Innovations Driven by AI in Products

🍪 AI Meets Snacks: The Future of Your Favorite Munchies 🍪 In a world where artificial intelligence is revolutionizing industries left and right, even your beloved Oreos aren't immune to the tech transformation. Mondelez International, the snack giant behind iconic brands like Oreo and Ritz, is embracing AI to reimagine classic treats while staying true to their timeless appeal. 🤖 Flavor Innovation Unleashed: AI algorithms are now the secret ingredient in Mondelez's recipe for success. These smart systems tirelessly analyze vast amounts of consumer feedback, social media trends, and market data to inspire new, exciting flavors and textures that resonate with snack enthusiasts worldwide. It's like having a tireless R&D team working 24/7 to create the next viral sensation in the snack aisle. 🧠 Perfecting the Crunch: Machine learning algorithms are becoming the ultimate taste testers, helping to optimize recipes for consistent quality across global production lines. These AI systems can detect subtle variations in ingredients and processing conditions, ensuring that every Oreo twist and Ritz cracker delivers the same satisfying crunch, no matter where it's made. 📊 Crystal Ball for Cravings: Predictive AI models are transforming Mondelez's supply chain, acting as a crystal ball for snack cravings. By forecasting demand with unprecedented accuracy, these systems help reduce waste, optimize inventory, and ensure your favorite treats are always in stock when the munchies strike. 🌿 Eco-Friendly Packaging Revolution: AI is not just about taste; it's also helping Mondelez tackle sustainability challenges. Advanced algorithms assist in developing innovative, eco-friendly packaging solutions, analyzing materials for durability, recyclability, and environmental impact. It's a delicious step towards guilt-free snacking, both for your taste buds and the planet. 👥 Human Touch in the Age of AI: While AI is revolutionizing snack development, Mondelez emphasizes that human expertise remains at the heart of their process. AI serves as a powerful tool to enhance, not replace, the creative minds behind our favorite treats. It's a perfect blend of artificial intelligence and human intuition, ensuring that while technology pushes boundaries, the soul of beloved snacks remains intact. #AIinSnacks #FoodInnovation #MondelezAI #FutureOfSnacking #TechMeetsTreats #SmartOreos #SustainableSnacking #AIFlavors #SnackTech #FoodTech

🔥12 Key Digital Health and Pharma Partnerships and Innovations This Month >> 💊AstraZeneca and Lunit Oncology are partnering to develop AI tools for faster Lung Cancer (NSCLC) diagnostics, starting with EGFR mutation prediction, aiming to streamline workflows and support precision medicine 💊 AstraZeneca and Qure.ai partner with the UAE’s Ministry of Health to advance early lung cancer detection using AI-powered tools and national guidelines, with similar initiatives underway in India, Thailand, and Malaysia 💊 Astellas Pharma and Desert Oasis Healthcare are piloting DIGITIVA™ for heart failure management that combines AI-driven insights, real-time monitoring, and personalized coaching to reduce acute events and hospital readmissions 💊 Sanofi and Healx collaborate using AI to identify new Rare Disease targets, leveraging Healx’s Healnet platform to analyze biological data and accelerate drug discovery for unmet needs 💊 Sanofi in collaboration with OpenAI and Formation Bio has introduced Muse, an AI tool to streamline patient recruitment for clinical trials by identifying ideal profiles, generating materials, and ensuring regulatory compliance 💊 Eli Lilly and Company’ new Digital Health Hub in Singapore leverages AI tools like Magnol.AI to advance drug discovery for Alzheimer’s, autoimmune diseases, and cancer, while supporting Phase 1 clinical trials and real-time monitoring 💊 GE HealthCare and DeepHealth (RadNet) are partnering to integrate AI tools for improved breast cancer screening, using solutions like SmartMammo and Smart Alerts to enhance accuracy, streamline workflows, and enable same-day diagnostics 💊 GE HealthCare launches AI Innovation Lab to accelerate early-concept AI innovations within the company, focusing on integrating AI into medical devices and enhancing decision-making across the care journey 💊 Daewoong Pharmaceutical partners with Revvity Signals to digitize its drug development systems, aiming to reduce decision-making time and lower experimental data error rates 💊 TEVOGEN BIO partners with Microsoft to develop targeted HPV cancer treatments by leveraging AI to train immune cells to destroy infected cells, aiming for faster, cost-effective therapies with improved outcomes 💊 Novo Nordisk and Thermo Fisher Scientific are partnering to build a state of the art manufacturing facility in Denmark, advancing scalable cell therapies for chronic diseases like diabetes and Parkinson’s, while enhancing production efficiency and innovation 💊 Dario Health partners with a top U.S. pharma company to enhance patient engagement and monitor outcomes for a new psoriasis drug, leveraging a subscription model and data tracking 👇 Link to source articles in comments #digitalhealth #ai #pharma

