Janie S.

Nudge Users to Catch Generative AI Errors Using large language models to generate text can save time but often results in unpredictable errors. Prompting users to review outputs can improve their quality. By Renée R, Yunhao Z, Haiwen Li, Paul D, Arnab D, Philippe R & Patrick Connolly; via MIT Sloan Management Review #TechnologyImplementation #MachineLearning https://cstu.io/805335

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To make your AI models operational in your product or service, you need to deploy an AI inference system into your production application. Where to start? Get this eBook for expert insight on AI inference challenges and strategies, and real-world case studies.

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Quantum Computing: The Market Makers’ Pandora’s Box? This groundbreaking and rapidly evolving technology could be used in a multitude of applications: 🪜 Enhancing market making with faster, more accurate pricing models 🦾 Improving price discovery through complex system modeling 🛠️ Optimizing portfolio management for institutional investors 🏃🏼‍♂️Accelerating derivatives pricing and risk calculations 🪢 Stabilizing volatile crypto markets with efficient cross-exchange arbitrage 🥽 Enhancing DeFi protocols and smart contract optimization Quantum computing stands poised to transform financial markets, offering unprecedented capabilities in data analysis and complex problem-solving. For traditional markets, this means more efficient market making, tighter bid-ask spreads, and improved liquidity. Institutional investors can leverage quantum algorithms for superior portfolio optimization, potentially leading to better risk-adjusted returns. In the crypto space, quantum computing could be the key to addressing volatility and fragmented liquidity. Quantum-powered market making algorithms could provide more consistent pricing across exchanges and trading pairs, while also enhancing the efficiency of DeFi protocols. This technology has the potential to bridge the gap between traditional finance and the emerging world of digital assets. As we move towards a quantum-enabled financial future, market participants must stay informed and prepared. While challenges remain in areas like regulation and data privacy, the potential benefits of quantum computing for financial markets are immense. Those who embrace this technology early stand to gain a significant competitive advantage in the evolving landscape of global finance. 🔗 Read more here: https://lnkd.in/eMwmE4aK

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Want to ensure you're implementing AI correctly? Our 3-Day Challenge includes a comprehensive AI Implementation Checklist. Kick start your AI projects with confidence and see immediate BIG impact! https://tinacaio.com/3dayC #AI #ThriveWithAIOnline

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This video from IBM is a nice overview of what synthetic data is and how it works. It’s interesting how much importance is given to traditional surveys that often have just 100 respondents. The answers from that micro segment are used as a platform from which to infer general preferences and behaviours for an audience that globally could be in the six figures. What do Saas CMOs care about or want most for example? #marketing #data https://lnkd.in/erCX9yBH

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I like this stat..."13% of CEOs have put the impetus on themselves to lead the charge on GenAI." The findings from Gartner demonstrate that AI is now playing a central role in driving business productivity. However, this is just the beginning of a much larger trend. The productivity gains highlighted in this survey primarily stem from tapping publicly available sources like ChatGPT. The real boost in business productivity will come when organizations are able to securely tap into their own authoritative data sources to create a single source of truth, which can then be leveraged to better serve clients and drive more business. Some examples of valuable uses include quickly providing colleagues and clients with up-to-date, authoritative answers to questions, and generating vetted, approved responses to bids and RFPs. To understand how this works, check out this ebook: https://lnkd.in/edSSyuej #artificialintelligence #business #productivity

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Governing #GenAI? A necessity. A challenge. And its' now possible with Domino Data Lab. Read more: https://gag.gl/duOMFA #AI #GenerativeAI #ResponsibleAI #DominoDataLab #AIGovernance

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AICX Institute™ Question of the Day. Here is one of the top 3 questions I am asked by global CMOs, Chief Data Officers, Chief Customer Officers and Chief AI Officers: Q: "...how do I optimize my Gen AI process to support hyper-personalization?" A: The AI Supply Chain. Shown below, the supply chain has 6 AI process streams integrated into 1 holistic Gen AI environment, they are: 1) Customer Journey - seamless, transparent brand experience 2) Interactions - offer, pricing, service 3) Gen AI Models - real-time Gen AI content & targeting 4) Back-end Apps - process enablement 5) Data Sources - The AI Data Ecosystem: CDPs + other 5) Infrastructure. The AICX Institute mission: "...take AI out of the lab and into production @ Enterprise scale." The Institute's solutions are grounded in case studies and actual experience vs. theory. Join today, it's free: https://lnkd.in/g86MhJyY aicxinstitute.com #ai #genAI #AICX #AIsupplychain #cmo #aicontent #customerjourney

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Nice one. I am just curious how Abobe and Meta, not with the SAM CV model, get to the list 🙂 For agents, so far, only Flowise, N8N, or Python code - no other options, unfortunately. Agents will be the hot topic in 2025; In 2024 only very basic things about agents, even with no agreed-upon terminology for what an AI agent is. For building a product, they missed V0. I'm sure something else is missing. Building my list based on hands-on experience is a nice idea. I will add it to my to-do list.

