Filippo Chiari

By Carsten Krause, July 29th, 2024 The relentless march of Artificial Intelligence (AI) has left many wondering whether we are destined to be mere sidekicks in a world dominated by algorithms and machine learning. But fear not! There is still room for the uniquely human touch. Imagine a future where your refrigerator orders your groceries, your car drives itself, and your digital assistant schedules your meetings. But in the middle of all this automation, it's easy to feel like we're becoming secondary characters in our own lives, with AI stealing the spotlight. Will our children grow up in a world where their best friend is a chatbot? #AIplusHI #AIStrategy https://lnkd.in/e7GDCnSK

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By Carsten Krause, July 29th, 2024 The relentless march of Artificial Intelligence (AI) has left many wondering whether we are destined to be mere sidekicks in a world dominated by algorithms and machine learning. But fear not! There is still room for the uniquely human touch. Imagine a future where your refrigerator orders your groceries, your car drives itself, and your digital assistant schedules your meetings. But in the middle of all this automation, it's easy to feel like we're becoming secondary characters in our own lives, with AI stealing the spotlight. Will our children grow up in a world where their best friend is a chatbot? #AIplusHI #AIStrategy https://lnkd.in/e7GDCnSK

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By Carsten Krause, July 29th, 2024 The relentless march of Artificial Intelligence (AI) has left many wondering whether we are destined to be mere sidekicks in a world dominated by algorithms and machine learning. But fear not! There is still room for the uniquely human touch. Imagine a future where your refrigerator orders your groceries, your car drives itself, and your digital assistant schedules your meetings. But in the middle of all this automation, it's easy to feel like we're becoming secondary characters in our own lives, with AI stealing the spotlight. Will our children grow up in a world where their best friend is a chatbot? #AIplusHI #AIStrategy https://lnkd.in/e7GDCnSK

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AI speculation appears to have gotten completely out of hand. As quoted in today’s FT, training the latest language models costs around $100m, while Anthropic’s CEO forecasts that training the next generation’s will cost $1-10bn. Meanwhile, Altman has been seeking funding amounting to trillions of dollars to bankroll OpenAI’s development of chips and further models. Despite these investments, we’re still not seeing many productised use cases for these models with a net positive ROI once run costs are accounted for. I’m a firm believer in the power of constraints to fuel creativity and innovation. But, as an outsider’s view to the Big Tech companies funding most of this, it seems like a lot of the R&D into GenAI is being driven by largely unconstrained investment and blank cheques. I’m definitely not the first person who’s predicted a boom-and-bust cycle relating to all this… I wonder how long until the bubble bursts? Keen to hear others’ thoughts on which GenAI use cases stand most chance of eventually achieving ROI-positive results - and how far off we are from cracking the feasibility challenges/ edge cases. #GenAI #SpeculationAboutSpeculation

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🧩 Reading [Google Research's latest article](https://lnkd.in/ejk3_wMH) on understanding relationships between datasets got me thinking about the bigger picture in data management. This research brings out the importance of uncovering and automating complex relationships within raw data—a task that’s essential but often challenging. ✨ Palantir’s Ontology approach came to mind here as a powerful example of putting these ideas into action. By creating a digital twin of business entities and their relationships, Palantir enables companies to interact with data at a higher, business-relevant level. This abstraction layer transforms raw data into meaningful insights. ⚙️ To bring further structure, tools like Featuretools, Woodwork, Compose, and EvalML offer an open-source framework set that standardizes features and prepares data for machine learning. With **Featuretools** for automated feature engineering and **Woodwork** for consistent data typing, this toolkit enables the creation of reusable data products right from raw schemas and tables. 🌐 Imagine combining Google’s research-driven insights, Palantir’s digital twin framework, and the Featuretools ecosystem. Together, they could enable a truly dynamic data ecosystem—one where relationships are not just mapped but also standardized, enriched, and primed for decision-making. #DataManagement #Ontology #FeatureEngineering #GoogleResearch #Palantir #MachineLearning #OpenSource

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A single ChatGPT query can generate up to 100 times more carbon emissions than a standard Google search. Now that the initial generative AI hype has passed its peak, it’s becoming more clear that we need a nuanced approach to tech adoption. As we push the boundaries of what’s possible with AI, we must also remain vigilant stewards of our planet. Balancing technological advancement with sustainability is not just a challenge but an opportunity to lead in both innovation and environmental responsibility. #AI #ChatGPT

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Unpopular Opinion: Gen AI has become a deep source of distraction for data scientists these days. One moment, they're deep in tuning models and running important tests. The next, they’re exploring fascinating but unrelated challenges—like why GPT can’t count the letter ‘R’ in the word ‘strawberry.’ 🍓🤖 Generative AI is a game-changer, no doubt. It helps automate tasks, spark creativity, and open up new ideas. But it’s important to balance these exciting tools with the practical methods of traditional ML when needed. ✨ Reminder: Embrace the power of Gen AI, but don’t lose focus on what really matters. Both can work hand-in-hand to achieve the best results! #DataScience #GenerativeAI #UnpopularOpinion #StayFocused #MachineLearning #Balance

