Articles tagged with "level-300"

MCP Authentication for Agent Connections in Amazon Bedrock AgentCore: A Complete Guide Agents are currently the go-to topic in AI, with AWS heavily pushing Amazon Bedrock AgentCore as the next-generation platform for building intelligent, tool-enabled applications. However, while LLMs excel at language understanding and generation, they have fundamental limitations in performing complex calculations, data processing, and accessing external systems. While an LLM might have learned that 2+2 equals 4, it cannot perform integral calculations or access real-time data from external APIs.

AWS released GA Automated Reasoning checks for Bedrock. What sounds so small could be the actual drug against AI hallucinations. But it turns out: It is complicated! Let me show you, what I mean.

At the beginning of a AWS software development project, some big architectural decisions need to be made. This is a classic: does AWS Lambda or Docker/Microservice make more sense? Well - with the GOpher Chameleon, you can have both worlds. The very same code for Lambda or container.

Lambda@Edge functions are executed in multiple regions around the world, but which ones exactly? In this post we’ll find out together, which will enable us to pre-create log groups and other resources for them.

Your agentic multi-channel, multi-modal GenAI solution idea may be buzz-word-compatible. But to do some expectation management: It will not run as fast as this dog. So, we share some of the tips from our projects on how to speed up your GenAI solution.

To battle security compliance is a challenge, which is besten solved as a team sport. We show you some solutions to win this tug of war, like knowing not only the technical, but also the psychological aspects of the game. This is the way our MSSP works together with you.

Even the best security measures can’t prevent all security incidents. With the right tools, you can detect and respond to incidents quickly. The problem is not anymore that you have no tools at hand but that you have too many. How do you choose the right one?

Retrieval-Augmented Generation (RAG) solutions are an impressive way to talk to one’s data. One of the challenges of RAG solutions is the associated cost, often driven by the vector database. In a previous blog article I presented how to tackle this issue by using Athena with Locality Sensitive Hashing (LSH) as a knowledge database. One the of the main limitations with Athena is the latency and the low number of concurrent queries. In this new blog article, I present a new low-cost serverless solution that makes use of an embedded vector database, SQLite, to achieve a low cost while maintaining high concurrency.