AI is rapidly transforming the auto manufacturing industry in several key areas, enhancing efficiency, safety, and innovation. Here are some of the top trends in AI within the automotive manufacturing space I have learned from Helen Yu and Chuck Brooks: 1. Smart Manufacturing with AI Predictive Maintenance: AI-powered systems can predict when machinery is likely to fail, reducing downtime and maintenance costs. Sensors and machine learning models help predict equipment failure, allowing manufacturers to schedule repairs before problems arise. AI-Driven Quality Control: Computer vision and deep learning are used for real-time defect detection, ensuring that every part meets quality standards. AI systems can identify minute defects in materials, welds, and components that are often too small for human eyes. Robotics and Automation: Collaborative robots (cobots) work alongside human workers, performing repetitive tasks like assembly, painting, and welding. These robots use AI for flexibility, adapting to various tasks without the need for reprogramming. A great example here in Savannah, Georgia is at the Hyundai Motor Company (현대자동차) META plant. 2. AI in Design and Prototyping Generative Design: AI can assist in creating optimized designs for car parts and structures. Generative design algorithms analyze and generate thousands of design variations based on input parameters, optimizing for weight, strength, and cost. Virtual Prototyping: AI-powered simulation tools enable manufacturers to create and test prototypes virtually, speeding up the design cycle and reducing the cost of physical prototypes. This also allows for better performance testing before the first physical model is built. Best Regards, Professor Bill Stankiewicz, OSHA Trainer, Heavy Lift & Crane Instructor Savannah Technical College Subject Matter Expert International Logistics Member of Câmara Internacional de Logística e Transportes CIT - CIT at The International Transportation Industry Chamber

🔬 Revolutionizing Pharma with AI & Gen AI: Roche and Genentech Lead the Way 🚀 The pharmaceutical and biotech industries are undergoing a massive transformation, and Roche and Genentech are at the forefront of this revolution. By strategically integrating Artificial Intelligence (AI) and Generative AI (Gen AI) across their operations, these industry leaders are redefining innovation in drug discovery, manufacturing, diagnostics, and personalized medicine. 💡 What’s happening? Faster Drug Discovery: The "lab in a loop" approach uses AI to predict, test, and refine potential drug candidates, cutting down timelines significantly. AI is even helping design personalized cancer vaccines and combating drug-resistant bacteria! Smarter Manufacturing: AI-driven predictive models are improving manufacturing yields by up to 10% and reducing quality control issues by 50%. Advanced Diagnostics: AI-powered imaging and digital pathology are enhancing cancer detection and diagnostics, with up to 97% accuracy in certain use cases. Personalized Medicine: AI is uncovering key biomarkers, enabling more targeted treatments, and transforming how we approach patient care. 🤝 Key Partnerships Roche and Genentech are teaming up with leading tech innovators like NVIDIA, Recursion Pharmaceuticals, and Genesis Therapeutics to harness cutting-edge AI tools for drug discovery and beyond. 🌍 Global Trends in AI Generative AI is accelerating drug design, reducing costs by up to 50%. AI is optimizing clinical trials, improving patient recruitment, and cutting trial timelines by 70%. AI-driven supply chain tools are enhancing resilience and reducing waste. 📈 Future Impact Roche and Genentech’s AI initiatives promise: ✅ Faster drug discovery and development. ✅ Enhanced precision medicine for better patient outcomes. ✅ Greater operational efficiency across R&D and manufacturing. ⚠️ Challenges Ahead Of course, integrating AI isn’t without risks: data privacy concerns, algorithm bias, and regulatory hurdles require careful navigation. But Roche and Genentech are leading with responsible AI practices, ensuring transparency, fairness, and compliance with evolving global regulations. 🌟 The Takeaway AI and Gen AI aren’t just tools—they’re transformational forces reshaping healthcare. Roche and Genentech are proving that by embracing innovation, the future of medicine can be faster, smarter, and more personalized than ever before. 💬 What are your thoughts on the role of AI in healthcare innovation? Let’s discuss in the comments! #PharmaInnovation #ArtificialIntelligence #GenerativeAI #HealthcareTransformation #Roche #Genentech #AIinHealthcare #DrugDiscovery #DigitalTransformation