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How is Ocean Spray getting ready for AI? In this preview of our podcast with Neil Hampshire CIO and CDO of Ocean Spray Cranberries we discuss how companies are getting ready for AI and how you have to be very strategic about use cases to move fast without being reckless. This includes generative AI retrieval augmented generation (#rag ) models using internal data and “old fashioned” machine learning. #datastrategy #generativeAI #machinelearning #cdo #cio #oceanspray #cdotimes

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Automatic Data Quality is the competitive advantage for success in the new IA era.

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AI augments retail companies in many ways, but advanced demand forecasting is among the most powerful. Here’s how you can get better at predicting the future: 1. Level up your data game. No amount of investment in expensive AI models will ever fix poor data sets. The more historical data points you have, the better: Customer demand records Logistics-related data   And even external data such as Economic indicators and Weather information. Clean it by removing irrelevant information, identifying and handling outliers, and resolving any inconsistencies so you can feed the models with relevant data for accurate analysis. 2. Select your perfect model. Consider different approaches like: Regression models Time-series analyses Neural networks Assess the computational resources available, understand each model's complexity, and decide based on the unique characteristics of your data sets. 3. Train and validate your model. Split the dataset into training and testing subsets. The model is trained using the training data and then rigorously tested against the testing dataset to validate its predictive capabilities. You should also regularly update the training dataset with new information, track the model's performance metrics, and incorporate user feedback for enhanced accuracy. 4. Deploy!  Create user-friendly interfaces to make the predictive insights accessible to decision-makers. Set up real-time prediction capabilities and alert mechanisms to communicate significant demand shifts effectively. The chart below illustrates a typical demand forecasting system (though it’s missing the testing and validation phase, which is super important, in my opinion). Ready to level up your foresight capabilities using AI? DM me, and we can make it a reality! ✉️ #management #ai #retai #ecommerce #digitaltransformation #RemoteNative Andreas Anding - Technical Leader with 20+ years of experience in large-scale digital transformation projects.

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A culture of AI experimentation is not simply born. It is cultivated through fostering curiosity and encouraging creative risk-taking. Leaders are often expected to have all the answers, particularly when it comes to the rapidly evolving field of AI. However, the reality is that we might not have all the solutions just yet. Instead of focusing solely on finding definitive answers, we should prioritise creating a culture that embraces AI experimentation. This is especially necessary as there is a significant disconnect between the growing interest in AI and its actual implementation in the workplace. With only 15% of workers feeling fully prepared to use AI effectively, it’s clear that there’s a need for a shift in approach. #AI Culture #Innovation #Leadership

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Holistic approach for AI adoption is the way to go…

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🎯GCPL X Trailytics 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐢𝐧𝐠 𝐒𝐮𝐩𝐩𝐥𝐲 𝐂𝐡𝐚𝐢𝐧 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐰𝐢𝐭𝐡 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐏𝐎 𝐏𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐨𝐧𝐬 𝐟𝐨𝐫 𝐞𝐂𝐨𝐦𝐦𝐞𝐫𝐜𝐞 𝐚𝐧𝐝 𝐌𝐓 𝐫𝐞𝐭𝐚𝐢𝐥𝐞𝐫𝐬 📊  Predicting the future isn’t about crystal balls—it’s about leveraging the power of data science and machine learning! 🚀  At Trailytics  we tackled the complexities of Purchase Order (PO) predictions for platforms like 𝐀𝐦𝐚𝐳𝐨𝐧, 𝐅𝐥𝐢𝐩𝐤𝐚𝐫𝐭, 𝐚𝐧𝐝 𝐁𝐥𝐢𝐧𝐤𝐢𝐭, driving transformative outcomes.  ⭕ 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬 𝐅𝐚𝐜𝐞𝐝 𝐛𝐲 𝐁𝐫𝐚𝐧𝐝𝐬   - Heavy reliance on retailer-shared forecasts, often resulting in low fill rates or excess inventory.   - Lack of accurate SKU-location-level predictions for effective demand planning at close as 10 days level ✅ 𝐎𝐮𝐫 𝐌𝐢𝐬𝐬𝐢𝐨𝐧   To build a forecasting system capable of predicting PO quantities with up to 95% accuracy at the SKU-location level—and we delivered!  🛠 𝐎𝐮𝐫 𝐀𝐩𝐩𝐫𝐨𝐚𝐜𝐡   - Tech Stack: Leveraged models like 𝐀𝐑𝐈𝐌𝐀, 𝐑𝐚𝐧𝐝𝐨𝐦 𝐅𝐨𝐫𝐞𝐬𝐭, 𝐚𝐧𝐝 𝐗𝐆𝐁𝐨𝐨𝐬𝐭 , analyzing historical data trends, seasonality, and inventory patterns.   - Hybrid Methods: Combined time series analysis with machine learning to achieve superior accuracy.   - Root Cause Analysis: Identified gaps in data availability and enhanced disaggregation methods for more reliable predictions.  🌟 𝐊𝐞𝐲 𝐎𝐮𝐭𝐜𝐨𝐦𝐞𝐬   - Enhanced Demand Planning: Reduced dependency on retailer forecasts, leading to better decisions.   - Minimized Inventory Waste: Struck the perfect balance between supply and demand.   - Optimized Production Schedules: Improved efficiency across the supply chain.  📈 𝐈𝐦𝐩𝐚𝐜𝐭 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬   - Forecasting Process Flowchart 🔄   - Model Performance Comparison 🔬   - Root Cause Analysis Summary 🛠  This initiative exemplifies the power of data-driven innovation to redefine operational efficiency and create lasting value.  🚀 We’re excited about the potential of predictive analytics to revolutionize supply chain management for brands worldwide. Want to know more about how we can make this happen for you? Let’s connect! #Trailytics #POOptimization #PO #eCommerce Shakti Singh

