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Streamline RAG applications with intelligent metadata filtering using Amazon Bedrock

AWS Machine Learning - AI

In some use cases, particularly those involving complex user queries or a large number of metadata attributes, manually constructing metadata filters can become challenging and potentially error-prone. The following diagram illustrates high level RAG architecture with dynamic metadata filtering.

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Build and deploy a UI for your generative AI applications with AWS and Python

AWS Machine Learning - AI

Traditionally, building frontend and backend applications has required knowledge of web development frameworks and infrastructure management, which can be daunting for those with expertise primarily in data science and machine learning.

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The Importance of Assessing Interpersonal Skills in Recruitment

Hacker Earth Developers Blog

Candidates with strong interpersonal skills can navigate these challenges constructively, ensuring that team dynamics remain intact. Example: “How do you approach giving constructive feedback to a teammate who isn’t meeting expectations?” Example: Ask a group of candidates to design an architecture for a scalable web application.

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Machine Learning Pipeline: Architecture of ML Platform in Production

Altexsoft

Machine learning (ML) history can be traced back to the 1950s, when the first neural networks and ML algorithms appeared. Analysis of more than 16.000 papers on data science by MIT technologies shows the exponential growth of machine learning during the last 20 years pumped by big data and deep learning advancements.

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Introducing AWS MCP Servers for code assistants (Part 1)

AWS Machine Learning - AI

Accelerate building on AWS What if your AI assistant could instantly access deep AWS knowledge, understanding every AWS service, best practice, and architectural pattern? Lets create an architecture that uses Amazon Bedrock Agents with a custom action group to call your internal API.

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CIOs are rethinking how they use public cloud services. Here’s why.

CIO

AI projects can break budgets Because AI and machine learning are data intensive, these projects can greatly increase cloud costs. For Perry, constructing the right IT infrastructure for his organizations applications is all about using the right building materials. I dont see that evolving too much beyond where we are today.

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Tech-enabled homebuilder Homebound raises $75M Series C led by Khosla

TechCrunch

Using machine learning and data, Homebound looks to purchase land in mostly off-market transactions. From there, it can help with everything from architectural plans to design to actual construction via its platform. The construction industry has long been plagued by inefficiencies and productivity challenges.