AI is no longer just an experimentation tool. It’s reshaping the entire optimization landscape. With this shift comes many untapped opportunities. Working with Andrius Jonaitis ⚙️, we've put together a growing list of 40+ AI-driven experimentation tools ( https://lnkd.in/gHm2CbDi) Combing through this list, here are the emerging market trends and opportunities you should know: 1️⃣ SELF-LEARNING, AUTO-OPTIMIZING EXPERIMENTS 💡 Opportunity: AI is creating self-adjusting experiments that optimize in real-time. 🛠️ Tools: Amplitude, Evolv Technology, and Dynamic Yield by Mastercard are pioneering always-on experimentation, where AI adjusts experiences dynamically based on live behavior. 🔮 How to leverage it: Focus on learning and developing tools that shift from static A/B testing to AI-powered, dynamically updating experiments. 2️⃣ AI-GENERATED VARIANTS 💡 Opportunity: AI can help you develop hypotheses and testing strategies. 🛠️ Tools: Ditto and ChatGPT (through custom GPTs) can help you generate robust testing strategies. 🔮 How to leverage it: Use custom GPTs to generate test ideas at scale. Automate hypothesis development, ideation, and test planning. 3️⃣ SMARTER EXPERIMENTATION WITH LESS TRAFFIC 💡 Opportunity: AI-driven traffic-efficient testing that gets results without massive sample sizes. 🛠️ Tools: Intelligems, CustomFit AI, and CRO Benchmark are pioneering AI-driven uplift modeling, finding winners faster -- with less traffic waste. 🔮 How to leverage it: Don't get stuck in a mentality that testing is only for enterprise organizations with tons of traffic. Try tools that let you test more and faster through real-time adaptive insights. 4️⃣ AI-POWERED PERSONALIZATION 💡 Opportunity: AI is creating a whole new set of experiences where every visitor will see the best-performing variant for them. 🛠️ Tools: Lift AI, Bind AI, and Coveo are some of the leaders using real-time behavioral signals to personalize experiences dynamically. 🔮 How to leverage it: Experiment with tools that match users with high-converting content. These tools are likely to develop and get even more powerful moving forward. 5️⃣ AI EXPERIMENTATION AGENTS 💡 Opportunity: AI-driven autonomous agents that can run, monitor, and optimize experiments without human intervention. 🛠️ Tools: Conversion AgentAI and BotDojo are early signals of AI taking over manual experimentation execution. Julius AI and Jurnii LTD AI are moving toward full AI-driven decision-making. 🔮 How to leverage it: Be open-minded about your role in the experimentation process. It's changing! Start experimenting with tools that enable AI-powered execution. 💸 In the future, the biggest winners won’t be the experimenters running the most tests, they’ll be the ones versed enough to let AI do the testing for them. How do you see AI changing your role as en experimenter? Share below: ⬇️

