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How ML System Design helps us to make better ML products

Xebia

Table of Contents What is Machine Learning System Design? Design Process Clarify requirements Frame problem as an ML task Identify data sources and their availability Model development Serve predictions Observability Iterate on your design What is Machine Learning System Design?

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What LinkedIn learned leveraging LLMs for its billion users

CIO

For LinkedIn, this was no different, as its road to LLM insights was anything but smooth, said LinkedIn’s Juan Bottaro, a principal software engineer and tech lead. As an example, Bottaro referenced the part of the system designed to understand intent. The initial deliverables “felt lacking,” Bottaro said.

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Why engineers need strong problem-solving skills—and how to ensure your team has them

Agile Engine

A story about hiring the wrong person As a young engineer before joining AgileEngine, I had a co-worker. Many engineers intimately know the details of their chosen technologies but fail to solve unstructured problems that cover unfamiliar territory. Let’s call him Dave. One more observation: while some hard problem-solving skills (e.g.,

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Build a contextual text and image search engine for product recommendations using Amazon Bedrock and Amazon OpenSearch Serverless

AWS Machine Learning - AI

Search engines and recommendation systems powered by generative AI can improve the product search experience exponentially by understanding natural language queries and returning more accurate results. Amazon OpenSearch Service now supports the cosine similarity metric for k-NN indexes.

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Simulation Theory, Observability, and Modern Software Practices

Honeycomb

s favorite three buzzwords (logs, metrics, and traces), we can draw several analogies to understand software development and debugging. The real vs. simulated systems In Baudrillard’s terms, the authentic experiences and the real have been replaced by symbols and signs ( logs , metrics , traces ).

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5 Types of Infrastructure Engineers Your Business May Need

Mobilunity

Infrastructure engineering is a branch of engineering as it uses the principles of science and mathematics to design and develop the structures required to perform certain processes. Infrastructure engineering in the IT world includes working with network connections, cabling, and storage area networks. Logs and Metrics.

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Bringing an AI Product to Market

O'Reilly Media - Ideas

The first step in building an AI solution is identifying the problem you want to solve, which includes defining the metrics that will demonstrate whether you’ve succeeded. It sounds simplistic to state that AI product managers should develop and ship products that improve metrics the business cares about. Agreeing on metrics.

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