Generative Data Intelligence

Tag: BERT

What is Prompt Engineering? A Comprehensive Guide for AI

IntroductionPrompt engineering, at its core, is the art of conversational alchemy with AI. It's where meticulous crafting of questions or instructions meets the world...

Reduce inference time for BERT models using neural architecture search and SageMaker Automated Model Tuning | Amazon Web Services

In this post, we demonstrate how to use neural architecture search (NAS) based structural pruning to compress a fine-tuned BERT model to improve model...

Luis Maldonado: «It’s Time For Regulation To Catch Up» – CryptoInfoNet

The winds of regulation moving around digital assets are strong and in the last few years, more and more countries have chosen to issue...

Deploy foundation models with Amazon SageMaker, iterate and monitor with TruEra | Amazon Web Services

This blog is co-written with Josh Reini, Shayak Sen and Anupam Datta from TruEra Amazon SageMaker JumpStart provides a variety of pretrained foundation models...

Frugality meets Accuracy: Cost-efficient training of GPT NeoX and Pythia models with AWS Trainium | Amazon Web Services

Large language models (or LLMs) have become a topic of daily conversations. Their quick adoption is evident by the amount of time required to...

Techniques for automatic summarization of documents using language models | Amazon Web Services

Summarization is the technique of condensing sizable information into a compact and meaningful form, and stands as a cornerstone of efficient communication in our...

How Getir reduced model training durations by 90% with Amazon SageMaker and AWS Batch | Amazon Web Services

This is a guest post co-authored by Nafi Ahmet Turgut, Hasan Burak Yel, and Damla Şentürk from Getir. Established in 2015, Getir has positioned...

Evaluate large language models for quality and responsibility | Amazon Web Services

The risks associated with generative AI have been well-publicized. Toxicity, bias, escaped PII, and hallucinations negatively impact an organization’s reputation and damage customer trust....

Accelerate deep learning model training up to 35% with Amazon SageMaker smart sifting | Amazon Web Services

In today’s rapidly evolving landscape of artificial intelligence, deep learning models have found themselves at the forefront of innovation, with applications spanning computer vision...

Schedule Amazon SageMaker notebook jobs and manage multi-step notebook workflows using APIs | Amazon Web Services

Amazon SageMaker Studio provides a fully managed solution for data scientists to interactively build, train, and deploy machine learning (ML) models. Amazon SageMaker notebook...

Amazon EC2 DL2q instance for cost-efficient, high-performance AI inference is now generally available | Amazon Web Services

This is a guest post by A.K Roy from Qualcomm AI. Amazon Elastic Compute Cloud (Amazon EC2) DL2q instances, powered by Qualcomm AI 100...

How Amazon Music uses SageMaker with NVIDIA to optimize ML training and inference performance and cost | Amazon Web Services

In the dynamic world of streaming on Amazon Music, every search for a song, podcast, or playlist holds a story, a mood, or a...

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