Andy Jassy’s Post

Since the very inception of AWS in 2006, among the many differentiators, has been both the breadth of AWS capabilities and our pace of innovation. This AWS advantage remains true in the world of GenAI 18 years later. #genai #awsishow

With the latest news out yesterday, building applications with generative AI capabilities have never been easier with the addition of cutting-edge bedrock capabilities 🙂 . New features enhance ease of use and cost-effectiveness, allowing users to import custom models and leverage advanced features like RAG and knowledge bases. Updates include Meta's Llama 3 and Cohere's new models for diverse linguistic support, along with Amazon Titan models for cost-effective, high-quality image generation. Discover these powerful tools and join the growing number of users creating real-world GenAI applications. Get started today! https://lnkd.in/g4rkak47" #Bedrock #GenAIUpdates #GenAIInnovation

Andy Jassy, Matt Wood explained to us, in reference to the new version of Amazon Bedrock and its versatile features, that choosing an #AI model is similar to buying an outfit. Daring to summarize the excellent analogy expressed: both processes involve customization according to specific requirements, require expert knowledge (whether in adaptation or data science) and represent an investment in quality that promises long-term value. Like the detailed, iterative fitting process of a custom suit, selecting and refining an AI model requires continuous adjustments based on performance feedback to ensure optimal results tailored to the user's needs. I conclude with my response on this topic to Adam Selipsky's post: It is incredible to see how the set of services and tools offered by Amazon Bedrock grows and evolves with the speed that developers demand and require.

Having attended AWS London Summit last week, it was clear how #AWS are making #GenAI / #AI accessible in three main ways: (1) practical, relatable case studies, (2) ability to change and use custom models, enabling tailored, organisation-specific insights, (3) Role Based Access Control (#RBAC), with data #privacy and #security ready to use. Please reach-out if you'd like to explore how to take #GenAI concepts, get beyond the hype, and turn GenAI into practical solutions to protect customers, automate decision-making and/or reduce cost-of-operations.

Unleash the Power of GenAI with Amazon Bedrock!! Prepare to supercharge your business with the latest GenAI capabilities from Amazon Bedrock. This cutting-edge platform is redefining the way we harness the power of Generative AI, empowering customers to build high-quality, low-latency, and cost-effective applications with ease. Bedrock's newest features are a game-changer for GenAI enthusiasts. Seamlessly import your own models from SageMaker and S3, and leverage Bedrock's advanced capabilities like Retrieval-Augmented Generation (RAG), agents, Knowledge Bases (guardrails), inference deployment, and advanced customization. Plus, the new Model Evaluation tool ensures you select the best model for your needs by quickly assessing predefined evaluation criteria like accuracy and robustness. But that's not all – Bedrock is expanding its model offerings to include Meta's Llama 3 models and Cohere's state-of-the-art Command R and R+ models with advanced RAG capabilities in 10 languages. Whether you're looking to summarize text, classify data, analyze sentiment, translate languages, or generate code, Bedrock has you covered. Tens of thousands of customers are already building real-world, production-ready GenAI applications on this platform, and now it's your turn to unleash the power of GenAI. Explore the possibilities at https://lnkd.in/g4rkak47.

🚀🚀🚀 #hereataws #genai #amazonbedrock #launched Amazon Titan Embeddings is now generally available! Amazon Titan Embeddings is a text embeddings model that converts natural language text including single words, phrases, or even large documents, into numerical representations that can be used to power use cases such as search, personalization, and clustering based on semantic similarity. Optimized for text retrieval to enable Retrieval Augmented Generation (RAG) use cases, Amazon Titan Embeddings, enables you to first convert your text data into numerical representations or vectors and then use those vectors to accurately search for relevant passages from a vector database, allowing you to make the most of your proprietary data in combination with other foundation models (FMs)! Titan Embeddings supports more than 25 languages, including English, Chinese, and Spanish.

