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Generative AI in Manufacturing 🤔 AI is the buzz right now in all industries, including manufacturing But does Generative AI... Does this have a space in manufacturing? Generative AI enables prompts to create outputs like text, code, images, animations, etc. This space is growing at an alarming rate... for good reason. Generative AI is a great tool to enhance existing workflows while providing entirely new ways of doing things. I use tools like ChatGPT and Midjourney for many different reasons/ tasks... But this is outside the manufacturing space. What can/is Generative AI bringing to manufacturing... IMO there are a few things today, in the mid-future, and the long-term future. Today Generative AI can: * Serve as a knowledge resource for service & maintenance data * Help in the development of code for manufacturing applications (Note: this is to augment knowledgeable programmers, not to replace programmers) * The first steps of modeling can be used for product development This is the "𝐢𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐯𝐞 𝐬𝐭𝐚𝐠𝐞," providing information that exists in an easy-to-use way. Mid-future Generative AI can: * 3D models can be generated; in the future, can service parts be produced * Data can be further refined into meaningful information in new and innovative ways * More advanced modeling of systems and processes changing dependencies This is the "𝐢𝐦𝐩𝐫𝐨𝐯𝐞𝐦𝐞𝐧𝐭 𝐬𝐭𝐚𝐠𝐞," where generative AI can make meaningful changes to improve uptime and operations. Long-term Future Generative AI can: * Layout facilities optimizing for production flows * Provide insight into data through natural language to diagnose, enhance, and predict change * Machines, systems, and processes can be queried at great depth to look into performance, operations, and more This is the "𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐯𝐞 𝐬𝐭𝐚𝐠𝐞," where the models have enough training and knowledge to look forward based on data, trends, and information to provide guidance to enhance future operations and design Beyond this stage is the complete modeling of the factory, operations, production flow, and more to virtualize its use. What are your thoughts on the use of Generative AI in manufacturing? #ai #manufacturing #maintenance

AI is a hot topic in all industries, including manufacturing There are 3 levels of Generative AI: Informative stage, Improvement stage, & Predictive stage What place does Generative AI have a space in manufacturing? Generative AI enables prompts to create outputs like text, code, images, animations, etc. This space is growing at an alarming rate... for good reason. Generative AI is a great tool to enhance existing workflows while providing entirely new ways of doing things. I use tools like ChatGPT and Midjourney for many different reasons/ tasks... But this is outside the manufacturing space. What can/is Generative AI bringing to manufacturing... IMO there are a few things today, in the mid-future, and the long-term future. Today Generative AI can: * Serve as a knowledge resource for service & maintenance data * Help in the development of code for manufacturing applications (Note: this is to augment knowledgeable programmers, not to replace programmers) * The first steps of modeling can be used for product development This is the "𝐢𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐯𝐞 𝐬𝐭𝐚𝐠𝐞," providing information that exists in an easy-to-use way. Mid-future Generative AI can: * 3D models can be generated; in the future, can service parts be produced * Data can be further refined into meaningful information in new and innovative ways * More advanced modeling of systems and processes changing dependencies This is the "𝐢𝐦𝐩𝐫𝐨𝐯𝐞𝐦𝐞𝐧𝐭 𝐬𝐭𝐚𝐠𝐞," where generative AI can make meaningful changes to improve uptime and operations. Long-term Future Generative AI can: * Layout facilities optimizing for production flows * Provide insight into data through natural language to diagnose, enhance, and predict change * Machines, systems, and processes can be queried at great depth to look into performance, operations, and more This is the "𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐯𝐞 𝐬𝐭𝐚𝐠𝐞," where the models have enough training and knowledge to look forward based on data, trends, and information to provide guidance to enhance future operations and design Beyond this stage is the "Star Level" complete modeling of the factory, operations, production flow, and more to virtualize its use. What are your thoughts on the stages of Generative AI in manufacturing?

