Hugo PERIER’s Post

5mo

What do French mutual insurance companies and Google have in common? … At least this last week’s meeting! 😄 Just a few days ago, I had the opportunity to attend a conference on generative #AI in the insurance industry at Google, organised by my company. This day marks a major milestone for Groupe VYV on this path. Here are some insights I'd love to share: 🔹Groupe VYV has an ambition roadmap (S3NS platform, IA lab, the use of GitHub Copilot in dev teams, HR use cases…) placing a huge emphasis on #dataquality to support their AI projects. 📊✨ 🔹 AI is revolutionizing tasks across the board— from drafting meeting minutes and generating follow-up emails, comparing health insurance policies and crafting personalized marketing campaigns. 📝🔍 Google's use cases with AG2R LA MONDIALE and Carrefour highlight how generative AI is set to transform business processes, boosting efficiency and exceeding customer expectations. Massive thanks to Anne Gradvohl ✨ and Aurélien Barthe for this enlightening day packed with valuable insights! There's still much to do … but I'm grateful to be at this stage and on this journey ! #AI #DataScience #Innovation #Conference #Google #GroupeVYV #Technology #FutureOfInsurance #Disruption

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Adam MacLennan

The Business of Digital Marketing, with AI Since ‘22
8mo
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There were some pretty cool developments at the intersection of insurance and AI over the last week and change. 🤖 AutoBind.AI launched its service, which can quote and bind insurance shoppers in 15 minutes on the phone using a verbal chatbot. It's far less risky (and creepy) than that probably seems; check them out. 🤖 BeyondRoadmap announced a closed beta test for a tool that automates time-consuming tasks for claims adjusters. They're still looking for adjusters to participate in the test, and they report good reviews so far. 🤖 Healthy Labs released the CMS Rulebot, a custom GPT to help everyone understand the new 1327-page CMS (Centers for Medicare and Medicaid Services) rule document. I tried this one personally, and while I'm a CMS journeyman at best, the answers are pretty good. These are practical, useful, here-and-now tools of different stripes, and I'm sure they're only the beginning. #Insurance #GenerativeAI (Image created with DALL E)
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Feruz Weldeghebrebi

Licensed Insurance agent
8mo Edited
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🚀 Exciting News! Vienna Insurance Group (VIG) is revolutionizing the insurance landscape by harnessing the power of AI! 🤖 In the face of rapid business evolution, VIG has embraced AI as a crucial tool, and here's how they're utilizing it: 🎨 Content Creation: VIG employs cutting-edge generative AI tools like Jasper and Midjourney to craft captivating content. Whether it's crafting catchy copy or designing visuals, AI streamlines the creative process, saving time and effort. 📊 Data Analysis and Reporting: With approximately 45% of marketers using generative AI, VIG has transformed data analysis and reporting. What was once a labor-intensive task is now seamlessly handled by AI, extracting insights and compiling sleek presentations for informed decision-making. 💡 Research and Inspiration: AI serves as a beacon of inspiration for VIG's marketing teams, providing endless research possibilities and innovative ideas. From exploring market trends to generating fresh campaign concepts, AI keeps VIG ahead of the curve. AI isn't just for tech giants; it's becoming a mainstream force across industries, including insurance. VIG's adoption of AI showcases its commitment to enhancing customer experiences, streamlining operations, and driving informed decisions. Now, I'm curious! What are your thoughts on VIG's AI-powered initiatives? How do you envision AI shaping the future of the insurance industry? Share your insights below! 👇 #AI #InsuranceInnovation #VIG #FutureForward# georgebrown college https://lnkd.in/ggyw2kyU
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Jason Demby

Generative AI and Machine Learning for Financial Services Business Development Leader at Amazon Web Services (AWS) | Keynote Speaker | Little League Coach | Balloon Handler
4mo Edited
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REGISTER TODAY! Excited to have our insurance customers join us for Generative AI Day on September 12 in NYC! I’m looking forward to being joined by leaders from our partners Anthropic, Accenture, Vertical Relevance and my AWS colleagues! Join us for an exclusive event where we will explore best practices to accelerate the adoption of Generative AI in the insurance industry. You will have the opportunity to hear from AWS and partner experts on the latest generative AI trends and learn how to accelerate your Proof-of-Concept (POC) initiatives to production. The event will also provide a platform for you to engage in peer-to-peer conversations on various generative AI topics under Chatham House Rules. Why Attend? -Engage in Meaningful Conversations: Share your experiences and insights in driving innovation with generative AI. -Meet with Experts: Interact with AWS and partner experts to identify solutions that can help you achieve your business goals. -Provide Feedback: Offer your feedback and insights that will shape the future vision of our services. -Learn Best Practices: Discover best practices for accelerating your generative AI initiatives. This event is designed for Engineering & Data Science Managers, Architects and Line of Business (LOB) Managers who are actively delivering generative AI initiatives within their organizations. It’s going to be a great one and appreciate your continued leadership Jimmy Kaw and partnering with our GenAI and Insurance industry leaders Bryan Davis Dan Ochs Jayme Hart Raghvender Arni Roop B. Jonathan Pelosi Dan Eckstein #generativeai #financialservices #insurance

