AI

The AWS DeepRacer League is the world’s first autonomous racing league, open to anyone. Announced at re:Invent 2018, it puts machine learning in the hands of every developer through the fun and excitement of developing and racing self-driving remote control cars. Through the past 7 years, over 560 thousand developers of all skill levels have […]

Some misconfigured AI chatbots are pushing people’s chats to the open web—revealing sexual prompts and conversations that include descriptions of child sexual abuse.

Recent advances in Large Language Models (LLMs) enable exciting LLM-integrated applications. However, as LLMs have improved, so have the attacks against them. Prompt injection attack is listed as the #1 threat by OWASP to LLM-integrated applications, where an LLM input contains a trusted prompt (instruction) and an untrusted data. The data may contain injected instructions

Data privacy comes with a cost. There are security techniques that protect sensitive user data, like customer addresses, from attackers who may attempt to extract them from AI models — but they often make those models less accurate. MIT researchers recently developed a framework, based on a new privacy metric called PAC Privacy, that could

Training a frontier model is highly compute-intensive, requiring a distributed system of hundreds, or thousands, of accelerated instances running for several weeks or months to complete a single job. For example, pre-training the Llama 3 70B model with 15 trillion training tokens took 6.5 million H100 GPU hours. On 256 Amazon EC2 P5 instances (p5.48xlarge,

As businesses and developers increasingly seek to optimize their language models for specific tasks, the decision between model customization and Retrieval Augmented Generation (RAG) becomes critical. In this post, we seek to address this growing need by offering clear, actionable guidelines and best practices on when to use each approach, helping you make informed decisions

Today, businesses are using AI and generative models to improve productivity in their teams and provide better experiences to their customers. Personalized outbound communication can be a powerful tool to increase user engagement and conversion. For instance, as a marketing manager for a video-on-demand company, you might want to send personalized email messages tailored to

Financial institutions today face an increasingly complex regulatory world that demands robust, efficient compliance mechanisms. Although organizations traditionally invest countless hours reviewing regulations such as the Anti-Money Laundering (AML) rules and the Bank Secrecy Act (BSA), modern AI solutions offer a transformative approach to this challenge. By using Amazon Bedrock Knowledge Bases alongside CrewAI—an open

Today, we are excited to announce that Mistral AI’s Pixtral Large foundation model (FM) is generally available in Amazon Bedrock. With this launch, you can now access Mistral’s frontier-class multimodal model to build, experiment, and responsibly scale your generative AI ideas on AWS. AWS is the first major cloud provider to deliver Pixtral Large as

Agents are revolutionizing how businesses automate complex workflows and decision-making processes. Amazon Bedrock Agents helps you accelerate generative AI application development by orchestrating multi-step tasks. Agents use the reasoning capability of foundation models (FMs) to break down user-requested tasks into multiple steps. In addition, they use the developer-provided instruction to create an orchestration plan and