Harness AI ‘s Creative Power to Drive Innovation https://ift.tt/rEDhkf9 Harness AI’s Creative Power to Drive Innovation: Learn & Leverage AI to bring paradigm shift to transform the businesses   Introduction Welcome to the future of innovation! ARCCHIE PUBLICATIONS proudly presents our latest book, Harness AI’s Creative Power to Drive Innovation: Learn & Leverage AI to Bring a Paradigm Shift to Transform Businesses. Authored by Aishwarya Gupta, Joseph Bulger, and Gaurav Aroraa, this comprehensive guide is an essential resource for anyone looking to understand and utilize Generative AI to revolutionize their field. Discover the Potential of Generative AI Generative AI, a subset of artificial intelligence, has the unique ability to create new content from existing data. This transformative technology is reshaping industries and driving unprecedented levels of innovation. Our book takes readers on a journey through the exciting world of Generative AI, demystifying complex concepts and providing practical insights that can be applied across various sectors. Real-World Applications of Generative AI Generative AI is not just a futuristic concept—it has tangible, real-time applications that are already making a significant impact in numerous industries. Here are some ways Generative AI is revolutionizing the world: Healthcare: In the medical field, Generative AI is making strides by generating synthetic medical images that assist doctors in diagnosing and planning treatments more accurately. This technology also plays a crucial role in drug discovery and personalized medicine. Entertainment: The entertainment industry benefits from AI-driven interactive storytelling, which creates personalized experiences for users. From video games to virtual reality environments, Generative AI enhances the creative process, offering new ways to engage audiences. Automotive: In the automotive sector, Generative AI is used to simulate real-world scenarios, improving the development and safety testing of autonomous vehicles. This technology helps manufacturers design more efficient and safer cars. Retail: Retailers are leveraging Generative AI to offer personalized shopping experiences, such as virtual try-ons for clothing and accessories. This not only enhances customer satisfaction but also drives sales and reduces returns. Finance: In finance, Generative AI aids in fraud detection by recognizing unusual patterns and behaviors. This technology helps financial institutions protect their customers and ensure the integrity of transactions. Creativity and Design: Generative AI is a powerful tool for creativity, driving design iterations in fields like architecture and fashion. Designers can explore countless possibilities and bring innovative concepts to life with the help of AI. Who Should Read This Book? Our book is designed for a wide audience, ensuring that anyone with an interest in Artificial Intelligence can benefit from its insights: Novice ...

Use your world as a prompt to your Generative AI model 🌍 🤖 The future of Generative Augmented Reality - GenAR 👇 Generative AI is changing the way we experience virtual and augmented realities, making them more interactive and lifelike. This technology is making it easier for us to blend our real and digital worlds in ways that are more engaging and personal. As Generative AI keeps improving, it will play a bigger role in our daily activities, offering new and exciting ways to learn and experience the world. It will assist people on professional and personal life, in work or home, from supporting on installing equipment to teach cooking... But, it's important to remember that there are still challenges and ethical issues to think about as we move forward with these advanced technologies. What developments I´m expecting that will bring Generative AR to another level: Advancements on TEXT-to-3D: -       TEXT-to-3D/AR tech advances significantly enhance 3D model generation quality and scope. -       Text-to-3D transforms written descriptions into detailed 3D models, using AI to interpret and visualize text input as realistic 3D objects. Multimodal Models with Video: -       Multimodal models integrating video redefine AI's interaction with dynamic, real-world environments. -       Video data enhances AI's contextual understanding, leading to richer, more nuanced outputs. - OpenAI's GPT-5 aspires video input/output, expanding AI's data processing capabilities. Your Thoughts ❔ What developments in Generative AR excite you the most? How do you envision these technologies impacting your professional or personal life? Video Credits: Microsoft - Copilot + Dynamics 365 #generativeai #augmentedreality #futureofwork

Future-Proofing the Past: AI’s Role in Protecting Cultural Legacies https://lnkd.in/dYuT9pkH The Power of AI in Protecting Cultural Heritage Cultural heritage around the world is under threat from conflicts and natural disasters. This puts ancient sites and artifacts at risk. AI provides advanced tools to document, analyze, and protect this heritage. It offers practical solutions to reduce these risks and ensure preservation for future generations. AI Solutions for Heritage Preservation AI technologies like text-to-image systems, 3D and 2D modeling tools, generative adversarial networks (GANs), and machine learning algorithms are revolutionizing the preservation and reconstruction of cultural heritage. These advancements enable the creation of detailed digital replicas, improve visualization accuracy, and provide crucial spatial data for protecting and digitally restoring heritage sites. Novel AI-Driven Reconstruction Method A research team has proposed a method using AI-driven text-to-image generation to reconstruct damaged heritage sites. By using detailed textual descriptions from historical sources, they create accurate visual representations, linking historical documentation with advanced AI capabilities. Methodology and Evaluation The research team collected textual descriptions and historical records, converted them into visual reconstructions using AI platforms, and rigorously evaluated the accuracy and fidelity of the AI-generated images against historical benchmarks. Real-world scenarios and collaboration with experts confirmed AI’s ability to faithfully depict historical details and architectural remains. AI’s Role in Cultural Heritage Preservation The study demonstrates AI’s potential in preserving cultural heritage through accurate digital reconstructions. Integrating AI with traditional methods offers a balanced approach to conserving and revitalizing cultural legacies, promising broader accessibility and educational opportunities. Evolve Your Company with AI Discover how AI can redefine your way of work, identify automation opportunities, define KPIs, select an AI solution, and implement gradually. For AI KPI management advice and insights into leveraging AI, connect with us at hello@itinai.com or visit our website. #AIheritage #CulturalPreservation #MachineLearning #HeritageReconstruction #FutureOfWork #productmanagement #ai #ainews #llm #ml #startup #innovation #uxproduct #artificialintelligence #machinelearning #technology #ux #datascience #deeplearning #tech #robotics #aimarketing #bigdata #computerscience #aibusiness #automation #aitransformation