Amazon Web Services (AWS) introduces Titan Text, a cutting-edge family of large language models (LLMs) tailored for enterprise applications. Designed to assist with content creation, summarization, information extraction, and Q&A tasks, Titan Text operates through AWS Console and Bedrock API, simplifying the execution of complex prompts without the need for infrastructure management. Key Features: Diverse Applications: Text generation, dialogue, in-context learning, retrieval-augmented generation, orchestration, and customization. Customer-Centric Design: Titan Text Lite for cost-effective English language tasks, and Titan Text Express for advanced, multi-lingual capabilities. Effectiveness Measurement: Effective completions judged by human evaluators based on language quality, prompt adherence, and safety standards. Considerate Limitations: Titan Text's probabilistic nature means outputs require careful evaluation, particularly for consequential decisions. Design and Testing: Utilizes transformer-based generative machine learning for token inference. Controllable behavior influenced by training data, fine-tuning, and safety filters. Performance varies with customer application and use case, demanding personalized testing for optimal results. Commitment to Safety: #AWS prioritizes safety, aligning with Amazon’s Global Human Rights Principles. Continuous performance evaluation through diverse testing methodologies, including HELM benchmarks, proprietary datasets, and red-teaming. A leap in AI-driven solutions, Titan Text represents AWS's commitment to innovative, responsible, and customer-focused #AI development.

Are you looking to leverage the power of artificial intelligence in your AWS cloud services? Look no further, as I have compiled a comprehensive list of few AWS cloud services that offer AI capabilities. 🧠 Amazon SageMaker: #AIinAWS #AmazonSageMaker Amazon SageMaker is a fully managed service that provides developers and data scientists with the tools to build, train, and deploy machine learning models quickly. With built-in algorithms and frameworks, SageMaker makes it easy to incorporate AI into your applications. Amazon Rekognition: #AWSAI #AmazonRekognition Amazon Rekognition is a deep learning-based image and video analysis service that can identify objects, people, text, scenes, and activities in images and videos. It is perfect for applications that require visual analysis, such as facial recognition and content moderation. Amazon Polly: #AWScloudservices #AmazonPolly Amazon Polly is a text-to-speech service that uses advanced deep learning technologies to synthesize speech from text. It supports multiple languages and voices, making it easy to create natural-sounding speech for your applications. Amazon Lex: #AIcapabilities #AmazonLex Amazon Lex is a service for building conversational interfaces into any application using voice and text. It provides advanced deep learning functionalities for natural language understanding and speech recognition, enabling you to create chatbots and virtual assistants. Amazon Comprehend: #AWSAItools #AmazonComprehend Amazon Comprehend is a natural language processing service that uses machine learning to find insights and relationships in text data. It can analyze sentiment, detect entities, and extract key phrases from text, making it ideal for text analytics applications. Amazon Translate: #AIintegration #AmazonTranslate Amazon Translate is a neural machine translation service that provides fast and high-quality language translation for your applications. It supports multiple languages and can be easily integrated into your existing workflows. Amazon Forecast: #AWSforecasting #AmazonForecast Amazon Forecast is a machine learning service that generates accurate forecasts for your time-series data. It uses deep learning algorithms to automatically build and train forecasting models, making it easy to predict future trends. These are just few mentioned. With these AWS cloud services offering AI capabilities, you can take your applications to the next level and unlock the full potential of artificial intelligence. 💡 Stay ahead of the curve and start integrating AI into your AWS infrastructure today! #AWScloud #AIinnovation Which of these services are you most excited to try out? Let me know in the comments below! 👇 #AIinthecloud #AWSAIcapabilities

Exciting news from Amazon Bedrock! Amazon Titan Text Lite and Amazon Titan Text Express are now generally available. Amazon Titan Text Lite is a lightweight, efficient model designed for fine-tuning English-language tasks such as summarization and copywriting, offering a cost-effective solution with high customization capabilities. Whether you're in need of a cost-effective model for specific tasks or a versatile general-language model for a wide range of applications, Amazon Titan Text Lite has you covered. On the other hand, Amazon Titan Text Express is a powerful model suitable for advanced, general-language tasks such as open-ended text generation, conversational chat, and support within Retrieval Augmented Generation (RAG) and function calling. With multilingual support for over 100 additional languages in preview, Amazon Titan Text Express is poised to revolutionize the way we interact with machines. Visit AWS AI Service Cards – Amazon Titan Text to learn more: https://lnkd.in/gVdnVDdc #genai Amazon Web Services (AWS)