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#cloud-ai

Every item tagged cloud-ai, newest first.

16 items

otherJun 9

Apple says its AI is still private, even when it's running on Google's servers

Apple claims its AI models can run on Google's servers without compromising user privacy. The company achieves this through secure enclaves that isolate and encrypt data during processing. This approach allows Apple to leverage cloud infrastructure while maintaining control over sensitive information. You can expect similar privacy-preserving measures in future AI deployments.

Key takeaways
  • Apple uses secure enclaves to isolate data on Google's servers.
  • No data access for Google.
  • Privacy preserved in cloud AI processing.
AArs Technica#private-ai#cloud-ai#secure-computing
otherMay 11

Building Blocks for Foundation Model Training and Inference on AWS

AWS and Hugging Face have collaborated to provide optimized building blocks for training and deploying foundation models on AWS infrastructure. The integration enables faster and more cost-effective model training and inference. You can leverage these building blocks to streamline your foundation model development workflow. This partnership aims to make foundation model development more accessible and efficient.

Key takeaways
  • AWS and Hugging Face collaborate on optimized foundation model building blocks.
  • The integration enables faster and more cost-effective model training and inference.
  • Streamlines foundation model development workflow on AWS infrastructure.
HHugging Face Blog#cloud-ai#model-training#inference-optimization
otherSep 19

Scaleway on Hugging Face Inference Providers 🔥

Scaleway has joined Hugging Face as an inference provider, expanding access to scalable and secure cloud infrastructure for deploying AI models. This partnership enables users to deploy models on Scaleway's cloud infrastructure. Builders can now leverage Scaleway's GPU-accelerated instances for model serving. Scaleway's infrastructure is designed for high-performance and low-latency AI workloads.

Key takeaways
  • Scaleway joins Hugging Face as an inference provider.
  • Enables deployment of AI models on Scaleway's cloud infrastructure.
  • Scaleway offers GPU-accelerated instances for model serving.
HHugging Face Blog#inference-providers#cloud-ai#model-serving
otherMay 19

Microsoft and Hugging Face expand collaboration

Microsoft and Hugging Face are expanding their collaboration to make Hugging Face models more accessible on Microsoft Azure. The partnership aims to simplify model deployment and fine-tuning for builders. This integration enables easier use of Hugging Face's model hub and tools on Azure's cloud infrastructure. You can now deploy Hugging Face models directly on Azure.

Key takeaways
  • Hugging Face models are now more accessible on Microsoft Azure.
  • The partnership simplifies model deployment and fine-tuning.
  • Builders can deploy Hugging Face models directly on Azure.
HHugging Face Blog#cloud-ai#model-deployment#partnerships
modelsDec 9

Hugging Face models in Amazon Bedrock

Hugging Face models are now available in Amazon Bedrock, expanding access to a wide range of open and closed models for builders. This integration allows users to deploy Hugging Face models directly within Bedrock, streamlining workflows. You can now discover, deploy, and manage Hugging Face models using Bedrock's existing tools and infrastructure. The partnership aims to provide more model choices and flexibility for builders.

Key takeaways
  • Hugging Face models integrated into Amazon Bedrock.
  • Streamlines deployment of Hugging Face models.
  • Increases model choices for builders using Bedrock.
HHugging Face Blog#model-marketplace#cloud-ai#partnerships
modelsAug 19

Deploy Meta Llama 3.1 405B on Google Cloud Vertex AI

Meta Llama 3.1 405B is now deployable on Google Cloud Vertex AI, allowing builders to run the model in a managed environment. The integration enables access to Llama 3.1 405B's capabilities without managing infrastructure. You can deploy the model through the Vertex AI console or API.

Key takeaways
  • Llama 3.1 405B available on Google Cloud Vertex AI.
  • Managed environment simplifies deployment.
  • Access via console or API.
HHugging Face Blog#model-deployment#cloud-ai#managed-services
otherJul 9

Google Cloud TPUs made available to Hugging Face users

Google Cloud has made its Tensor Processing Units (TPUs) available to Hugging Face users through a new integration. This allows Hugging Face customers to deploy and run models on TPUs, leveraging Google's custom hardware for faster inference. Builders can now access TPUs through Hugging Face's Inference Endpoints and Spaces, enabling them to optimize model performance and reduce costs. The integration aims to provide a seamless experience for deploying AI models at scale.

Key takeaways
  • TPUs now available to Hugging Face users for model deployment.
  • Integration enables faster inference and potential cost savings.
  • Hugging Face provides access through Inference Endpoints and Spaces.
HHugging Face Blog#cloud-ai#model-deployment#hardware-acceleration
modelsMay 22

Deploy models on AWS Inferentia2 from Hugging Face

Hugging Face now supports deploying models on AWS Inferentia2, a custom chip designed for high-performance, low-cost inference. This integration allows you to deploy models with optimized performance and cost efficiency. Builders can use Inferentia2 to run models at scale while reducing infrastructure costs. The partnership aims to make AI deployment more accessible and affordable.

