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Explainability in AI and Machine Learning Systems: An Overview

Heartbeat

However, they are often considered " black boxes " because it can be challenging to comprehend how their internal workings generate specific predictions. However, they are often considered " black boxes " because it can be challenging to comprehend how their internal workings generate specific predictions.

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Instruction fine-tuning for FLAN T5 XL with Amazon SageMaker Jumpstart

AWS Machine Learning Blog

The power of LLMs comes from their capacity to learn and generalize from extensive and diverse training data. Text completion or imputation is one of the most common unsupervised objectives: given a chunk of text, the model learns to accurately predict what comes next (for example, predict the next sentence).

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Google Research, 2022 & beyond: Algorithmic advances

Google Research AI blog

Hence, developing algorithms with improved efficiency, performance and speed remains a high priority as it empowers services ranging from Search and Ads to Maps and YouTube. In 2022, we continued this journey, and advanced the state-of-the-art in several related areas. You can find other posts in the series here.)

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How to choose a graph database: we compare 6 favorites

Cambridge Intelligence

Each has its own strengths and weaknesses, and the best option for you will depend on your specific use case and requirements. Each has its own strengths and weaknesses, and the best option for you will depend on your specific use case and requirements. We’ve seen how much effort it is to switch databases mid-project.

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The Full Story of Large Language Models and RLHF

Hacker News

In the past months, an exquisitely human-centric approach called Reinforcement Learning from Human Feedback (RLHF) has rapidly emerged as a tour de force in the realm of AI alignment. What is the learning process of a language model? What is RLHF and how to make language models more aligned with human values?

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Fundamentals of Recommendation Systems

PyImageSearch

We will start by learning the basics of these systems and then delve into some of the most popular ones in detail. With the rise of the internet and the increasing use of smart devices, it has become more important than ever to understand user preferences and provide personalized content and services.

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Deploy large models at high performance using FasterTransformer on Amazon SageMaker

AWS Machine Learning Blog

However, as the size and complexity of the deep learning models that power generative AI continue to grow, deployment can be a challenging task. Then, we highlight how Amazon SageMaker large model inference deep learning containers (LMI DLCs) can help with optimization and deployment.

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