"Transforming Industries: The Expansive Reach of Generative AI" The revolution brought by Generative AI is not confined to a single sector. It’s rippling across diverse industries, reshaping operations, products, and services. Here's how: 1. Healthcare: Generative models are becoming indispensable. Consider the case of *DeepMind's AlphaFold*, which predicts protein folding, potentially revolutionizing drug discovery and disease understanding. On another front, AI-generated medical imaging allows for the creation of detailed, realistic images, enabling better training for medical professionals without exposing patients to unnecessary scans. 2. Fashion & Retail: Brands like *Stitch Fix* employ algorithms to tailor fashion choices to individual preferences. Now, envision this process being enhanced by generative AI, creating unique designs inspired by personal style histories, or even mood predictions. 3. Entertainment & Media: Movies like *“Sunspring”* are scripted using AI, and artists like *Taryn Southern* have albums composed with the assistance of AI tools. This heralds a new era where man and machine collaborate to create art, leading to outputs we hadn't previously imagined. 4. Architecture & Urban Planning: *Autodesk's generative design tool* evaluates thousands of design options by setting parameters, leading to efficient, sustainable, and innovative architectural solutions. Imagine cities planned with optimized traffic flow, sunlight exposure, and green spaces, all proposed by AI. 5. Automotive & Manufacturing: Car manufacturers like *General Motors* have been leveraging generative design to optimize parts, making them lighter yet durable. In manufacturing, AI can predictively design assembly lines, balancing efficiency with worker safety. 6. Finance: Banks like *JP Morgan* utilize AI to simulate millions of trading days within minutes to prepare for potential economic shocks. Such simulations by generative models allow for proactive strategies, minimizing financial risks. 7. Agriculture: With a tool like *IBM’s Watson Decision Platform for Agriculture*, generative models can forecast crop yields and recommend planting strategies, maximizing output while accounting for changing weather patterns and soil health. In essence, generative AI is not just about mimicking existing processes but redefining them. It's about creating something new, unique, and, often, better than what humans could achieve alone. As this technology continues to mature, its capacity to revolutionize industries will only magnify. Businesses and professionals must, therefore, stay attuned, embracing the change and capitalizing on the unprecedented opportunities it presents. The future is generative, and it beckons with promise. #GenerativeAI #TransformationAcrossSectors #EmbracingTheFuture

This AI Paper Introduces Rational Transfer Function: Advancing Sequence Modeling with FFT Techniques https://lnkd.in/dXN-8zth State-space models (SSMs) are important in deep learning for modeling sequences, but they face challenges with memory and computational costs. This limits their performance in large-scale applications. Recent advancements have introduced practical solutions to address these challenges. Frameworks like S4, S4D, Hyena, and Liquid-S4, along with FFT-based methods and transformers, have significantly improved the efficiency and capability of sequence modeling. One notable approach is the Rational Transfer Function (RTF) method, which uses transfer functions for efficient sequence modeling. This method improves computational speed and scalability in parallel inference using FFT. The RTF model has demonstrated significant improvements in training speed and accuracy across various benchmarks, offering an efficient solution for scalable and effective sequence modeling. In the realm of AI solutions for business, it's important to identify automation opportunities, define KPIs, select an AI solution, and implement gradually. For AI KPI management advice and continuous insights into leveraging AI, you can connect with us at hello@itinai.com or stay tuned on our Telegram or Twitter channels. One practical AI solution is the AI Sales Bot from itinai.com/aisalesbot, designed to automate customer engagement 24/7 and manage interactions across all customer journey stages. For free consultation, you can join our AI Lab in Telegram @itinai, and for updates, follow us on Twitter @itinaicom. #productmanagement #ai #ainews #llm #ml #startup #innovation #uxproduct #artificialintelligence #machinelearning #technology #ux #datascience #deeplearning #tech #robotics #aimarketing #bigdata #computerscience #aibusiness #automation #aitransformation