Key takeaways
  • Hugging Face supports AWS Inferentia2 for model deployment.
  • Inferentia2 offers high-performance, low-cost inference.
  • Partnership aims to make AI deployment more accessible.
HHugging Face Blog#model-deployment#inference-optimization#cloud-ai
otherMay 21

From cloud to developers: Hugging Face and Microsoft Deepen Collaboration

Hugging Face and Microsoft have expanded their collaboration to provide developers with easier access to Hugging Face models and datasets on Microsoft Azure. The partnership aims to simplify the deployment of AI models and enable more developers to build AI-powered applications. This collaboration targets builders who want to leverage Hugging Face's open-source AI tools and Microsoft's cloud infrastructure. The integration is designed to streamline AI model deployment and management.

Key takeaways
  • Hugging Face models and datasets now available on Microsoft Azure.
  • Simplified deployment and management of AI models.
  • Expanded access to open-source AI tools for developers.
HHugging Face Blog#open-source#cloud-ai#model-deployment
modelsFeb 1

Hugging Face Text Generation Inference available for AWS Inferentia2

Hugging Face has made Text Generation Inference available for AWS Inferentia2, enabling faster and more cost-effective deployment of text generation models on AWS. This integration allows builders to optimize model performance and reduce costs. The move targets developers looking to deploy AI models efficiently on cloud infrastructure. Inferentia2 chips provide optimized performance for machine learning workloads.

Key takeaways
  • Text Generation Inference now supported on AWS Inferentia2.
  • Enables faster and more cost-effective model deployment.
  • Optimized for Inferentia2 chips' machine learning performance.
HHugging Face Blog#cloud-ai#text-generation#model-deployment
otherJan 25

Hugging Face and Google partner for open AI collaboration

Hugging Face and Google have partnered to enable seamless integration of Hugging Face models with Google Cloud Platform services. The partnership aims to simplify AI model deployment and management for builders. You can expect to see more open-source models optimized for Google Cloud. This collaboration targets builders who want to deploy AI models at scale.

Key takeaways
  • Hugging Face models integrate with Google Cloud Platform.
  • Partnership focuses on simplifying AI model deployment.
  • Open-source models optimized for Google Cloud.
HHugging Face Blog#open-source#cloud-ai#partnerships
modelsMay 31

Introducing the Hugging Face LLM Inference Container for Amazon SageMaker

Hugging Face and AWS have collaborated on an LLM inference container for Amazon SageMaker, streamlining deployment of Hugging Face models on SageMaker. This integration allows for one-click deployment of Hugging Face models, enabling faster and more efficient model serving. You can deploy models with optimized performance and reduced latency. The container supports popular Hugging Face Transformers and is available for use on SageMaker.

Key takeaways
  • One-click deployment of Hugging Face models on SageMaker.
  • Optimized performance and reduced latency for model serving.
  • Supports popular Hugging Face Transformers.
HHugging Face Blog#model-deployment#cloud-ai#inference-optimization
otherFeb 21

Hugging Face and AWS partner to make AI more accessible

Hugging Face and AWS have partnered to make AI more accessible to developers and businesses. The partnership aims to provide easier access to AI models, datasets, and tools. This collaboration is expected to lower the barriers to AI adoption. You can now deploy Hugging Face models on AWS with one-click.

Key takeaways
  • Hugging Face models are now deployable on AWS with one-click.
  • The partnership aims to make AI more accessible to developers and businesses.
  • Easier access to AI models, datasets, and tools is provided.
HHugging Face Blog#ai-accessibility#cloud-ai#partnerships
modelsAug 19

Deploying 🤗 ViT on Vertex AI

You can deploy Hugging Face's ViT model on Google Cloud's Vertex AI for image classification tasks. The integration allows for scalable model serving and automated batching. This setup enables you to focus on building applications rather than managing infrastructure. The deployment process is streamlined through Hugging Face's tools.

Key takeaways
  • Deploy ViT on Vertex AI for scalable image classification.
  • Integration allows for automated batching and managed infrastructure.
  • Hugging Face tools simplify the deployment process.
HHugging Face Blog#model-deployment#cloud-ai#image-classification
otherJul 8

Deploy Hugging Face models easily with Amazon SageMaker

Hugging Face and Amazon SageMaker have integrated to simplify model deployment for builders. This integration allows users to deploy Hugging Face models directly on SageMaker, streamlining workflows and reducing operational overhead. You can now easily deploy and manage models on SageMaker. The integration supports popular Hugging Face model repositories.

Key takeaways
  • Hugging Face models deployable on Amazon SageMaker directly.
  • Integration streamlines workflows and reduces operational overhead.
  • Supports popular Hugging Face model repositories.
HHugging Face Blog#model-deployment#cloud-ai#hugging-face
otherMar 23

The Partnership: Amazon SageMaker and Hugging Face

Amazon SageMaker and Hugging Face have partnered to integrate Hugging Face models with SageMaker, allowing users to deploy and fine-tune models directly within the SageMaker platform. This integration aims to simplify the process of building and deploying AI models for developers. The partnership enables seamless access to Hugging Face's model hub and tools. You can now use Hugging Face models with SageMaker's automated model tuning and hyperparameter optimization.

Key takeaways
  • Hugging Face models are now integrated with Amazon SageMaker.
  • