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🚀 Welcome to the Era of Small Language Models (SLM) and Extreme Quantization 🔍 The world of AI is evolving rapidly, and we're witnessing a shift towards smaller, more efficient language models. These lightweight models, combined with extreme quantization techniques, are pushing the boundaries of performance and efficiency. Gone are the days of relying solely on massive models—now, we can harness the power of AI with reduced computational requirements, lower energy consumption, and faster inference speeds, all while maintaining high accuracy. This is a game-changer for industries looking to deploy AI at scale. #AI #MachineLearning #LanguageModels #Quantization #EfficientAI #DeepLearning #SmallModels #TechInnovation #AIOptimization

Is AI Thinking Shallowly? Yann LeCun’s Vision on What True Intelligence Requires 🌐🤖 Yann LeCun, a leading AI mind and Meta’s Chief Scientist, sees large language models (LLMs) as an impressive but incomplete path to real intelligence. While LLMs predict text sequences effectively, LeCun argues that true AI requires embodied understanding—interacting with and learning from the physical world. Consider this: LLMs, despite their vast data, have no real-world context. They can generate responses but don’t “experience” or anchor their knowledge in reality. Imagine a system that knows “walking” from text alone but has never taken a step. LeCun advocates for models like Joint Embedding Predictive Architectures (JEPAs) that process sensory data—visuals, spatial cues, sounds—to form a more abstract and versatile understanding. For example, a JEPA-driven self-driving car would abstract the world around it without getting bogged down by details irrelevant to safety, navigating effectively by “seeing” holistically. Our takeaway? Intelligence is more than prediction. Real understanding involves context, layered thinking, and the ability to act based on the world’s complexity. We need AI that “gets” the world, not just simulates it. The future of AI isn’t just about more data—it’s about smarter, human-like interaction with reality. What’s your perspective on the balance between prediction and understanding in AI? #AI #FutureOfAI #YannLeCun #EmbodiedIntelligence #OpenSourceAI #AGI

Are Small Language Models the next evolution for Generative AI? In the fast-evolving world of AI and machine learning models, a new contender is making waves: SLMs. This isn't just another tech buzzword. SLMs, or Specific Language Models, are being hailed for their nimbleness and efficiency over their broader counterparts, the LLMs (Large Language Models). Why does this matter? In a realm where precision, adaptability, and resource efficiency are key, SLMs stand out. They're not just another step in the evolution of computing; they're a leap towards more tailored, effective AI solutions. The advantages of SLMs over LLMs are clear, marking a significant shift in how we approach and deploy AI models. For professionals and businesses invested in the cutting edge of AI and machine learning, understanding this shift isn't just beneficial; it's imperative. The future of AI is getting more specific, and it's an exciting journey to be a part of. --- Are you curious to find valuable resources and more interesting AI content? Dive into our blog on www.ellogy.ai #ellogy #contentgeneration #AIsoftwaredevelopment #AIbusinessanalyst Check this out: https://lnkd.in/dA3VZwCE

Exciting times in AI! 🚀 Can't wait to see what the Llama 405B model with reflection tuning will bring to the table. Open-source innovation is pushing boundaries, with the 70B version already outperforming giants like GPT-4 and Claude 3.5. 🤯 Reflection tuning is a game-changer, allowing models to self-assess and refine their outputs iteratively. Here's a quick breakdown: 💡 How Reflection-Tuning Works: • Self-Assessment: The model evaluates its own output for quality and correctness • Refinement: It provides self-feedback and revises its response • Iterations: Multiple rounds of reflection lead to improved reasoning and coherence This community-driven approach showcases the power of open-source in AI development. Imagine the possibilities with 405B parameters and refined reflection capabilities! Are we on the cusp of a new era in language models? What are your thoughts on this breakthrough? #AI #MachineLearning #OpenSourceAI #LLMs #TechInnovation

🚀 Embracing the Power of Quantization in AI! 🌐💡 Large Language Models (LLMs) often pose a challenge with their extensive parameters and computations, translating to higher costs for businesses. Enter Quantization – the game-changer in making models deployable and cost-effective! Quantization, in essence, strikes a balance by compromising on representational power with effort on minimising the impact on performance. 📉✨  To illustrate, imagine time as a value: If the current time is 10:34:50 with 6 digits, quantizing to 4 digits simplifies it to 10:35, and further reducing to 2 digits gives us 11. Precision diminishes, but for certain use cases, it's a compromise we can afford. In the realm of AI, where float32 values can represent fraction of as small as 1e-45, the shift to INT8 allows us to represent values in the gap of 2^-8. we can only represent 255(2^8-1) numbers with the help of INT8 datatype🤖💪 Quantization is simple concept but it is tricky to maintain accuracy. #AI #Quantization #TechTalk

