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Quality inspection in manufacturing powered by Axelera AI. Effective. Efficient. Scalable.

🚀 Powering Industries with Cutting-Edge AI - Axelera AI Leads the Charge 🌍 At Axelera AI, we're revolutionizing quality control in manufacturing with our advanced AI-driven vision inspection systems. Our unique In-Memory Architecture and Metis Platform provide unparalleled accuracy and speed in defect detection, seamlessly integrating with existing manufacturing systems. This ensures that manufacturers stay ahead of the curve, driving innovation and operational excellence. As Europe pushes forward in AI and industrial automation, Axelera AI is a critical player in the ecosystem. We’re strengthening Europe’s position in the global AI landscape. Together, we can build a stronger, more resilient industrial base that sets new standards for quality and sustainability. #AI #Manufacturing #QualityControl #Innovation #Europe

With the increment of AI applications, it’s important to consider the implications of its use for safety applications, like in the automotive industry. While looking for some solutions and recommendations I found an interesting paper focused on Machine Learning and the hashtag #ISO26262, "𝐀𝐧 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬 𝐨𝐟 𝐈𝐒𝐎 𝟐𝟔𝟐𝟔𝟐: 𝐔𝐬𝐢𝐧𝐠 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐒𝐚𝐟𝐞𝐥𝐲 𝐢𝐧 𝐀𝐮𝐭𝐨𝐦𝐨𝐭𝐢𝐯𝐞 𝐒𝐨𝐟𝐭𝐰𝐚𝐫𝐞," authored by Rick Salay, Rodrigo Queiroz, and Krzysztof Czarnecki from the University of Waterloo. They give some recommendations on adapting ISO 26262 to better accommodate ML, focusing on: 1. Identifying new types of hazards introduced by ML. 2. Understanding faults and failure modes specific to ML. 3. The importance of using comprehensive training sets. 4. Addressing non-transparency and error rates in ML models. 5. Ensuring robustness in ML-based systems. 🔷 What are your thoughts on the recommendations provided in this paper? 🔷 Do you use some hashtag #ML or #AI in your automotive SW? How do you ensure it’s in line with ISO26262? Post credit Pablo Bartolome Molina #AutomotiveSafety #MachineLearning #ArtificialIntelligence #ADAS #AutonomousVehicles #SafetyStandards #Innovation #AutomotiveIndustry #SWDevelopment

It's such a fascinating expanding frontier using machine learning, AI and robotics to deliver enhanced personalized customer service. What critiera would it have to meet? Standards? New laws? What sub-fields will be created with emerging budding innovation and technology? Efficiency vs Cost? Customer awareness? How steep is the customer learning curve? New customers? Pain points? So many questions... https://lnkd.in/gZj4sPGm

Take our quiz and discover how AI is pioneering the future of smart manufacturing. Manufacturers can earn one hour of free engineering services for AI integration by being the top scorers. Let's get started! →

False positives are a major bugbear in automotive manufacturing, leading to wasted time, resources, and money. The limited accuracy and shortcomings of machine learning technology accelerate false positive challenges. Now, say goodbye to costly recalls and production setbacks with the Visual Inspection AI model. This AI model is capable of accumulating an adequate amount of data from the line of inspection and training the model accordingly, allowing manufacturers to conduct predictive analysis and error-free production.  Catch more insight in our article on the role of visual inspection AI in reducing false positive rates. https://lnkd.in/gQ7zsTVE #manufacturing #machinelearning #visualinspection #computervision #qualityassurance #qualityinspection #manufacturingindustry #startmanufacturing #qualitycontrol #AImachinelearning #deeplearning #lincode

False positives are a major bugbear in automotive manufacturing, leading to wasted time, resources, and money. The limited accuracy and shortcomings of machine learning technology accelerate false positive challenges. Now, say goodbye to costly recalls and production setbacks with the Visual Inspection AI model.  This AI model is capable of accumulating an adequate amount of data from the line of inspection and training the model accordingly, allowing manufacturers to conduct predictive analysis and error-free production.  Catch more insight in our article on the role of visual inspection AI in reducing false positive rates.  https://lnkd.in/gQ7zsTVE #manufacturing #machinelearning #visualinspection #computervision #qualityassurance #qualityinspection #manufacturingindustry #startmanufacturing #qualitycontrol #AImachinelearning #deeplearning #lincode

Artificial Intelligence and Machine Learning have significantly simplified the creation of autonomous systems. Their influence on product development is anticipated to be equally profound. In our upcoming Webinar, Industry leaders and Ansys experts will share insights on how AI/ML has already influenced their product development processes while guiding you in leveraging these technologies to enhance engineering design. Please register to attend the webinar. https://ansys.me/3x8Griv

Great words from Pablo Bartolomé Molina about how to integrate Machine Learning in critical applications (ISO 26262, Autosar, MLAB, ASIL-D). Research is mandatory in the automotive industry to plan your roadmap for the next years and gain a competitive advantage over your competitors in the market. Don't put off until tomorrow what you can start researching today 😉. #softwareintegration #iso26262 #machinelearning

🚀 Leveraging Advanced Analytics and AI in Manufacturing →Predictive Maintenance: AI-powered models analyze sensor data to predict equipment failures, saving time and costs. →Quality Control: Machine learning algorithms detect defects early, improving product quality. →Supply Chain Optimization: AI helps manage inventory and demand forecasting, reducing waste. As AI continues to evolve, we can expect more breakthroughs in automation, smarter data-driven decisions, and a stronger, more agile manufacturing landscape. 🌟 #AI #Manufacturing #DataAnalytics #Innovation #Industry40 #PredictiveMaintenance