"Small Data, Smart Models: The Key to Effective SLMs"

As Large Language Models (#LLMs) become core to enterprise AI strategies, context integration has emerged as a key differentiator for relevance, accuracy, and performance. Our latest insight breaks down the leading approaches: 🔹 In-Context Learning (ICL): Injecting context directly into the prompt 🔹 Fine-Tuning: Tailoring models to specific tasks and Domains 🔹 Retrieval-Augmented Generation (RAG): Enriching responses with real-time data 🔹 Hybrid & Multi-method: Combining approaches for greater flexibility and control These methods are shaping how businesses deploy scalable, secure, and intelligent AI solutions. Have a look: https://okt.to/6ZDzMJ Get in touch: Abhigyan Malik Karthi P #LLMs #EnterpriseAI #GenerativeAI #ContextIntegration #AIInnovation #EverestGroup #MachineLearning #RAG #AIModels

As Large Language Models (#LLMs) become core to enterprise AI strategies, context integration has emerged as a key differentiator for relevance, accuracy, and performance. Our latest insight breaks down the leading approaches: 🔹 In-Context Learning (ICL): Injecting context directly into the prompt 🔹 Fine-Tuning: Tailoring models to specific tasks and Domains 🔹 Retrieval-Augmented Generation (RAG): Enriching responses with real-time data 🔹 Hybrid & Multi-method: Combining approaches for greater flexibility and control These methods are shaping how businesses deploy scalable, secure, and intelligent AI solutions. Have a look: https://okt.to/4U0dAC Get in touch: Abhigyan Malik Karthi P #LLMs #EnterpriseAI #GenerativeAI #ContextIntegration #AIInnovation #EverestGroup #MachineLearning #RAG #AIModels

🚀 Highly effective AI agents arent simply powered by a solitary model. Instead, they leverage the strength of a diverse ecosystem of Large Language Models or LLMs. From GPT, leading the pack with contextual text generation, to MoE for expert routing, VLM and HRM specializing in vision-language fusion and structured reasoning respectively, each type plays a vital role in propelling the force of intelligent automation. Its a fascinating landscape to delve into as each model contributes to a unique piece of the AI puzzle. Introducing 8 crucial types of LLMs that are paving the way for next-gen AI agents. These innovative tools are pushing the envelope, reinventing how AI operates and bringing us closer than ever to the future of work. Want to know more about how these groundbreaking models are reshaping the face of AI and the possibilities they open up for business and technology? Visit our website www.jaiinfoway.com to delve deeper into the future of AI, enabled by these cutting-edge LLMs. How do you see these models reshaping your industry in the near future? Let us know in the comments.👇 #AI #LLMs #AIagents #FutureOfWork #GenerativeAI #Jaiinfoway

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

Are today's large language models truly equipped to navigate the complexity of real-world agentic environments—or are they merely sophisticated pattern matchers struggling to execute purposeful actions? This study from Tongyi Lab and Alibaba Group introduces AgentScaler, a novel framework designed to reshape how we train LLMs for agentic intelligence. Unlike traditional end-to-end fine-tuning, AgentScaler employs a two-phase strategy that significantly enhances function-calling efficiency. In phase one, the model is pre-tuned on a diverse set of tool interaction trajectories. In phase two, task-specific fine-tuning refines these capabilities, resulting in up to 32% better tool usage accuracy and 27% faster convergence, according to the research. For AI development teams and research labs, this means a more structured path to building scalable, reliable agent systems—reducing the guesswork and computational overhead traditionally associated with training agentic behaviors. AgentScaler's modular approach not only improves performance but also offers interpretability into how models learn to use tools. As enterprise AI strategies evolve, infrastructural innovations like AgentScaler could be pivotal in bridging the gap between experimental AI and real-world deployment. How might frameworks like this redefine your organization's approach to AI scalability and agent intelligence? #AIResearch #LLM #AgentIntelligence #MachineLearning Source: https://lnkd.in/erh3cnF4