Generative AI Day for Insurance

generativeaidayforinsurancesept2024.splashthat.com

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Dr. Chan Naseeb Dr. Chan Naseeb is an Influencer

Global AI Leader | IBM, X-KPMG, X-Accenture. AI Expert | Agentic AI | Generative AI | Multi-Modal & LLMs | MLOps | Responsible AI | Keynote Speaker | Advisor | Consultant | Career Coach
4mo
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#RAG use cases realized with #watsonx while working with our #build #partners #ecosystem Find out the details below.
Omkar Nimbalkar

Vice President at IBM
4mo Edited

In our work with #build #partners, we have explored many flavors of how #RAG can be implemented with #watsonx. Inspired by the documentary "14 Peaks: Nothing Is Impossible," in which #Sherpas took on the monumental challenge of climbing 14 of the world’s highest mountains, we have embraced our own challenge by developing over 14 use cases showcasing various implementations of RAG. They are completely open for you to review and experiment with on https://lnkd.in/eFMbbDrx. We have recently published 5 new RAG use cases on our Digital Self-serve Co-create Experience (#DSCE) with watsonx that are worth highlighting. Two of them are in collaboration with our partner Persistent Systems: * Auto insurance quote generator with Persistent Systems: Auto insurance quotes are generated by analyzing claims history and driver profiles to predict risk. Uses Mistral AI 'mixtral-8x7b-instruct-v01' for risk assessment and watsonx Assistant for user interaction. * Auto insurance finder with Persistent Systems: A recommendation engine analyzes customer-specific data to provide numerous tailored vehicle insurance policy options. Leverages IBM 'granite-13b-chat-v2' and Meta 'llama-3-70b-instruct' for personalized recommendations. * Smart catalog search: A retail user can use image search to find related products in the online store catalog. Employs #Milvus #vectordatabase in watsonx.data to match product images based on similarity. * Multi-domain documents Q&A: Users can ask questions related to the information contained in documents from various domains that are stored in the same knowledge base. Indexes documents in watsonx Discovery and uses watsonx.ai models to generate answers via watsonx Assistant chat. * Health report assistant: A database stores complex medical reports uploaded by healthcare providers, enabling a conversational AI, powered by watsonx.ai and watsonx Assistant capabilities, to generate concise and actionable summaries. #AI #MachineLearning #EnterpriseAI #RAG Savio Rodrigues Raj Datta Ayal Steinberg Kate Woolley Ritika Gunnar Armand Ruiz Maryam Ashoori, PhD Edward Calvesbert Parul Mishra
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Persistent Systems

1,415,527 followers
4mo
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We've just rolled out 2 new retrieval-augmented generation use cases on IBM's Digital Self-Serve Co-Create Experience (DSCE) with watsonx, and they’re game-changers! 🌟 These innovative use cases include: Auto Insurance Quote Generator: Analyzing claims history and driver profiles, the tool predicts risk and generates accurate auto insurance quotes. It utilizes Mistral AI for risk assessment, paired with watsonx Assistant for seamless user interaction. Auto Insurance Finder: This recommendation engine analyzes customer-specific data to offer tailored vehicle insurance policy options. It leverages IBM's Granite and Meta Llama for highly personalized recommendations. Explore these use cases and more on DSCE https://lnkd.in/dHqyBGkg Kuljesh Puri, Neerav Shah, Keyur Shroff, Mangesh Naik, Talat Shaheen #DSCE #watsonx #GenAI #Innovation #IBMPartner
Omkar Nimbalkar

