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Accelerated PyTorch inference with torch.compile on AWS Graviton processors | Amazon Web Services

Originally PyTorch used an eager mode where each PyTorch operation that forms the model is run independently as soon as it’s reached. PyTorch 2.0...

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Accelerate deep learning training and simplify orchestration with AWS Trainium and AWS Batch | Amazon Web Services

In large language model (LLM) training, effective orchestration and compute resource management poses a significant challenge. Automation of resource provisioning, scaling, and workflow management...

A practical guide to making your AI chatbot smarter with RAG

Hands on If you've been following enterprise adoption of AI, you've no doubt heard the term “RAG” tossed around. Short for retrieval augmented generation, the...

Get started quickly with AWS Trainium and AWS Inferentia using AWS Neuron DLAMI and AWS Neuron DLC | Amazon Web Services

Starting with the AWS Neuron 2.18 release, you can now launch Neuron DLAMIs (AWS Deep Learning AMIs) and Neuron DLCs (AWS Deep Learning Containers)...

Lithuanian startup Spike raises €3.2 million to supercharge health enterprises with GenAI | EU-Startups

Vilnius-based Spike, a B2B data technology and AI startup, has announced the successful close of an €3.2 million oversubscribed seed round that will be...

Linus Torvalds on Why He Does Not Like Cryptocurrencies

In a recent forum post, renowned Finnish-American software engineer Linus Torvalds, best known for creating the Linux operating system, expressed his skepticism about cryptocurrencies....

Accelerate NLP inference with ONNX Runtime on AWS Graviton processors | Amazon Web Services

ONNX is an open source machine learning (ML) framework that provides interoperability across a wide range of frameworks, operating systems, and hardware platforms. ONNX...

Linux VPS Management Skills for Data Scientists

We have talked a lot about the growing demand for data scientists. While it is a very lucrative career, it is also very competitive.Data...

Ollama Tutorial: Running LLMs Locally Made Super Simple – KDnuggets

 Image by Author  Running large language models (LLMs) locally can be super helpful—whether you'd like to play around with LLMs or build more powerful apps...

Simple guide to training Llama 2 with AWS Trainium on Amazon SageMaker | Amazon Web Services

Large language models (LLMs) are making a significant impact in the realm of artificial intelligence (AI). Their impressive generative abilities have led to widespread...

Develop and train large models cost-efficiently with Metaflow and AWS Trainium | Amazon Web Services

This is a guest post co-authored with Ville Tuulos (Co-founder and CEO) and Eddie Mattia (Data Scientist) of Outerbounds. ...

Accelerate ML workflows with Amazon SageMaker Studio Local Mode and Docker support | Amazon Web Services

We are excited to announce two new capabilities in Amazon SageMaker Studio that will accelerate iterative development for machine learning (ML) practitioners: Local Mode...

Deploying Machine Learning Model Using Flask on AWS with Gunicorn and Nginx

Introduction In the previous article, We went through the process of building a machine-learning model for sentiment analysis that was encapsulated in a Flask application....

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