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In this #a16zpodcast 🎙 Justine Moore and Bryan Kim discuss recent developments in large language models (LLMs). Main points: 🤖 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐦𝐞𝐧𝐭𝐬 𝐢𝐧 𝐀𝐈: The episode highlights significant updates from #OpenAI's GPT-4o and Google's #Gemini. 🗣 𝐌𝐮𝐥𝐭𝐢-𝐦𝐨𝐝𝐚𝐥 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐨𝐧𝐬: The discussion centers around these AI models taking on the role of companions and their ability to interact through voice. 🎧 𝐍𝐮𝐚𝐧𝐜𝐞𝐬 𝐨𝐟 𝐚𝐮𝐝𝐢𝐨 𝐜𝐨𝐦𝐦𝐮𝐧𝐢𝐜𝐚𝐭𝐢𝐨𝐧: They dive into the importance of factors like speech patterns and personality in effective communication through audio.

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Combining point-of-sale (POS) data with demographic data can unlock a world of insights for CPG brand managers. Here’s how generative AI like AisleAI is transforming this data into actionable strategies, in seconds: Purchase Patterns 🛒: Delve into which products resonate with specific demographic groups. Market Segmentation 🔍: Tailor marketing efforts to niche markets by overlaying demographic details on POS data. Targeted Marketing 🎯: Use demographics and purchase behavior to craft laser-focused marketing campaigns. Product Development 💡: Inform your product pipeline with insights into what different demographic groups are really buying. Seasonal Trends 📅: Spot purchase patterns across seasons for different demographic segments to better plan inventory and promotions. Competitive Analysis 💼: Gauge how your products stack up against competitors within various demographic markets. In-Store Placement 🏪: Optimize shelf space and product assortment based on shopper demographics to enhance in-store experience. Price Sensitivity 💲: Adjust pricing strategies by understanding the financial landscape of your customer base. I'd love to hear from the LinkedIn community - Which of these insights have been the biggest game changer for your strategy? And are there any others you have discovered? Comment below and share your thoughts!

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I've watched an amazing engineering team get this new release out and introduce some really interesting new capabilities. I've used or seen a bunch of Strategy systems over the years - this is the only one I've seen that covers everything. Most of the others are mostly just glorified project management tools. That's fine if all one wants to do is track activities. But it's not just about monitoring activity; it's about actually getting to the desired outcome. This platform goes End-to-End. From the Vision-to-Outcomes. And the use of AI makes it significantly faster and easier. Do yourself a favor, go take a look. #strategy #V2O #Vision-to-Outcomes #Success #BusinessGrowth

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How Generative AI is Revolutionizing Empathetic Customer Care for Lifetime Value In an enlightening study published in the Journal of Marketing, Ming-Hui Huang and Roland T. Rust delve into the transformative power of Generative AI (GenAI) in enhancing empathetic customer relationships. Their research, "The Caring Machine: Feeling AI for Customer Care," conducted in collaboration between National Taiwan University and the University of Maryland, underscores the significant role that AI can play in fostering deep emotional connections with customers, which in turn boosts loyalty and profitability. Generative AI, which encompasses leading technologies like OpenAI's GPT models and Google's Bard, represents the next frontier in customer service. These AI systems are adept at understanding and reacting to human emotions, a critical component for building lasting customer relationships. By analyzing customer inputs, GenAI can deliver personalized responses that resonate emotionally, demonstrating a profound understanding of the customer's needs and feelings. Key Insights for CXOs: — Emotion Recognition Accurately identifying customer emotions is paramount. Misunderstandings can escalate emotions, hence, precision in recognizing and addressing customer feelings is crucial. Empathy and Understanding GenAI's ability to empathize, driven by deep learning from vast datasets, enables it to craft responses that are not only accurate but also genuinely empathetic. Emotion Management Effective emotion management recommendations tailored to individual customer scenarios can significantly enhance the customer experience. Emotional Connection The study advocates for a "caring machine" with enough self-awareness to align with both the firm's strategic goals and the customer's personal intentions, thereby strengthening the emotional bond. For CMOs and customer care executives, the study emphasizes the importance of integrating GenAI into the customer care strategy thoughtfully. While GenAI holds immense potential, the human element remains indispensable in interpreting complex customer emotions and managing them effectively. This research invites marketing leaders to rethink how empathetic AI can not only meet but exceed customer expectations, creating enduring value and loyalty. As we move forward, the synergy between human insight and AI capabilities will be key to unlocking profound customer engagement and satisfaction. #MarketingLeadership #CustomerEngagement #GenerativeAI #DigitalTransformation #AIinMarketing https://lnkd.in/gDX_9fRz

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