay ahead in a rapidly evolving industry. Nice to be part of the AI movement. If you're thinking about leveling up your skills, AI-900 is a great place to start. 💡 #AI900 #MicrosoftCertified #AzureAI #TechSupportEngineer #AIReady #CareerGrowth #AIFirst

Discover the evolving landscape of agentic AI for the public sector with PwC new thought leadership paper, co-authored with Microsoft. Learn how Agentic AI is reshaping government, education, and defense—driving efficiency, innovation, and citizen-centric services. Read more and see how PwC and Microsoft are leading the way: https://msft.it/6042sllda

AI work in SUPPLY CHAIN MGT machine learning to pioneer algorithmic carrier pricing, which ensures that carriers receive upfront guaranteed pricing for trucking and freight. “By looking at hundreds of different parameters, we’ve been able to make [this model] accurate enough to introduce a marketplace that is now removed of all the friction, guessing, and back-and-forths [of] trying to estimate the price of trucking,” Ron said." /how-artificial-intelligence-transforming-logistics#:~ "typically use operations research and human problem-solving to minimize the time, cost, and distance of trucking and freight. On a larger scale, with more complicated routes and additional factors, operations research and human problem-solving no longer suffice. " /how-artificial-intelligence-transforming-logistics#:~ "

Discover the evolving landscape of agentic AI for the public sector with PwC new thought leadership paper, co-authored with Microsoft. Learn how Agentic AI is reshaping government, education, and defense—driving efficiency, innovation, and citizen-centric services. Read more and see how PwC and Microsoft are leading the way: https://msft.it/6048sllY6

Discover the evolving landscape of agentic AI for the public sector with PwC new thought leadership paper, co-authored with Microsoft. Learn how Agentic AI is reshaping government, education, and defense—driving efficiency, innovation, and citizen-centric services. Read more and see how PwC and Microsoft are leading the way: https://msft.it/6049soJRl