Arshad Ali
Founder at Genesyslabs | NVIDIA Certified & Intel Gold Partner | AI & ML Enthusiast | Transforming Workflows with High-Performance Workstations & Servers | Empowering Creative & Data-Driven Innovation
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NVIDIA AI: Bridging the gap between raw data and AI-powered applications, AI query engines will grow to play a crucial role in helping organizations extract value from their data. 👍
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NVIDIA AI
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Enterprises Need AI Query Engines to Fuel Agentic AI👤An AI query engine is a system that connects #AI applications, or #AIagents, to data enabling more accurate, context-aware responses. Here’s how:📊 Diverse data handling: It can access and process various data types from multiple sources.⚖️ Scalability: It can efficiently handle petabyte-scale data, making all enterprise knowledge available to AI apps.💻 Accurate retrieval: It provides high-accuracy, high-performance embedding, vector search, and reranking of knowledge.📖 Continuous learning: It can store and incorporate feedback from AI-powered apps to refine models and increase app effectiveness.Learn more ➡️ https://nvda.ws/41Y0365#GenerativeAI
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Naing Kyaw
Marvery - 软件工程物理作业
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So Cool,
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Bahareh Banijamali
Director of Product/Program Management at NVIDIA
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Enterprises Need AI Query Engines to Fuel Agentic AI 👤An AI query engine is a system that connects #AI applications, or #AIagents, to data enabling more accurate, context-aware responses. Here’s how:📊Diverse data handling: It can access and process various data types from multiple sources.⚖️Scalability: It can efficiently handle petabyte-scale data, making all enterprise knowledge available to AI apps.💻Accurate retrieval: It provides high-accuracy, high-performance embedding, vector search, and reranking of knowledge.📖Continuous learning: It can store and incorporate feedback from AI-powered apps to refine models and increase app effectiveness.Read the blog to learn more ➡️ bit.ly/3Pnzwrv#GenerativeAI
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Cassiano Ziegler Bein
Senior Solutions Architect at MongoDB
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Ensuring AI accuracy and relevance? Retrieval augmented generation (RAG) is key. MongoDB’s Abhinav Mehla shares how RAG pipelines bring enterprise data into AI apps, driving smarter chatbots, recommendations, and more in this Technology Record article! 👇https://lnkd.in/dvHepCue
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Charles Gervais
Driving Digital Transformation and Empowering SMBs
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🤖 AI is Sexy, but Are You Ready? 🤖AI can revolutionize your business, but it all starts with a solid data strategy. Wondering what that involves? I always start at the end and work backward: 1. Objective (Use Case): Define what you want to achieve. 2. Technology Required: Decide if you need an AI app (off-the-shelf), a custom ML algorithm, or something else. 3. Data Required: Identify the data you need. 4. Data Readiness: Assess if your data is ready for use. 5. Necessary Changes: Determine what changes are needed to make your objective a success.If you're unsure where to start, we can help! Plus, there are grants available to support your AI journey. Let's get your business AI-ready! 🚀#DigitalTransformation #AI #Modernization #SMBSuccess #DataStrategy #iTransform #GrantsAvailable
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Jeffrey Fleischer
GTM Lead at Athena Intelligence
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Athena Insights Vol. 4The future of AI isn't in new apps -- it's in the tools you already use every day.Here's a reality check: The average knowledge worker spends 4 hours in their email inbox daily. That's where the REAL opportunity for AI transformation lies.The conventional wisdom said we needed to retrain workers on new AI platforms. We were wrong. Dead wrong.Let's flip the script:* Instead of forcing users to learn new interfaces, embed AI capabilities into their existing workflow* Rather than creating AI silos, integrate intelligence directly into communication channels* Focus on augmenting familiar tools instead of replacing them with shiny new solutionsAI adoption happens naturally when it feels invisible. The most successful implementations are the ones users barely notice.This isn't just about convenience - it's about MASSIVE competitive advantage. Companies that deploy AI through existing channels see adoption rates 3-4x higher than those requiring new platforms.How are you meeting your users where they are? Or are you still expecting them to come to you?
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Willem Cierenberg
Software Developer | Hybrid Azure Cloud and On-Premises Integration | Server and Network Administration | Database Administration | C++ | C# | Python | JavaScript
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My personal AIImagine an AI that's deeply personalized and tailored to your work, containing knowledge relevant to everything you’ve ever created. This AI would have access to your emails, documents, and data, becoming a powerful tool that understands your needs. Now, imagine a large language model (LLM) like this seamlessly integrated into your daily workflow, available in your everyday apps without the need for a web browser. It could suggest solutions, assist with tasks, and offer insights instantly. The possibilities of boosting productivity and efficiency are immense when AI becomes part of your routine, unlocking the full potential of your work.#AIinWorkflows #ProductivityBoost #InnovativeTech
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Matthew Jacobs
Founder @ AiVoy | Helping Short-Term Rentals + Serviced Accomodation automate communication with AI.
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I came across an interesting Reuters article recently about AI agents and how they’re set to dominate AI trends in 2025.But it got me thinking—does everyone know what AI agents actually are?Simply put, AI agents are tools that can independently complete tasks, not just assist you. Unlike traditional AI that waits for commands, these agents can:✅ Plan what needs to be done.✅ Take action across apps, tools, or platforms.✅ Adapt as they gather more information.Imagine this: Instead of asking an AI tool to draft an email, you tell it to “schedule a meeting with Client X.” The AI agent finds a time, drafts the email, sends it, and updates your calendar—all without further input from you.It’s not sci-fi—it’s already happening. Companies are building AI agents that handle customer support, analyse financial data, and even write code.The potential is huge, but it raises questions, too: How do businesses integrate these tools responsibly? What tasks should we automate—and what still needs the human touch?AI agents are coming fast, and 2025 could be the year they take off.Have you come across AI agents in action?#AI
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Presspool.ai
415 followers
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𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀: 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗙𝗲𝗲𝗱𝗯𝗮𝗰𝗸 𝗕𝗲𝘀𝘁 𝗠𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗼𝗳 𝗚𝗲𝗻𝗔𝗜An article published in Harvard Business Review argues customer-feedback analysis offers the most likely AI app for positive ROI. https://lnkd.in/gDZqHxXi
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Mainul Hossain
Founder & CGO of Fintech Pen: Reach 10 Million Targeted Client With Organic Content.
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How to Design an AI Marketing Strategy?In order to realize AI’s giant potential, CMOs need to have a good grasp of the various kinds of applications available and how they may evolve. This article guides marketing executives through the current state of AI and presents a framework that will help them classify their existing projects and plan the effective rollout of future ones. It categorizes AI along two dimensions: intelligence level and whether it stands alone or is part of a broader platform. Simple stand-alone task-automation apps are a good place to start. But advanced, integrated apps that incorporate machine learning have the greatest potential to create value, so as firms build their capabilities, they should move toward those technologies.Follow For More : Fintech Pen#aiinmarketing#digitalmarketing#aiindigitalmarketig#fintechmarketing.
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