🟣 𝗛𝘂𝗺𝗮𝗻 𝗯𝗿𝗮𝗶𝗻𝘀 𝗮𝗿𝗲 𝗮𝘄𝗲𝘀𝗼𝗺𝗲. 𝗔𝗻𝗱 𝗔𝗜 𝘄𝗶𝗹𝗹 𝗯𝗲 𝘁𝗼𝗼. 𝗙𝘂𝘁𝘂𝗿𝗲 𝘁𝗲𝗻𝘀𝗲 🔮 Large language models are revolutionizing human-computer interaction, creating experiences that feel like real conversations. But are we really there yet? Do these machines really understand us? 🤔 In our latest article, 𝙏𝙝𝙚 𝙘𝙤𝙣𝙫𝙚𝙧𝙨𝙖𝙩𝙞𝙤𝙣𝙖𝙡 𝙛𝙪𝙩𝙪𝙧𝙚 𝙤𝙛 𝙥𝙧𝙤𝙢𝙥𝙩𝙨 by Gerardo Sanz, we dive deep into the current landscape of LLMs and explore where we truly stand today. At newspective, we are committed to exploring and implementing solutions that are both impressive and realistic. Our goal is to harness the full potential of LLMs in a functional and reliable manner, ensuring scalable success. What’s your take on the future of conversational AI? Share your thoughts in the comments! 🔗 Read the full article by following the link in the comments 🔗 #AI #LLM #ConversationalAI #TechInnovation

🌟 Exploring The tech behind agent workflows (technology)🌟 - Language Models & Knowledge: Meet your AI ally! Think GPT-4o and Claude 3—these big guns understand and generate human-like language, backed by vast text data for deep insights. - Retrieving & Generating: Need specifics? Enter RAG! It helps agents fetch up-to-date info from external sources, enhancing accuracy and relevance in responses. - Function Calling: Beyond talk, let's action! Agents tapping into APIs can fetch live data—picture weather updates or even complex calculations in real-time. - Fine-Tuning: Tailor-made excellence! Fine-tuning with specialized data boosts agent performance on specific tasks, ensuring it shines in its designated role. - Guardrails: Keeping it safe and sound! From rule-based filters to rigorous training, we ensure our agents stay on track, producing reliable and responsible outputs. Excited about the future of AI agents? Let's shape it together! 🚀 #AI #AgentEngineering #TechInnovation _________________ Hi, I'm Olivia Deka, your guide to all things AI! Join me as we explore cutting-edge technologies, discuss industry trends, and shape the future of artificial intelligence together. Follow me for insightful updates and let's innovate with AI! 🚀 #AI #Innovation #TechTrends

🚀 Unlocking Precision in AI: The Power of Retrieval-Augmented Generation (RAG) Have you ever wondered how AI models like Large Language Models (LLMs) quickly generate responses to general queries? It's all about their vast knowledge stored in parameters, enabling them to understand language patterns and respond at lightning speed. But what happens when you need specific, up-to-date information or a deep dive into a particular topic? That's where Retrieval-Augmented Generation (RAG) comes in. RAG is a game-changer in the world of AI. It enhances the accuracy and reliability of generative AI models by integrating real-time facts from external sources. This means that instead of relying solely on past data, AI models can fetch the latest information and use it to craft more precise and contextually relevant responses. Imagine having an AI assistant that not only understands general concepts but also provides insights and answers tailored to the latest developments in your field. That's the power of RAG. Whether it's answering complex questions, providing in-depth analysis, or delivering up-to-date information, RAG opens new doors for AI applications across industries. It bridges the gap between general knowledge and specialized expertise, making AI more versatile and valuable than ever before. As we continue to explore the frontiers of AI, RAG stands out as a crucial innovation that unlocks precision and reliability, paving the way for smarter and more effective AI solutions. #AI #RAG #GenerativeAI #Innovation #TechTrends #ArtificialIntelligence #MachineLearning #DataScience #LinkedInPost

🤔 LLM progress is slowing—what will it mean for AI? Ever feel like you're riding a wave of innovation, only to find it's not as massive as it once appeared? That's where we might be with large language models (LLMs). We've seen mind-blowing leaps like GPT-3 to GPT-4, but now the advances are feeling... less groundbreaking. 🚀📉 Here's a scoop from my perspective: This shift could mean a fascinating pivot in AI's journey. Imagine running a marathon, thinking every mile is a sprint. Then suddenly, you hit a steady pace. Does it mean the race is less thrilling? Nah, it just means we’ll start seeing new strategies and tactics unfold. That's where the excitement lies! 👉 For one, we'll likely witness a game of AI specialization. Rather than a one-model-does-all approach, we'll see tailored solutions—AI agents designed to suit specific needs and communities. It's like swapping a Swiss Army knife for a custom toolset built for precision and expertise! 🛠️ Got thoughts on what the future of AI might hold? Are you excited or concerned about this slowdown in LLMs? How do you think this will affect specialization in your industry? Let's chat! 💬 #AI #LLMs #Innovation #Specialization #FutureOfAI

🚀 FINANCIAL TIMES: Unlock Your Creative Potential with AI 🚀 Imagine having an AI assistant that can write captivating stories, create stunning visuals, and even code like a pro. This is what Generative AI and Large Language Models like GPT-4 can do for you. As a marketing and creative professional, you can spend more time on your big ideas and less on routine tasks. Companies like Google and OpenAI are offering tools to supercharge your creativity and productivity. But remember, with this power comes the need for responsible use. Let’s embrace AI revolution together and turn your boldest visions into reality. 🌟 This interactive Financial Times article will guide you on better comprehending how these latest tools are working to shape our future! #AI #Creativity #Marketing #FutureOfWork #GPT4 #Innovation #DigitalTransformation