Category: FAANG

In today’s data-intensive business landscape, organizations face the challenge of extracting valuable insights from diverse data sources scattered across their infrastructure. Whether it’s structured data in databases or unstructured content in document repositories, enterprises often struggle to efficiently query and use this wealth of information. In this post, we explore how you can use Amazon …

Read more “Unify structured data in Amazon Aurora and unstructured data in Amazon S3 for insights using Amazon Q”

Your next big customer doesn’t speak your language. In fact, 40% of global consumers won’t even consider buying from websites not in their native tongue. With 51.6% of internet users speaking languages other than English, you’re potentially missing half your market.  Until now, enterprises faced an impossible choice in addressing translation use cases. They had …

Read more “Announcing new updates to Cloud Translation AI, now covering 189 languages”

In 2018, I sat in the audience at AWS re:Invent as Andy Jassy announced AWS DeepRacer—a fully autonomous 1/18th scale race car driven by reinforcement learning. At the time, I knew little about AI or machine learning (ML). As an engineer transitioning from legacy networks to cloud technologies, I had never considered myself a developer. …

Read more “Racing into the future: How AWS DeepRacer fueled my AI and ML journey”

Today, we are happy to announce the availability of Binary Embeddings for Amazon Titan Text Embeddings V2 in Amazon Bedrock Knowledge Bases and Amazon OpenSearch Serverless. With support for binary embedding in Amazon Bedrock and a binary vector store in OpenSearch Serverless, you can use binary embeddings and binary vector store to build Retrieval Augmented …

Read more “Build cost-effective RAG applications with Binary Embeddings in Amazon Titan Text Embeddings V2, Amazon OpenSearch Serverless, and Amazon Bedrock Knowledge Bases”

The rapid advancement of generative AI promises transformative innovation, yet it also presents significant challenges. Concerns about legal implications, accuracy of AI-generated outputs, data privacy, and broader societal impacts have underscored the importance of responsible AI development. Responsible AI is a practice of designing, developing, and operating AI systems guided by a set of dimensions …

Read more “Considerations for addressing the core dimensions of responsible AI for Amazon Bedrock applications”

Cloud costs can significantly impact your business operations. Gaining real-time visibility into infrastructure expenses, usage patterns, and cost drivers is essential. This insight enables agile decision-making, optimized scalability, and maximizes the value derived from cloud investments, providing cost-effective and efficient cloud utilization for your organization’s future growth. What makes cost visibility even more important for …

Read more “Governing ML lifecycle at scale: Best practices to set up cost and usage visibility of ML workloads in multi-account environments”