“Clothes designed with AI outsold human-only ones by more than 2 to 1.”    That’s a compelling headline, but there’s a deeper story on how humans working with AI can drive innovation in luxury fashion.  Page Moreau, Emanuela Prandelli and Martin Schreier worked with luxury fashion house Missoni, digital co-creation platform AWAYTOMARS and IBM on a unique design experiment.  Here’s how it worked: Missoni fed hundreds of 𝘭𝘰𝘴𝘪𝘯𝘨 𝘦𝘯𝘵𝘳𝘪𝘦𝘴 from a crowdsourcing contest into an AI model. Then 𝘩𝘶𝘮𝘢𝘯 𝘥𝘦𝘴𝘪𝘨𝘯𝘦𝘳𝘴 created new pieces based on the AI’s output. These products went on to outsell the contest winners by a 2 to 1 margin. Here are my takeaways:  • 𝗥𝗲𝘁𝗵𝗶𝗻𝗸 𝘁𝗵𝗲 𝘃𝗮𝗹𝘂𝗲 𝗼𝗳 “𝗯𝗮𝗱” 𝗱𝗮𝘁𝗮. The losing designs provided a unique input for model training. What valuable data is your company discarding?    • 𝗕𝗿𝗶𝗻𝗴 𝗔𝗜 𝘂𝗽𝘀𝘁𝗿𝗲𝗮𝗺. Most businesses are harnessing AI for cost cutting, but it can drive innovation as well.  • 𝗛𝘂𝗺𝗮𝗻𝘀 + 𝗔𝗜: 𝗯𝗲𝘁𝘁𝗲𝗿 𝘁𝗼𝗴𝗲𝘁𝗵𝗲𝗿. This new process harnessed AI’s power and preserved Missoni’s brand identity. Research Credit: Page Moreau Wisconsin School of Business, Emanuela Prandelli Università Bocconi University and Martin Schreier WU (Vienna University of Economics and Business) #AI #FashionDesign #Creativity #HumanInTheLoop #WisconsinResearch #DesignThinking

Reading new report from BioAsia 2025 report from EY and Microsoft suggesting key trends that AI is reshaping drug discovery, clinical trials, manufacturing, diagnostics, and personalized medicine, driving efficiency, precision, and innovation. Key applications include predictive analytics, generative design, intelligent automation, and wearable technology, enabling breakthroughs in early disease detection, surgical robotics, and patient-specific treatments. AI's adoption is critical for competitiveness, with the global AI market in pharmaceuticals projected to reach $16.49 billion by 2034 and AI-powered medical devices expected to hit $97.1 billion by 2028. Challenges such as ethical concerns, data privacy, and talent shortages require strategic implementation across five pillars: business transformation, technology enhancement, data readiness, workforce preparation, and risk management. This repot also emphasizes AI maturity levels i.e foundational, innovative, and transformational and also the importance of scaling AI across enterprises. It showcases real-world examples of AI-driven advancements by companies like Pfizer, AstraZeneca, and GE Healthcare, and highlights India's contributions through initiatives like BharatGen and CRDMO Aurigene. Strategic alliances and M&A deals are accelerating AI integration, with over 300 AI-focused partnerships in life sciences from 2020-2024. #AI #LifeSciences #HealthcareInnovation #DrugDiscovery #MedTech #PersonalizedMedicine #ClinicalTrials #DigitalTransformation #ArtificialIntelligence #GenAI #Pharma #Biotech #DataGovernance #SurgicalRobotics #Diagnostics #FutureOfHealthcare Source:www.ey.com Disclaimer: The opinions are mine and not of employer's

