Ibrahim Sobh - PhD’s Post

Unlocking Creativity with AI: Understanding Temperature, Top-K, and Top-P in LLMs   When using Large Language Models (LLMs), controlling how creative or predictable the output is comes down to tweaking three key parameters : Temperature: Adjusts how random the model's output is. Low temp = more predictable, high temp = more creative! Top-K: Limits how many words the model considers. Smaller values keep it safe, larger values open up more options. Top-P: A smarter approach! It selects tokens until a certain probability is reached (e.g., top 90%).   #LLM  #GenerativeAI Source- https://lnkd.in/gEBBhZhy

Meta AI introduced #Llama3 - the latest generation of their #opensource large language model (LLM) family. The model is available in 8B and 70B parameter sizes, each with a base and instruction-tuned variant. Get all the insights you need via #InfoQ: https://bit.ly/3Uyqpq8 #LLMs #GenerativeAI #AI

Boost Language Model Efficiency with #KV #Cache #Quantization, By reducing memory usage without sacrificing much accuracy, this method paves the way for faster inference and more accessible #LLM deployment. read more: https://lnkd.in/dNeACbjK #AI #MachineLearning #LLM #Quantization #Efficiency #HuggingFace #NaturalLanguageProcessing #TechInnovation #DeepLearning #neevcloud #neevai #ALML #gpucloud

Imagine a large language model taking an open-book test. 📚 This is similar to how Retrieval Augmented Generation (RAG) works. #RAG integrates the generative abilities of LLMs with data retrieved from specified sources. Discover how this combination ensures information remains up to date and reduces the likelihood of inaccuracies. https://bit.ly/4e98VcP #AI

New Diff Transformer for Improved Machine Learning Accuracy… Transformers often struggle with paying attention to irrelevant information, which can reduce their accuracy in tasks like text summarization or question answering. To address this issue, Microsoft researchers introduced the Diff Transformer in a recent paper. This innovative approach leverages a differential attention mechanism, where instead of calculating attention scores uniformly, it subtracts two attention mappings. By doing this, it eliminates noise and irrelevant information, promoting sparse attention patterns. Experimental results show that Diff Transformer not only performs better in tests but also offers significant benefits in real-world applications. For example, in handling long texts, it has shown notable improvements in retrieving key information and reducing hallucinations in language models. #AI #MachineLearning #NaturalLanguageProcessing #Transformers #MicrosoftResearch #Innovation

🌐✨ Exploring AI and Entity Matching: Vectorization, ML Models, and LLMs! In the realm where artificial intelligence meets entity matching, the magic happens through advanced techniques like vectorization, machine learning models, and even Large Language Models (LLMs). 🤖🔍 For your products, the benefits are clear. Integrating these technologies enhances accuracy in identifying and linking related data points. Imagine a system that accounts for typos, missing information, language barriers, and more, yet is still able to connect the information seamlessly. These advancements elevate user experience, drive efficiency, and reduce operational costs. With AI-driven entity matching, your products become smarter, more intuitive, and exceptionally effective at meeting customer needs. 🚀💡 #runtimerevolution #AI #entitymatching #vectorization #machinelearning #LLMS #innovation

"The right analogy for AI is not humans, but an alien intelligence with a distinct set of capabilities and limitations. Just because it exceeds human ability at one task doesn’t mean it can do all related work at human level. Although AIs and humans can perform some similar tasks, the underlying “cognitive” processes are fundamentally different," writes Ethan Mollick. https://lnkd.in/gpw94Rxh #ai #genai #generativeai

Could this be the AI breakthrough we've been waiting for? 🌐 A mysterious new model promises unlimited modalities—but what does that mean for the future of technology? Unveiling 'One Peace'—let's explore this game-changing development together. #AI #Innovation #TechMystery https://lnkd.in/dSJdRbHN

Hello All, Hello All, I was writing this blog because people like me are confused about the #AI terms, so to make sure everyone is on the same page I wrote this blog. I covered what #AI Agents, #RAG (Retrieval-Augmented Generation), #GenerativeAI, and #GPTs and how they are interconnected concepts in the realm of artificial intelligence. To know more: https://lnkd.in/gzZZZHXm #rag #genai #AI #AIAgents #opensource #GPTs

Small language models (SLMs) are specialized, making them easier to train, faster to operate and lighter on the wallet than larger-scale AI models. Does this shift towards specialization sound familiar? Maxime Vermeir shares with Intelligent Document Processing Community that the industry trend towards purpose-built solutions is exactly what buyers in the market are expecting today. Read more: https://hubs.li/Q02rnkgy0 #LargeLanguageModels #LLMs #SmallLanguageModels #SLMs #AI #GenerativeAI #ArtificialIntelligence #IntelligentAutomation #IDP #IntelligentDocumentProcessing