Michal Barabanow’s Post

📣Happy to share that Amazon Titan Image Generator is now generally available in Amazon Bedrock, giving you an easy way to build and scale generative AI applications with new image generation and image editing capabilities, including instant customization of images. 🙌📷 #Amazon Bedrock #Amazon #Artificial Intelligence #Generative AI

📣Happy to share that Amazon Titan Image Generator is now generally available in Amazon Bedrock, giving you an easy way to build and scale generative AI applications with new image generation and image editing capabilities, including instant customization of images. 🙌📷 #Amazon Bedrock #Amazon #Artificial Intelligence #Generative AI

📣Happy to share that Amazon Titan Image Generator is now generally available in Amazon Bedrock, giving you an easy way to build and scale generative AI applications with new image generation and image editing capabilities, including instant customization of images. 🙌📷 #Amazon Bedrock #Amazon #Artificial Intelligence #Generative AI

📣Happy to share that Amazon Titan Image Generator is now generally available in Amazon Bedrock, giving you an easy way to build and scale generative AI applications with new image generation and image editing capabilities, including instant customization of images. 🙌📷 #Amazon Bedrock #Amazon #Artificial Intelligence #Generative AI

Just as we were catching our breath on Claude 3 Opus arriving on Amazon Bedrock, here we go again, this time it's Meta's Llama 3 model - designed for you to build, experiment, and responsibly scale your generative artificial intelligence (AI) applications; now with improvements in reasoning, code generation, and instruction. #generativeai #amazonwebservices #ai #llama3 #aws https://lnkd.in/enxvGPWA

Hello everyone, 👋 Ever thought about how you could amp up the performance of your large language models using Amazon SageMaker Large Model Inference? Here's something incredibly insightful that could help! 🚀 The breakthroughs in AI have given us large language models (LLMs), but serving these models efficiently can be quite challenging. But no worries! This captivating article outlines a highly efficient way to improve not just the throughput but also the latency of Falcon-40B models using Amazon SageMaker. 🎯 Some key takeaways that blew my mind: 1) Continuous Batching: Rolling batching is a hit right now, and understanding how it optimizes the deployment of LLMs is mindboggling! 2) SageMaker LMI: A fantastic look into how you can use it to deploy the Falcon family of models. Also, gain insights into understanding the configuration parameters for real-world application 👀 3) Language Model Decoding: Deep-dive into the concept of autoregressive decoding process in models like Falcon or GPT 🎓 In essence, the article is an enlightening read that offers a cutting-edge approach to LLMs using SageMaker LMI. Understand, implement, and witness the difference! 💡 Follow the link for this in-depth reading: https://lnkd.in/gr-iwPVs Let's keep pushing boundaries in AI, folks! And don't be shy, share your thoughts on this, I'd love to hear them.💭 #AmazonSageMaker #AI #MachineLearning #LargeLanguageModels #ContinuousBatching Cheers! 🖖 Casey Jones.

🚀 Exciting news! Learn how to harness the power of Amazon Titan models for image generation, editing, and searching with our latest blog post. Discover how the new Amazon Titan Image Generator model facilitates the creation of high-quality, realistic images from simple English text prompts, and explore the advanced AI capabilities that enable efficient, studio-quality image generation for various applications. We also delve into the Amazon Titan Multimodal Embeddings model, showcasing its ability to optimize search and recommendations by understanding text, images, or both. In this comprehensive post, we walk you through the process of using these models via the AWS Python SDK, providing code examples to demonstrate image generation, editing, and searching use cases. From creating custom images to leveraging semantic vectors for accurate search experiences, this post equips you with the tools and knowledge to leverage these groundbreaking AI technologies. Read the full blog post here: [Use Amazon Titan models for image generation editing and searching](https://ift.tt/RNxVG2O) #AI #imagegeneration #machinelearning #AWS #TitanModels

Ever wondered how the future of machine learning and AI could transform your business? Well, the future is here, and it's called Gemma! Available now in Amazon SageMaker JumpStart, Gemma models are setting the stage for a revolution in AI capabilities. Inspired by Google's Gemini models and developed by the brilliant minds at Google DeepMind, these models are not just powerful—they're designed to be lightweight and state-of-the-art. Whether you're dealing with 7 billion or 2 billion parameters, Gemma models are trained on up to 6 trillion tokens of text, showcasing unparalleled generalist capabilities in text domains. What's more, deploying and fine-tuning these models for your specific needs has never been easier, thanks to SageMaker JumpStart's comprehensive guide and resources. Dive into the world of Gemma models and discover how they can elevate your AI game. For a deeper understanding, check out the full article here: [https://lnkd.in/gBwXFcfq). Happy Thursday! In a nutshell, Gemma models, inspired by Google's Gemini models, are now accessible through Amazon SageMaker JumpStart, offering a lightweight yet advanced solution for AI development. These models, available in two versions, are designed for strong generalist capabilities in text domains. The article guides users on deploying and fine-tuning Gemma models within SageMaker JumpStart, highlighting the ease of leveraging pre-trained foundation models for various applications. #MachineLearning #ArtificialIntelligence #AmazonSageMaker #AWS Casey Jones

Document processing has witnessed significant advancements with the advent of Intelligent Document Processing (IDP). This post takes you through the synergy of IDP and generative AI, unveiling how they represent the next frontier in document processing. In this post, we discuss how to extend a new or existing IDP architecture with large language models (LLMs). #awscloud #aws #deeplearning #nlp #llms #llm #amazonbedrock #intelligentdocumentprocessing

Great work, Philipp Schmid! 🚀 The challenges of deploying large language models like Llama 2 on Amazon SageMaker with optimal latency and cost-effectiveness are significant, but your comprehensive benchmarking effort has provided valuable insights. It's impressive to see the analysis of over 60 different deployment configurations to identify the best strategies for various use cases, from cost-effectiveness to throughput and latency. The transparency and reproducibility of your benchmarking process, including sharing the GitHub repository, raw data, and processed data, set a high standard for ensuring the reliability of your findings. This not only benefits the community but also empowers companies to use Llama 2 efficiently and optimally for their specific requirements. Moreover, your explanation of the Hugging Face LLM Inference Container and Llama 2, along with the introduction of GPTQ, adds depth to the understanding of the technologies involved. I appreciate your dedication to providing specific recommendations based on the benchmark results, making it easier for organizations to make informed decisions regarding Llama 2 deployment. Your findings for cost-effectiveness, throughput, and latency will undoubtedly guide many in selecting the right configuration for their use cases. An outstanding contribution to the field, and I look forward to exploring your GitHub repository for more in-depth insights. Kudos to you and your team for this valuable work! 👏👏 #AI #MachineLearning #Benchmarking #Llama2 #AmazonSageMaker https://lnkd.in/ghU9Rbmd