Gen AI Log - Day 60 Is anyone else feeling this? The AI story everyone is telling is about billion-dollar models and endless computing power. It's a world that feels out of reach for most of us. But when it comes to business, a model's generic training data is useless if it doesn't understand your specific needs. That’s the real challenge. The paper confirms this, stating that most current AI agents are "overengineered with heavyweight LLMs." This is where the emergence of small language models (SLMs) and tools like RAG comes in. They hit the nail on the head. These solutions are practical because they can be tailored to a business's specific context, yielding actual, measurable outcomes. Because at the end of all the hype, what matters is whether AI is actually helping a business on the ground. Paper link: https://lnkd.in/dWMNJB_v #AI #MachineLearning #SLM #LLM #AIAdoption #Business #Tech #0to100xengineers #100xEngineers
The Limitations of Billion-Dollar AI Models for Business
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🚀 Until yesterday, the world was obsessed with LLMs. Today, the conversation is shifting towards SLMs (Small Language Models). Why? Because the future of AI isn’t just about building the biggest models — it’s about making them smarter, faster, and more efficient. SLMs bring: ⚡ Lower latency & compute costs 🔒 Easier deployment on edge devices with stronger privacy 🎯 Task-specific adaptability (instead of “one-size-fits-all”) 🌍 Democratization of AI — not everyone needs a 500B parameter model to create impact In other words: the next big thing in AI might actually be smaller. Curious to hear — do you think SLMs will complement LLMs, or eventually replace them in most business applications? #AI #LLM #SLM #ArtificialIntelligence #Efficiency
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SLMs are the real future of Agentic AI—small, smart, and unstoppable. While giant LLMs grab all the headlines, the real future of agentic AI lies in small language models (SLMs). ✅ Faster, cheaper, and easier to deploy ✅ Tuned for specific domains → higher accuracy ✅ Energy efficient → sustainable AI adoption As businesses demand practical, real-world AI agents, SLMs will become the backbone — delivering agility without the heavy cost of massive models. 💡 The next wave of innovation isn’t about size, it’s about smart specialization. 👉 Do you think small language models will outpace LLMs in enterprise adoption? #AI #AgenticAI #FutureOfWork #LLM #SLM
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🚀 Revolutionizing AI with CAG (Cache Augmented Generation) 🧠⚡ In the world of LLMs, efficiency and context are everything. Enter CAG – Cache Augmented Generation 🔁📚 A game-changer that combines the power of language models with the speed of retrieval systems. 🔍 What it does: ✅ Caches previous responses ✅ Reuses relevant outputs intelligently ✅ Boosts performance while reducing compute costs ✅ Enhances accuracy, speed, and scalability 💡 Perfect for applications like: 📄 Document Q&A 📈 Business intelligence 🤖 Chatbots 🧾 Enterprise search As we scale AI systems, CAG is becoming a vital strategy to make them faster, cheaper, and smarter. 🛠️⚙️ #AI #CAG #LLM #CacheAugmentedGeneration #MachineLearning #Efficiency #Innovation #GenerativeAI #FutureOfWork #TechTrends
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The rise of 'AI slop', has created unexpected economic opportunities, demonstrating the evolving relationship between human creativity and machine automation. Read our take on how organisations can harness AI effectively whilst maintaining the human touch to combat AI slop https://lnkd.in/eefG3GD9
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This week's AI press digest explores critical trends impacting the AI industry, including Elon Musk's lawsuit alleging AI market monopolization, China's advancement with the open-source GLM-4.5 model, and the escalating talent war for AI researchers. These developments have significant business implications. Companies must monitor antitrust developments and talent acquisition strategies to leverage AI's transformative potential. Stay informed with our analysis: https://lnkd.in/eh3Brjcn. #AI #ArtificialIntelligence #MachineLearning #Innovation #AITalent #ChinaAI
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Had the privilege of learning from Ms. Drishti Wali,(Software Engineer at Ion Health)in an insightful session on the evolving landscape of Large Language Models (LLMs) and Agentic AI. 🔑 Key takeaways that stood out for me: LLMs are no longer just “text predictors” — they are becoming reasoning engines that can adapt across domains. Agentic AI is about making AI more goal-driven and autonomous, moving beyond passive assistance to active problem-solving. The shift from chatbots ➝ agents marks the next big leap in how organizations will leverage AI. Real-world adoption depends on balancing capabilities vs. risks (bias, security, transparency). This session was a reminder that if you want to stay relevant in the AI era, you must: ✅ Understand how LLMs work at a conceptual level. ✅ Keep track of where agentic AI is headed. ✅ Build a mindset of adapting with AI, not resisting it. Avinash Dara #CCBP #NxtWave
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The AI Ecosystem Era Begins 💡 Large Language Models (LLMs) are rapidly becoming commoditized. The focus in AI competition is no longer just about the foundational model itself. The real battleground is now about who can build the most robust and valuable ecosystem around these powerful tools. What implications does this strategic shift hold? * ⚙️ Drives focus on practical, business-specific AI solutions. * 📈 Creates new competitive arenas for platform providers and integrators. * 💡 Accelerates innovation in data handling, reasoning, and application layers. Article Link: https://lnkd.in/epdbJ76X Is your organization prepared for the AI ecosystem competition, or are you still chasing the 'best' base model? #AI #LLM #GenAI #AIEcosystem #BusinessAI #AIStrategy
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🚀 What makes an AI system an Agent? AI is evolving fast! We are moving from static models to dynamic systems that perceive, plan, and act in the real world. But where do we draw the line between a powerful Large Language Model (LLM) and a true AI Agent? In my upcoming presentation, I’ll unpack: 🔹 The 5-step loop that defines an agent’s intelligence 🔹 The levels of agentic capability (from tool-using problem solvers to collaborative multi-agent systems) 🔹 Why the future of AI lies in teams of specialized agents working together 🔹 The next frontier: personalized, embodied, and economy-shaping agents What makes an AI system an Agent? 💡 If you’ve ever wondered “When does AI stop being just smart software and start acting like an agent?”., then this session is for you. 👉 Stay tuned for insights that will shape how we build, deploy, and trust the next generation of AI. Please comment "include me" for more info #AI #Agents #ArtificialIntelligence #FutureOfWork #TechWithTravis
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#AutoTwinNews 🔔 🤖 𝙒𝙝𝙖𝙩 𝙢𝙖𝙠𝙚𝙨 𝘼𝙜𝙚𝙣𝙩𝙞𝙘 𝘿𝙞𝙜𝙞𝙩𝙖𝙡 𝙏𝙬𝙞𝙣𝙨 𝙪𝙣𝙞𝙦𝙪𝙚? 🆕 In our latest article, our IBM Research partners explain how AI systems powered by large language models can show unpredictable behavior—and how tools like process discovery and causal discovery can help make them more ✅ reliable and 💎transparent. Dive in » https://lnkd.in/d_WwT3pG to learn 💡 more! ✍️ Fabiana Fournier & Lior Limonad #digitaltwins #AI #processmanagement #business #horizoneu #research
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