Vice President at IBM
4mo Edited

In our work with #build #partners, we have explored many flavors of how #RAG can be implemented with #watsonx. Inspired by the documentary "14 Peaks: Nothing Is Impossible," in which #Sherpas took on the monumental challenge of climbing 14 of the world’s highest mountains, we have embraced our own challenge by developing over 14 use cases showcasing various implementations of RAG. They are completely open for you to review and experiment with on https://lnkd.in/eFMbbDrx. We have recently published 5 new RAG use cases on our Digital Self-serve Co-create Experience (#DSCE) with watsonx that are worth highlighting. Two of them are in collaboration with our partner Persistent Systems: * Auto insurance quote generator with Persistent Systems: Auto insurance quotes are generated by analyzing claims history and driver profiles to predict risk. Uses Mistral AI 'mixtral-8x7b-instruct-v01' for risk assessment and watsonx Assistant for user interaction. * Auto insurance finder with Persistent Systems: A recommendation engine analyzes customer-specific data to provide numerous tailored vehicle insurance policy options. Leverages IBM 'granite-13b-chat-v2' and Meta 'llama-3-70b-instruct' for personalized recommendations. * Smart catalog search: A retail user can use image search to find related products in the online store catalog. Employs #Milvus #vectordatabase in watsonx.data to match product images based on similarity. * Multi-domain documents Q&A: Users can ask questions related to the information contained in documents from various domains that are stored in the same knowledge base. Indexes documents in watsonx Discovery and uses watsonx.ai models to generate answers via watsonx Assistant chat. * Health report assistant: A database stores complex medical reports uploaded by healthcare providers, enabling a conversational AI, powered by watsonx.ai and watsonx Assistant capabilities, to generate concise and actionable summaries. #AI #MachineLearning #EnterpriseAI #RAG Savio Rodrigues Raj Datta Ayal Steinberg Kate Woolley Ritika Gunnar Armand Ruiz Maryam Ashoori, PhD Edward Calvesbert Parul Mishra
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Karim F Khinouche

Building a better, safer future for food at global scale.
2mo
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Fascinating read by Angela Strange and James da Costa on Andreessen Horowitz about AI's role in transforming white-collar work. As a vertical SaaS, Novolyze is already seeing this shift firsthand. We're integrating AI copilot capabilities to empower food safety professionals, enhancing efficiency and decision-making in critical processes. It’s exciting to witness how AI is evolving from a buzzword to a practical tool driving real impact across industries. Read more on a16z's perspective: The Copilot and the AI Agent #AI #SaaS #DigitalTransformation #VerticalSaas #foodsafety

Every White-Collar Role Will Have An AI Copilot. Then An AI Agent. | Andreessen Horowitz

a16z.com
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elyadata

20,919 followers
7mo
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❇ Imagine transforming insurance pricing from a guessing game to a data-driven force for good. ❇ We recently partnered with a leading insurance company to level up their system. Leveraging AI and data engineering, we created a FASTER, FAIRER and MORE PROFITABLE approach for everyone involved. Swipe to discover the blueprint for a future-proof insurance experience ! #Insurance #InsurancePricing #DataEngineering #AI #DataDriven
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AiShelter

317 followers
1mo Edited
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🚀 𝗘𝘅𝗰𝗶𝘁𝗶𝗻𝗴 𝗡𝗲𝘄𝘀! 🚀 We’re thrilled to launch The AiShelter Deep Dive, a new monthly series exploring the evolving landscape of AI liability insurance, the unique challenges and opportunities it brings. Powered by Google's #NotebookLM, this series dives into the latest in AI, from groundbreaking advancements to the critical risks often overlooked in emerging tech. For our inaugural episode, we tested NotebookLM simply by entering the AiShelter website link, along with a few custom prompts. Unlike our competitors, we had to disable a safeguard against AI-powered bots, allowing NotebookLM the ability to read our website. 💡 𝘼𝙄 𝙋𝙧𝙤 𝙏𝙞𝙥: Did you know that robots.txt—a basic text file—controls what web crawlers and AI bots can and cannot access? NotebookLM is a remarkable tool, but it struggles with some fundamental nuances, like pronouncing our name AiShelter correctly, even with prompt adjustments. While this may seem minor, it reflects the broader challenges AI systems face in grasping context and producing accurate results in real-world applications. Tune in weekly as we unpack the complexities of AI insurance, risk management, and why understanding AI’s limitations is crucial to safe and reliable innovation. 🎧 🎥 Watch the first episode now to see how we’re navigating the balance between innovation and accountability, and why a deep understanding of AI is essential for building trust in this tech-driven world. #AIInsurance #AIRiskManagement #AIGovernance #AiShelter #AIDeepDive #NotebookLM #Google

Deep Dive on AiShelter
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Keyur Shroff