Tsinghua University Researchers Propose V3D: A Novel Artificial Intelligence Method for Generating Consistent Multi-View Images with Image-to-Video Diffusion Models https://lnkd.in/dTAX-QDB Subject: Revolutionizing 3D Content Creation with V3D AI Method Dear Middle Managers, The digital landscape is rapidly evolving, and one of the most dynamic areas is 3D content creation. The introduction of automatic 3D generation technologies has transformed this sphere, making 3D content creation accessible to creators with varying levels of expertise. The Challenge: Creating detailed and complex 3D objects swiftly has always been a challenge. Previous techniques often struggled to balance detail with time efficiency, resulting in laborious processes and models that needed more detail despite considerable computational resources and time. The Solution: V3D Researchers at Tsinghua University and ShengShu have introduced V3D, a breakthrough approach that leverages video diffusion models to produce intricate 3D models with unprecedented detail and fidelity in record time. This method significantly reduces the time required for 3D model generation from hours to minutes, offering a faster, more efficient, and detail-oriented approach to model creation. Key Aspects of V3D: - Enables rapid production of detailed 3D models - Generates multi-view images as a video sequence for 3D model creation - Ensures coherent reconstruction of 3D models from generated images - Produces high-quality 3D meshes or Gaussians in a significantly reduced time frame - Enhances digital experiences with detailed and consistent imaging through object-centric generation and scene-level view synthesis Practical AI Solutions for Middle Managers: If you are looking to evolve your company with AI, consider how AI can redefine your way of work. Identify Automation Opportunities, Define KPIs, Select an AI Solution, and Implement Gradually. For AI KPI management advice, connect with us at hello@itinai.com. Spotlight on a Practical AI Solution: Consider the AI Sales Bot from itinai.com/aisalesbot, designed to automate customer engagement 24/7 and manage interactions across all customer journey stages. For continuous insights into leveraging AI, stay tuned on our Telegram or Twitter. For more information, you can also check out the Paper and Github. Best regards, [Your Name] AI Solutions Representative AI News, Adnan Hassan, AI, AI tools, Innovation, itinai.com, LLM, MarkTechPost, t.me/itinai

Instead of method 1, or method 2, or method 3, can Generative AI enrich the “flexible design” decision making. Can the creative process be “and” vs “or?” #JUSTasking

Intelligent Automation Trends 2024 📈 As we navigate the rapidly evolving landscape of technology, several trends are shaping the future of intelligent automation. Here are three key trends to watch in 2024: 1.- Robotic Process Automation (RPA): RPA continues to revolutionize business processes by leveraging software robots to automate repetitive tasks. These bots mimic human actions, such as data entry and form filling, streamlining workflows and reducing errors. In 2024, we expect to see RPA adoption soar as organizations strive to enhance efficiency and productivity. 💻 2.- Artificial Intelligence (AI): AI is driving innovation across industries, with applications ranging from virtual assistants to autonomous vehicles. Machine learning, natural language processing, and computer vision are just a few examples of AI technologies that are transforming business operations. In 2024, we anticipate AI becoming even more pervasive, enabling organizations to make smarter decisions and deliver more personalized experiences. 🤖 3.- Generative AI: Generative AI is a subset of AI that focuses on creating new and original content. Models like GANs are capable of generating realistic images, human-like text, and other forms of creative content. In 2024, we expect to see generative AI being used in new and exciting ways, such as in content creation, design, and even in the development of new products. 💹 These technologies are increasingly being integrated to create intelligent automation solutions that not only automate repetitive tasks but also have the ability to make decisions and learn from data. As we look ahead to 2024, it's clear that intelligent automation will continue to drive innovation and transform the way we work. Are you using these technologies in your organization? ⁉ #IntelligentAutomation #RPA #AI #GenerativeAI #AutomationTrends #FutureTech #Innovation2024 #DigitalTransformation