Spacio’s Post

⏱ The "operational digital twin" is not just a building map or fancy CAD program, but rather a virtualization of the operations and workflows happening inside a building in real-time.   🤖 Organizations are realizing the importance of "AI first" approach, where AI and rational agents are a foundational part of the digital twin. The AI is given the problem, inputs, and provides the solution, replacing traditional software engineering processes.   🕵️ Rational agents provide the architecture to do this for our digital twin. With rational agents we model and automate decision-making workflows based on desired outcomes, perceiving the environment, thinking through options, and acting on the optimal choice.   📍Location sensing of people/assets is key for the rational agents' perception step to make informed decisions in the digital twin environment.   📖 We should be learning about these architectures before we learn about algorithms. Customers who understand this "AI first" architectural approach will shape the future of these intelligent digital twin systems.   📈 If we focus on providing AI with rich data resources from the digital twin model, we will enable it to focus on optimal decision-making rather than low-level tasks. Let’s build one together! Book time on my calendar. https://lnkd.in/guxHrdMJ #LBS #AI #SmartBuildings #DigitalTwin #Innovation #WhyWhereMatters #FutureOfWork #LocationBasedServices https://lnkd.in/gS8fKqaT

Everyone is talking about RAG (Retrieval-Augmented Generation) and we know it helps prevent LLM hallucinations, but that's just the tip of the iceberg. Check out this enterprise architecture guide on effective RAG strategies for LLM applications and services. https://lnkd.in/gChdzHSW

>🎙️ Today, at 5 pm CET, let’s talk about 𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝘁𝗹𝘆 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗻𝗴 𝗥𝗔𝗚 and 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗚𝗿𝗮𝗽𝗵𝘀 to enhance the quality of GenAI solutions! Join my colleague, Irina Adamchic, PhD for a live session hosted by Neo4j. Irina will introduce her innovative 𝗧𝗵𝗿𝗲𝗲-𝗟𝗮𝘆𝗲𝗿 𝗙𝗶𝘅𝗲𝗱 𝗘𝗻𝘁𝗶𝘁𝘆 Architecture, designed to: - enhance data retrieval, - improve contextual understanding, and - reduce computational costs. The architecture organizes RAG workflows into: 🔹 Input Layer: Data ingestion. 🔹 Middle Layer: Knowledge graph representation and reasoning. 🔹 Output Layer: AI-driven, contextually accurate results. 📅 When: 22nd January at 5 PM CET 📍 Where: Live on YouTube 🔗 More details: Irina's Article on Medium: https://lnkd.in/epYguVBj Don’t miss this insightful session 😉 https://lnkd.in/ePqWuPFB #AI #KnowledgeGraphs #GenerativeAI #Neo4j #RAG Kathrin Schwan | Claudia Leischner | Dr. Dirk Alexander Molitor | Reyhan Merekar | Tobias Abt | Felix Klemm | Igor Aranovsky | Dominik Krimpmann, PhD

RAG is a major buzzword in the GenAI space, but it's only an approach. Read this guide to differentiate between basic vs. advanced RAG strategies and how they impact the business context and content you give to LLMs!

Interesting insights into AI and Architecture but the value of what we do is still in the thinking process. At the moment AI is only helping us to save some time.

🌟 Thrilled to share our latest article: Unlocking Business Potential with AI: A Journey from Concept to Cutting-Edge Solutions! AI is more than a tech trend—it’s a game-changer reshaping industries and driving growth. 🚀 In this piece, we explore: 🔍 The transformative impact of AI on businesses 📈 Key steps to move from idea to real-world implementation 🌐 Inspiring examples of AI solutions in action Ready to uncover new possibilities for your business? Dive into the article here: https://lnkd.in/ePycd35q Let’s keep the conversation going! I’d love to hear your thoughts or discuss how AI can empower your projects. #ArtificialIntelligence #Innovation #BusinessGrowth #Technology

Time Series forecasting is a use case that is a staple in many businesses. By being able to forecast the business needs, we can gain a competitive advantage. There are many ways for time-series forecasting, but it often involves a lot of data collection and understanding. That's why Chronos is giving a fresh take on time series forecasting by using LLM. The model's architecture relies on LLM,which allows it to use zero-shot capability. This means we don't need to train the model much. So, how does Chronos work? Read it all in my latest article!

I find this white paper by Google on what AI agents are and the details of the information provided on the overall architecture brilliantly awesome. Reading this whitepaper, you will never confuse the difference between what a model (e.g., LLM models) is and what an AI agent really is. But the struggle I keep having in tech in general is how terminologies and concepts are sometimes scarier than what the meanings of those words are. One of those is the concept used—cognitive architecture.

The unprecedented risks of GenAI are naturally causing uncertainty for organisations that want to harness its vast potential. Oliver Cronk’s white paper, 'How to de-risk GenAI across your enterprise', delves deeper into the business and tech risks of generative AI, providing a simple overview of a software architecture that can significantly reduce them. Download your copy: https://buff.ly/3yRkxRA #GenAI #AISecurity #AIArchitecture

Last Tuesday I showcased how you can use LLMs for designing and diagramming the software solutions within G2i community. We covered the usage of local models and ChatGPT for creating beautiful diagrams. Find the recording below. But if you really like this demo, I have a 2 hour workshop about using AI for better architecture decisions. All the details can be found here: https://lnkd.in/geEy_ipA https://lnkd.in/dnaDREjD