Tag: faang

In the domain of software development, AI-driven assistance is emerging as a transformative force to enhance developer experience and productivity and ultimately optimize overall software delivery performance. Many organizations started to leverage AI-based assistants, such as Gemini Code Assist, in developer IDEs to support them in solving more difficult problems, understanding unfamiliar code, generating test …

Read more “Boost your Continuous Delivery pipeline with Generative AI”

Swiss Re & Palantir Scaling Data Operations with Foundry Editor’s note: This guest post is authored by our customer, Swiss Re. Authors Lukasz Lewandowski, Marco Lotz, and Jarek Sobanski lead the core technical team responsible for the implementation of Palantir Foundry at the Swiss reinsurer. They have been managing overall platform operations, core architectural principles, site reliability, …

Read more “Swiss Re & Palantir: Scaling Data Operations with Foundry”

As generative AI models advance in creating multimedia content, the difference between good and great output often lies in the details that only human feedback can capture. Audio and video segmentation provides a structured way to gather this detailed feedback, allowing models to learn through reinforcement learning from human feedback (RLHF) and supervised fine-tuning (SFT). …

Read more “Enhance speech synthesis and video generation models with RLHF using audio and video segmentation in Amazon SageMaker”

Large language models (LLMs) give developers immense power and scalability, but managing resource consumption is key to delivering a smooth user experience. LLMs demand significant computational resources, which means it’s essential to anticipate and handle potential resource exhaustion. If not, you might encounter 429 “resource exhaustion” errors, which can disrupt how users interact with your …

Read more “Don’t let resource exhaustion leave your users hanging: A guide to handling 429 errors”

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”