Artificial Inteligence Metrics System Design Training 
CIO
APRIL 25, 2024
During the summer of 2023, at the height of the first wave of interest in generative AI, LinkedIn began to wonder whether matching candidates with employers and making feeds more useful would be better served with the help of large language models (LLMs). We didn’t start with a very clear idea of what an LLM could do.”
AWS Machine Learning - AI
APRIL 3, 2024
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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Xebia
AUGUST 9, 2023
With the industry moving towards end-to-end ML teams to enable them to implement MLOPs practices, it is paramount to look past the model and view the entire system around your machine learning model. Table of Contents What is Machine Learning System Design?
AWS Machine Learning - AI
SEPTEMBER 6, 2024
Generative artificial intelligence (AI) applications powered by large language models (LLMs) are rapidly gaining traction for question answering use cases. This post focuses on evaluating and interpreting metrics using FMEval for question answering in a generative AI application.
O'Reilly Media - Ideas
MAY 1, 2019
Get hands-on training in machine learning, blockchain, cloud native, PySpark, Kubernetes, and many other topics. Learn new topics and refine your skills with more than 160 new live online training courses we opened up for May and June on the O'Reilly online learning platform. AI and machine learning.
Hacker Earth Developers Blog
JULY 18, 2023
This term covers the use of any tech-based tools or systems designed to understand and respond to human emotions. The kinds of things that count as empathetic technology include: Wearables that use physical metrics to determine a person’s mood. Platforms that use AI to make an easy-to-learn user interface.
Cloudera
DECEMBER 3, 2021
They identified four main categories: capturing intent, system design, human judgement & oversight, regulations. An AI system trained on data has no context outside of that data. Designers therefore need to explicitly and carefully construct a representation of the intent motivating the design of the system.
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