Category: FAANG

Imagine a code review process that doesn’t slow you down. Instead of a queue of pending pull requests, you have an intelligent assistant that provides a near-instant, comprehensive summary of every change. It flags potential bugs, suggests improvements based on best practices, and frees up your human reviewers to focus on the complex architectural decisions …

Read more “A deep dive into code reviews with Gemini Code Assist in GitHub”

Organizations across various sectors face significant challenges when converting meeting recordings or recorded presentations into structured documentation. The process of creating handouts from presentations requires lots of manual effort, such as reviewing recordings to identify slide transitions, transcribing spoken content, capturing and organizing screenshots, synchronizing visual elements with speaker notes, and formatting content. These challenges …

Read more “Automate the creation of handout notes using Amazon Bedrock Data Automation”

Today, we’re excited to announce that Mistral-Small-3.2-24B-Instruct-2506—a 24-billion-parameter large language model (LLM) from Mistral AI that’s optimized for enhanced instruction following and reduced repetition errors—is available for customers through Amazon SageMaker JumpStart and Amazon Bedrock Marketplace. Amazon Bedrock Marketplace is a capability in Amazon Bedrock that developers can use to discover, test, and use over …

Read more “Mistral-Small-3.2-24B-Instruct-2506 is now available on Amazon Bedrock Marketplace and Amazon SageMaker JumpStart”

Drug discovery is a complex, time-intensive process that requires researchers to navigate vast amounts of scientific literature, clinical trial data, and molecular databases. Life science customers like Genentech and AstraZeneca are using AI agents and other generative AI tools to increase the speed of scientific discovery. Builders at these organizations are already using the fully …

Read more “Build a drug discovery research assistant using Strands Agents and Amazon Bedrock”

Organizations need ML compute resources that can accommodate bursty peaks and periodic troughs. That means the consumption models for AI infrastructure need to evolve to be more cost-efficient, provide term flexibility, and support rapid development on the latest GPU and TPU accelerators. Calendar mode is currently available in preview as the newest feature of Dynamic …

Read more “Understanding Calendar mode for Dynamic Workload Scheduler: Reserve ML GPUs and TPUs”

Legal teams spend bulk of their time manually reviewing documents during eDiscovery. This process involves analyzing electronically stored information across emails, contracts, financial records, and collaboration systems for legal proceedings. This manual approach creates significant bottlenecks: attorneys must identify privileged communications, assess legal risks, extract contractual obligations, and maintain regulatory compliance across thousands of documents …

Read more “Build an intelligent eDiscovery solution using Amazon Bedrock Agents”

Developers building with gen AI are increasingly drawn to open models for their power and flexibility. But customizing and deploying them can be a huge challenge. You’re often left wrestling with complex dependencies, managing infrastructure, and fighting for expensive GPU access. Don’t let that complexity slow you down. In this guide, we’ll walk you through …

Read more “Your guide to taking an open model from discovery to a production-ready endpoint on Vertex AI”

Cold start in recommendation systems goes beyond just new user or new item problems—it’s the complete absence of personalized signals at launch. When someone first arrives, or when fresh content appears, there’s no behavioral history to tell the engine what they care about, so everyone ends up in broad generic segments. That not only dampens …

Read more “Boost cold-start recommendations with vLLM on AWS Trainium”