𝐀𝐈 𝐚𝐧𝐝 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 𝐑𝐞𝐯𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐢𝐳𝐢𝐧𝐠 𝐌𝐚𝐧𝐮𝐟𝐚𝐜𝐭𝐮𝐫𝐢𝐧𝐠: 𝐖𝐡𝐚𝐭'𝐬 𝐍𝐞𝐰?  In today's rapidly evolving manufacturing landscape, AI and automation are at the forefront of transformative change. Recent studies highlight the increasing adoption of AI technologies within the industry, underscoring both opportunities and challenges. 👉𝐀𝐈 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐦𝐞𝐧𝐭𝐬 𝐢𝐧 𝐌𝐚𝐧𝐮𝐟𝐚𝐜𝐭𝐮𝐫𝐢𝐧𝐠 • AI is transforming the sector, with investment in generative AI expected to spike, adding $4.4 billion in revenue from 2026 to 2029 • 70% of manufacturers now use generative AI for discrete processes, particularly in computer-aided design (CAD), significantly boosting productivity • AI-powered predictive maintenance is reducing downtime, with companies like Pepsi and Colgate leveraging this technology to detect machinery problems early 👉𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧𝐬 • Collaborative robots (cobots) are gaining traction, with BMW and Ford utilizing them for tasks like welding and quality control • Amazon has deployed over 750,000 robots in its fulfillment centers, including the new Sequoia system that processes orders up to 25% faster • AI-driven "smart manufacturing" enables more precise process design and problem diagnosis through digital twin technology 👉𝐈𝐦𝐩𝐚𝐜𝐭 𝐨𝐧 𝐈𝐧𝐝𝐮𝐬𝐭𝐫𝐲 • AI is enabling "lights-out" factories, where production can continue 24/7 with minimal human intervention • Machine learning models are optimizing supply chains, enhancing resilience to volatility • AI-powered quality control systems are improving product consistency and reducing defects 👉𝐊𝐞𝐲 𝐒𝐭𝐚𝐭𝐢𝐬𝐭𝐢𝐜𝐬 • The global AI in manufacturing market is projected to reach $20.5 billion by 2029 • 85% of manufacturers have invested or plan to invest in AI/ML for robotics this year • Manufacturers using AI report a 69% increase in efficiency and 61% improvement in productivity 👉𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬 𝐢𝐧 𝐈𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭𝐢𝐧𝐠 𝐀𝐈 𝐢𝐧 𝐌𝐚𝐧𝐮𝐟𝐚𝐜𝐭𝐮𝐫𝐢𝐧𝐠 • Talent Gap: There's a shortage of experienced data scientists and AI engineers in the manufacturing sector • Data Quality and Privacy: Ensuring clean, accurate, and unbiased data while maintaining privacy and security is crucial • Technology Infrastructure: Integrating AI with legacy systems and ensuring interoperability between different technologies can be complex • Cultural Resistance: Overcoming employee concerns about job security and adapting to new AI-driven processes can be challenging • Ethical Considerations: Ensuring fairness, transparency, and accountability in AI decision-making processes is essential As AI and automation continue to evolve, they're reshaping the manufacturing landscape. How is your company leveraging these technologies to stay competitive? 𝐒𝐨𝐮𝐫𝐜𝐞𝐬: https://lnkd.in/ge3TGArE https://lnkd.in/gc276FhK #AI #DigitalTransformation #GenerativeAI #GenAI #Innovation  #ThoughtLeadership #NiteshRastogiInsights 

Stanford University researchers released a new AI report, partnering with the likes of Accenture, McKinsey & Company, OpenAI, and others, highlighting technical breakthroughs, trends, and market opportunities with large language models (LLMs).  Since the report is 500+ pages!!! (link in comments), sharing a handful of the insights below: 1. Rise of Multimodal AI: We're moving beyond text-only models. AI systems are becoming increasingly adept at handling diverse data types, including images, audio, and video, alongside text. This opens up possibilities for apps in areas like robotics, healthcare, and creative industries. Imagine AI systems that can understand and generate realistic 3D environments or diagnose diseases from medical scans. 2. AI for Scientific Discovery: AI is transforming scientific research. Models like GNoME are accelerating materials discovery, while others are tackling complex challenges in drug development. Expect AI to play a growing role in scientific breakthroughs, leading to new materials and more effective medicines. 3. AI and Robotics Synergy: The combination of AI and robotics is giving rise to a new generation of intelligent robots. Models like PaLM-E are enabling robots to understand and respond to complex commands, learn from their environment, and perform tasks with greater dexterity. Expect to see AI-powered robots playing a larger role in manufacturing, logistics, healthcare, and our homes. 4. AI for Personalized Experiences: AI is enabling hyper-personalization in areas like education, healthcare, and entertainment. Imagine educational platforms that adapt to your learning style, healthcare systems that provide personalized treatment plans, and entertainment experiences that cater to your unique preferences. 5. Democratization of AI: Open-source models (e.g., Llama 3 just released) and platforms like Hugging Face are empowering a wider range of developers and researchers to build and experiment with AI. This democratization of AI will foster greater innovation and lead to a more diverse range of applications.