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Following suits of great people in my network and seeing a trend almost before we bit goodbye to 2024, so here ny my 2024 LinkedIn Rewind, by Coauthor.studio: 2024: The year I discovered that building world-class data platforms isn't about perfect technology—it's about creating an environment where human imperfection becomes our greatest innovation engine. This journey transformed how I see leadership in AI and data. No longer just about technical excellence, but about understanding how diverse perspectives and unique human strengths can solve complex challenges. My transition to Director of AI and Data Platform at Collinson wasn't just a title change; it was a profound shift in understanding that breakthrough innovations emerge from teams who embrace their differences. Three posts this year crystallized this transformation: ➡️ Product Development Insight: "An underappreciated engineer and an overwhelmed product manager—two sides of the same coin, yet often miles apart." Success comes from bridging technical excellence with human understanding. https://lnkd.in/efJE8Yub ➡️ Team Building Reflection: "Building a great team means bringing together great people. Not everyone needs to fit perfectly into your ideal checklist; what someone lacks in one area often highlights their strengths in another." https://lnkd.in/egEV6qf4 ➡️ Leadership Philosophy: "Make it a habit to ask at least one person every day, 'How can I help?'" https://lnkd.in/ekWHy7ap Beyond these insights, 2024 marked significant milestones: completing the INSEAD Leadership Communication with Impact certification, speaking at the CDO Travel and Hospitality Exchange, and continuing to grow "One Perspective at Once" on Substack. Looking ahead to 2025, my focus remains unwavering: building platforms that unifies the intelligence both of human and machines, that don't just process information, but unlock true potential. The most sophisticated AI won't replace human creativity—it will amplify our collective intelligence. For data leaders and AI practitioners: your most powerful technology is the team you build, not just the code you write. #AI #DataLeadership #LeadershipLessons #TeamBuilding #LinkedInRewind #Coauthor #2024wrapped

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Exciting Developments in AI-Powered Search Technologies! 🚀 We're on the brink of a revolution in digital information retrieval! With OpenAI potentially entering the search engine arena, the question arises: Will OpenAI redefine how we search online? 🔍 AI-powered search engines are transforming how we interact with the web. They offer more intuitive, intelligent, and personalized search experiences, utilizing advanced machine learning and natural language processing to understand the context and intent behind queries better. 🌐 From enhancing user personalization to integrating multimodal search capabilities, AI is setting new standards in search technology. OpenAI's foray could further shake up the industry, promising innovative approaches beyond traditional search models. 🤖 Stay tuned as we explore the potential impact of OpenAI's search engine and what it means for the future of digital queries. The evolution is not just about speed and efficiency but about making our interaction with information more meaningful and contextually rich. 🔗 Dive deeper into this fascinating topic and join the conversation about how AI is reshaping the search landscape: https://lnkd.in/gGDPpkcw #AI #SearchEngine #DigitalTransformation #OpenAI #Innovation #TechnologyTrends

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🚀 #Microsoft releases SpreadsheetLLM, a model designed to optimize LLMs' powerful understanding on spreadsheets. One of the key advantages of SpreadsheetLLM is its ability to potentially query and manipulate spreadsheet data using plain English, rather than complex formulas or programming languages. This could democratize access to data insights and empower more individuals within an organization to make data-driven decisions. Furthermore, SpreadsheetLLM could help automate many of the tedious and time-consuming tasks associated with spreadsheet data analysis, such as data cleaning, formatting, and aggregation. #llm #generativeai #artifialintelligence

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