🚀 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

🚀 The AI Race Shifts: It's All About the Ecosystem Large Language Models (LLMs) are rapidly becoming commoditized. The focus in AI competition is moving from core model performance to building comprehensive, problem-solving ecosystems around these foundational technologies. How will this ecosystem shift redefine AI strategy? * Seamless integration: Tailored solutions for specific business operations. * Data handling advantage: Unlocking competitive edge through smarter data orchestration. * Innovation potential: Driving new services and value beyond raw model outputs. This transition highlights the critical need for a holistic view of AI adoption, focusing on real-world utility and deep integration. Read more: https://lnkd.in/epdbJ76X Is your strategy shifting towards an ecosystem-first AI reality? #AI #LLM #GenAI #AIEcosystem #BusinessAI #AIStrategy

Exciting Times Ahead for AI & Business As the tech community eagerly anticipates the release of GPT-6, Sam Altman’s recent hints about the next-gen model are incredibly promising. From improved natural language understanding to more powerful, context-aware capabilities, GPT-6 could significantly enhance how businesses use AI, transforming everything from customer service to decision-making processes. At Spendkey, we’re always looking for innovative ways to integrate cutting-edge AI into the financial ecosystem. With advancements like these, the potential for more innovative procurement technology solutions, automated processes, and even more intuitive interactions is limitless. As we continue to build on AI-driven technology, the arrival of GPT-6 marks an exciting new chapter, bringing us one step closer to more intelligent, dynamic systems that can solve complex challenges at scale. Looking forward to the next phase of innovation and how it will shape the future of business operations, especially in the procurement technology sector. #AI #Innovation #MachineLearning #GPT6 #Procuretech #Procurement #BusinessIntelligence #TechInnovation #ArtificialIntelligence #Spendkey

Nathan Clark, ML engineer on #TeamNoblis, presented research today at the New England Mechanistic Interpretability (NEMI) workshop to showcase Noblis’ groundbreaking work on making Large Language Models more efficient through feature steering. We're achieving remarkable results by:   ✅ Adding tiny learned vectors inside an LLM that nudge it to write shorter code without altering original weights ✅ Testing with unit-tested coding tasks for clear pass/fail evaluation ✅ Creating a "dial" effect to control which layers to modify and by how much   Why this matters: - Lower compute costs and faster results compared to full fine-tuning - Clear, auditable control of model behavior - Builds trust through explainable AI interventions - Provides valuable insights for governance and safety guardrails   Our benchmark provides an objective yardstick for measuring both correctness and token savings quantitatively.   We are excited about the team's contributions to more interpretable and efficient AI!   To learn more about our research and capabilities in AI and to contact our experts, visit https://noblis.org/ai/.   #AI #MachineLearning #LLM #InterpretableAI #ArtificialIntelligence #TechInnovation

𝐃𝐞𝐦𝐲𝐬𝐭𝐢𝐟𝐲𝐢𝐧𝐠 𝐭𝐡𝐞 𝐀𝐈 𝐬𝐭𝐚𝐜𝐤 𝐢𝐬 𝐭𝐡𝐞 𝐟𝐢𝐫𝐬𝐭 𝐬𝐭𝐞𝐩 𝐭𝐨𝐰𝐚𝐫𝐝 𝐦𝐚𝐬𝐭𝐞𝐫𝐲. To effectively integrate AI into your operations, it's crucial to understand its foundational components. At its core, the AI stack today is made up of five core capabilities that work together to deliver results: ➡️ Large Language Models (LLMs): The communication engine. ➡️ Toolkits: The methods and skills needed to accomplish specific tasks. ➡️ Agents: The orchestrators that use rules and data to pursue a goal. ➡️ Data: The high-quality ingredients needed for any successful AI application. ➡️ Surfaces: The integrated interfaces where AI goes to work. Understanding how these layers interact is essential for any leader looking to move beyond experimentation and into the practical "industrialization" of AI. My latest reflection, "From Wow to Now," provides a clear breakdown of this stack to help you build a stronger, more informed AI strategy. Which of these five capabilities presents the biggest challenge or opportunity for your organization? Read the full reflection on Substack: https://lnkd.in/eWzfmAkq and subscribe for more insights. #AI #BusinessTransformation #Innovation #TechStrategy #DoGoodByDoingBetter