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Hammerspace Unveils the Fastest File System in the World for Training Enterprise AI Models at Scale

insideBIGDATA

Hammerspace, the company orchestrating the Next Data Cycle, unveiled the high-performance NAS architecture needed to address the requirements of broad-based enterprise AI, machine learning and deep learning (AI/ML/DL) initiatives and the widespread rise of GPU computing both on-premises and in the cloud.

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Was ist eine Vektor-Datenbank? Und warum spielt sie für AI eine so große Rolle?

Data Science Blog

Vektor-Datenbanken sind ein weiterer Typ von Datenbank, die unter Einsatz von AI (Deep Learning, n-grams, …) Wissen in Vektoren übersetzen und damit vergleichbarer und wieder auffindbarer machen. der k-Nächste-Nachbarn -Prädiktionsalgorithmus (Regression/Klassifikation) oder K-Means-Clustering. von OpenAI genutzt.

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FPGA vs. GPU: Which is better for deep learning?

IBM Journey to AI blog

Underpinning most artificial intelligence (AI) deep learning is a subset of machine learning that uses multi-layered neural networks to simulate the complex decision-making power of the human brain. Deep learning requires a tremendous amount of computing power.

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How to Visualize Deep Learning Models

The MLOps Blog

Deep learning models are typically highly complex. While many traditional machine learning models make do with just a couple of hundreds of parameters, deep learning models have millions or billions of parameters. The reasons for this range from wrongly connected model components to misconfigured optimizers.

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Meta’s open AI hardware vision

Hacker News

At the Open Compute Project (OCP) Global Summit 2024, we’re showcasing our latest open AI hardware designs with the OCP community. These innovations include a new AI platform, cutting-edge open rack designs, and advanced network fabrics and components. Prior to Llama, our largest AI jobs ran on 128 NVIDIA A100 GPUs.

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Learning from deep learning: a case study of feature discovery and validation in pathology

Google Research AI blog

To our knowledge, this is the first demonstration that medical experts can learn new prognostic features from machine learning, a promising start for the future of this “learning from deep learning” paradigm. We then used the prognostic model to compute the average ML-predicted risk score for each cluster.

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Accelerate pre-training of Mistral’s Mathstral model with highly resilient clusters on Amazon SageMaker HyperPod

AWS Machine Learning Blog

The compute clusters used in these scenarios are composed of more than thousands of AI accelerators such as GPUs or AWS Trainium and AWS Inferentia , custom machine learning (ML) chips designed by Amazon Web Services (AWS) to accelerate deep learning workloads in the cloud.