Generative Data Intelligence

Tag: PyTorch

Streamlining ETL data processing at Talent.com with Amazon SageMaker | Amazon Web Services

This post is co-authored by Anatoly Khomenko, Machine Learning Engineer, and Abdenour Bezzouh, Chief Technology Officer at Talent.com. Established in 2011, Talent.com aggregates paid...

Fine-tune Llama 2 using QLoRA and Deploy it on Amazon SageMaker with AWS Inferentia2 | Amazon Web Services

In this post, we showcase fine-tuning a Llama 2 model using a Parameter-Efficient Fine-Tuning (PEFT) method and deploy the fine-tuned model on AWS Inferentia2....

AMD Launches Instinct MI300 Series To Compete In The AI Accelerator Market

AMD launches MI300X AI accelerator packs a performance punch. AMDā€™s ROCm platform counters Nvidiaā€™s software stronghold. Microsoft, Meta, Oracle opt for AMD AI...

Mitigate hallucinations through Retrieval Augmented Generation using Pinecone vector database & Llama-2 from Amazon SageMaker JumpStart | Amazon Web Services

Despite the seemingly unstoppable adoption of LLMs across industries, they are one component of a broader technology ecosystem that is powering the new AI...

Enable faster training with Amazon SageMaker data parallel library | Amazon Web Services

Large language model (LLM) training has become increasingly popular over the last year with the release of several publicly available models such as Llama2,...

Foundational data protection for enterprise LLM acceleration with Protopia AI | Amazon Web Services

This post is written in collaboration with Balaji Chandrasekaran, Jennifer Cwagenberg and Andrew Sansom and Eiman Ebrahimi from Protopia AI. New and powerful large...

Welcome to a New Era of Building in the Cloud with Generative AI on AWS | Amazon Web Services

We believe generative AI has the potential over time to transform virtually every customer experience we know. The number of companies launching generative AI...

Package and deploy classical ML and LLMs easily with Amazon SageMaker, part 2: Interactive User Experiences in SageMaker Studio | Amazon Web Services

Amazon SageMaker is a fully managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning (ML)...

Package and deploy classical ML and LLMs easily with Amazon SageMaker, part 1: PySDK Improvements | Amazon Web Services

Amazon SageMaker is a fully managed service that enables developers and data scientists to quickly and effortlessly build, train, and deploy machine learning (ML)...

Scale foundation model inference to hundreds of models with Amazon SageMaker ā€“ Part 1 | Amazon Web Services

As democratization of foundation models (FMs) becomes more prevalent and demand for AI-augmented services increases, software as a service (SaaS) providers are looking to...

Build and evaluate machine learning models with advanced configurations using the SageMaker Canvas model leaderboard | Amazon Web Services

Amazon SageMaker Canvas is a no-code workspace that enables analysts and citizen data scientists to generate accurate machine learning (ML) predictions for their business...

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

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

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