VP of Engineering, GenAI CoE at Persistent Systems
4mo
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If you are running a business in auto insurance sector and want to leverage GenAI technology, then you would be wise to consider Persistent Systems! #ibm #persistentsystems #genai #partnership #rag #autoinsurance #watsonx
Omkar Nimbalkar

Vice President at IBM
4mo Edited

In our work with #build #partners, we have explored many flavors of how #RAG can be implemented with #watsonx. Inspired by the documentary "14 Peaks: Nothing Is Impossible," in which #Sherpas took on the monumental challenge of climbing 14 of the world’s highest mountains, we have embraced our own challenge by developing over 14 use cases showcasing various implementations of RAG. They are completely open for you to review and experiment with on https://lnkd.in/eFMbbDrx. We have recently published 5 new RAG use cases on our Digital Self-serve Co-create Experience (#DSCE) with watsonx that are worth highlighting. Two of them are in collaboration with our partner Persistent Systems: * Auto insurance quote generator with Persistent Systems: Auto insurance quotes are generated by analyzing claims history and driver profiles to predict risk. Uses Mistral AI 'mixtral-8x7b-instruct-v01' for risk assessment and watsonx Assistant for user interaction. * Auto insurance finder with Persistent Systems: A recommendation engine analyzes customer-specific data to provide numerous tailored vehicle insurance policy options. Leverages IBM 'granite-13b-chat-v2' and Meta 'llama-3-70b-instruct' for personalized recommendations. * Smart catalog search: A retail user can use image search to find related products in the online store catalog. Employs #Milvus #vectordatabase in watsonx.data to match product images based on similarity. * Multi-domain documents Q&A: Users can ask questions related to the information contained in documents from various domains that are stored in the same knowledge base. Indexes documents in watsonx Discovery and uses watsonx.ai models to generate answers via watsonx Assistant chat. * Health report assistant: A database stores complex medical reports uploaded by healthcare providers, enabling a conversational AI, powered by watsonx.ai and watsonx Assistant capabilities, to generate concise and actionable summaries. #AI #MachineLearning #EnterpriseAI #RAG Savio Rodrigues Raj Datta Ayal Steinberg Kate Woolley Ritika Gunnar Armand Ruiz Maryam Ashoori, PhD Edward Calvesbert Parul Mishra
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Mahesh Sawaiker

Go Lang, Java, python cloud web services architect
4mo
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Bringing together the domain knowledge in insurance to augment LLMs using RAG.Way to go!!
Omkar Nimbalkar

Vice President at IBM
4mo Edited

In our work with #build #partners, we have explored many flavors of how #RAG can be implemented with #watsonx. Inspired by the documentary "14 Peaks: Nothing Is Impossible," in which #Sherpas took on the monumental challenge of climbing 14 of the world’s highest mountains, we have embraced our own challenge by developing over 14 use cases showcasing various implementations of RAG. They are completely open for you to review and experiment with on https://lnkd.in/eFMbbDrx. We have recently published 5 new RAG use cases on our Digital Self-serve Co-create Experience (#DSCE) with watsonx that are worth highlighting. Two of them are in collaboration with our partner Persistent Systems: * Auto insurance quote generator with Persistent Systems: Auto insurance quotes are generated by analyzing claims history and driver profiles to predict risk. Uses Mistral AI 'mixtral-8x7b-instruct-v01' for risk assessment and watsonx Assistant for user interaction. * Auto insurance finder with Persistent Systems: A recommendation engine analyzes customer-specific data to provide numerous tailored vehicle insurance policy options. Leverages IBM 'granite-13b-chat-v2' and Meta 'llama-3-70b-instruct' for personalized recommendations. * Smart catalog search: A retail user can use image search to find related products in the online store catalog. Employs #Milvus #vectordatabase in watsonx.data to match product images based on similarity. * Multi-domain documents Q&A: Users can ask questions related to the information contained in documents from various domains that are stored in the same knowledge base. Indexes documents in watsonx Discovery and uses watsonx.ai models to generate answers via watsonx Assistant chat. * Health report assistant: A database stores complex medical reports uploaded by healthcare providers, enabling a conversational AI, powered by watsonx.ai and watsonx Assistant capabilities, to generate concise and actionable summaries. #AI #MachineLearning #EnterpriseAI #RAG Savio Rodrigues Raj Datta Ayal Steinberg Kate Woolley Ritika Gunnar Armand Ruiz Maryam Ashoori, PhD Edward Calvesbert Parul Mishra
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