Neel Mani的动态

Check the podcast on the Paper : A Survey on Large Language Model based Autonomous Agents Youtube : https://lnkd.in/gEg7-_fz Spotify : https://lnkd.in/gHuvwvb4 ?? Discover the future of AI! ?? This survey paper breaks down the revolutionary impact of Large Language Models (LLMs) on autonomous agents. From enhanced memory and planning strategies to cutting-edge applications in social sciences, engineering, and beyond, this paper covers it all! ?? Dive deep into: - A unified framework for LLM-based agents. - Key challenges like role-playing and human alignment. - Future research directions in AI! Read more here: https://lnkd.in/gy6tU-x3 #AI #AutonomousAgents #LLM #MachineLearning #FutureOfWork #AIResearch #Innovation #Tech #GenAI #NLP

In the ever-evolving world of AI, understanding different types of language models is crucial. Here's a quick rundown: #SimplifyingLLMs #Post18 1. Base Models: The foundation, trained on vast amounts of text. (e.g., GPT-3, BERT) 2. Instruction-Tuned Models: Tailored to follow specific instructions. Perfect for versatile AI assistants. 3. Chat-Tuned Models: Optimized for conversations. Ideal for chatbots and interactive AI. 4. RLHF Models: Aligned with human preferences. Safer and more helpful AI systems. 5. Constitutionally-Aligned Models: Constrained by predefined rules. Ensures ethical behavior. 6. Mixture of Experts (MoE) Models: Multiple specialized sub-networks. Efficient for diverse, large-scale tasks. Choosing the right model depends on your specific needs. Often, a combination works best for creating powerful, versatile, and responsible AI systems. #ArtificialIntelligence #MachineLearning #NLP #AIEthics #SimplifyingLLMs #Post18

Thrilled to announce I've completed the "Generative AI with Large Language Models" course by DeepLearning.AI! This challenging journey immersed me in the fascinating world of LLMs, exploring their technical foundations and practical applications. https://lnkd.in/eGTNfptA #AI #artificialintelligence #GenerativeAI #Data #Innovation #NLP #technology

Amazon unveils BASE TTS, a groundbreaking 980M parameter LLM with 'emergent abilities' Amazon researchers announce the development of BASE TTS, the largest text-to-speech model to date, boasting 980 million parameters. Trained on up to 100,000 hours of public domain speech data, the model exhibits remarkable versatility and robustness, particularly on challenging test sentences containing complex lexical and paralinguistic features. While further research is planned to optimize model size, BASE TTS offers promising advancements for conversational AI, with its lightweight and streamable design enabling transmission across low-bandwidth connections. Read More: https://lnkd.in/ewNyHf3Z #TextToSpeech #LLM #AI #Innovation #Technology #Research #SpeechRecognition #NLP #ArtificialIntelligence #ConversationalAI #ModelTraining #TechNews #EmergingTech #IndustryArticle

AI first is about centering AI in everything from product design to business processes. In an "AI-first" approach, AI is not an add-on but a fundamental element shaping the overall strategy and operations. DAAS LABS along with SCIKIQ is building an Ai-First future and Organisations. Collaborate with us to know how we can help you build an AI first Enterprise. write to us at [email protected] #Aifirst #Artificialintelligence #AI #GenerativeAI #NLP #Dataengineering #Datascience #DAASLABS #DAAS #SCIKIQ #Smartcities #Data #Product #Tech #Technology

In the race to build smarter AI, the focus has been on training bigger models. But I believe the future lies in inference over fine-tuning. Retrieval-Augmented Generation (RAG) enables AIs to dynamically "look up" information from vast knowledge bases at inference time, rather than relying solely on training data. This results in more knowledgeable, adaptive AI that can efficiently tackle a wider range of tasks without the need for retraining. I’ve heard the arguments for fine-tuning but I’m just not convinced. Smarter inference for smarter AI - what do you think? #AI #MachineLearning #ArtificialIntelligence #DeepLearning #NLP #Tech #Innovation #SmartAI #Inference

?? RAG Basics: A Quick Overview ?? Retrieval-Augmented Generation (RAG) is a powerful AI approach that combines the best of two worlds: retrieval and generation. Instead of relying solely on pre-trained models, RAG dynamically retrieves relevant information from external sources to enhance the quality and accuracy of generated responses. How does it work? 1. Retrieve: The model searches for and pulls in contextually relevant documents or data. 2. Generate: It then uses this data to craft more informed, accurate, and context-aware responses. This hybrid approach is transforming AI applications, making them more reliable and contextually aware. ?? ?? Free Infographic: Want to dive deeper? Check out our free infographic that breaks down the RAG process step-by-step! #AI #MachineLearning #NLP #ArtificialIntelligence #Innovation 4Enlight, AI Innovation Lab, AI Research Lab, Advanced Prompt Engineering

?? Unlock the Power of Large Language Models (LLMs)! ?? LLMs are revolutionizing the way we understand and generate human language. These cutting-edge AI tools are pushing the boundaries of what’s possible in industries like customer service, content creation, healthcare, and more. ?? Core Concepts You Should Know: - Vector Databases: Manage and retrieve high-dimensional vector data for efficient searches. - Retriever-Augmented Generation (RAG): Combines retrieval and generation to deliver accurate, contextual responses. - Fine-Tuning: Tailors pre-trained models to specific tasks or domains, enhancing performance. - LLM Agents: Autonomous systems that perform tasks and engage in dynamic conversations. - Deploying LLMs: Ensuring models are integrated and operational in real-world applications. ?? Want to dive deeper into these concepts? I've compiled a PDF that explains each of these key ideas in more detail. You can read the document below to explore how LLMs are shaping the future of AI! #AI #MachineLearning #LLMs #DataScience #Innovation #LLMAgents #ArtificialIntelligence #NLP #Tech #FutureOfWork #DeepLearning

Just finished an interesting AI course “Generative AI: Working with Large Language Models”: https://lnkd.in/gHdTkveu #generativeai #largelanguagemodels #naturallanguageprocessing #transformermodels.

Just finished the course “Generative AI: Working with Large Language Models” by Jonathan Fernandes!?? This immersive journey delved deep into the world of AI and language generation,? https://lnkd.in/dfJkeBBG #generativeai #largelanguagemodels #naturallanguageprocessing #transformermodels?#AI #GenerativeAI #LanguageModels #ArtificialIntelligence #ContinuousLearning