GPU

Pushing beyond the limits of embedded real-time AI for edge devices

Startup highlight: Interview with Kevin Conley, CEO at Applied Brain Research (ABR) Applied Brain Research (ABR) is a fabless semiconductor company founded by a team from the University of Waterloo’s Centre for Theoretical Neuroscience, under the leadership of Dr. Chris Eliasmith, the Centre’s founding chair, to commercialize brain-inspired AI inference solutions. Can you introduce Applied […]

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Enhancing Customer Service with Interactive Avatars

Startup highlight: Interview with Fatma Chelly, Marketing Manager at Jumbo Mana Jumbo Mana is a deep-tech startup founded in 2022. Specializing in Agentic AI, the company creates conversational solutions, including avatars and digital assistants that provide precise, fast, reliable and engaging answers. Can you introduce Jumbo Mana and its mission? Jumbo Mana’s solution distinguishes by

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Five ways to develop sovereign, sustainable AI solutions

Now that organisations understand AI and what it can achieve, businesses around the world are focusing on how to build it responsibly. Three of the five main themes at the Paris AI Action Summit examine the need for responsible AI, with separate streams on trust, public interest and good governance. These themes are not simple.

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Fine-Tuning LLaMA 2 Models with a single GPU and OVHcloud

Fine-Tuning LLaMA 2 Models using a single GPU, QLoRA and AI Notebooks

In this tutorial, we will walk you through the process of fine-tuning LLaMA 2 models, providing step-by-step instructions. All the code related to this article is available in our dedicated GitHub repository. You can reproduce all the experiments with OVHcloud AI Notebooks. Introduction On July 18, 2023, Meta released LLaMA 2, the latest version of

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using GPU on Managed Kubernetes Service with NVIDIA GPU operator

Using GPU on Managed Kubernetes Service with NVIDIA GPU operator

Two years after launching our Managed Kubernetes service, we’re seeing a lot of diversity in the workloads that run in production. We have been challenged by some customers looking for GPU acceleration, and have teamed up with our partner NVIDIA to deliver high performance GPUs on Kubernetes. We’ve done it in a way that combines

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Managing GPU pools efficiently in AI pipelines

Managing GPU pools efficiently in AI pipelines

A growing number of companies are using artificial intelligence on a daily basis — and dealing with the back-end architecture can reveal some unexpected challenges. Whether the machine learning workload involves fraud detection, forecasts, chatbots, computer vision or NLP, it will need frequent access to computing power for training and fine-tuning. GPUs have proven to

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How PCI-Express works and why you should care? #GPU

How PCI-Express works and why you should care? #GPU

What is PCI-Express ? Everyone, and I mean everyone, should pay attention when they do intensive Machine Learning / Deep Learning Training. As I explained in a previous blog post, GPUs have accelerated Artificial Intelligence evolution massively. However, building a GPUs server is not that easy. And failing to create an appropriate infrastructure can have

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Distributed Learning in a Deep Learning context

Distributed Training in a Deep Learning Context

Previously on OVHcloud Blog … In previous blog posts we have discussed a high level approach to deep learning as well as what is meant by ‘training’ in relation to Deep Learning. Following the article, I had lots of questions entering my twitter inbox, especially regarding how GPUs actually works. I decided, therefore, to write

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What does training neural networks mean?

What does Training Neural Networks mean?

In a previous blog post we discussed general concepts surrounding Deep Learning. In this blog post, we will go deeper into the basic concepts of training a (deep) Neural Network. Where does “Neural” comes from ? As you should know, a biological neuron is composed of multiple dendrites, a nucleus and a axon (if only

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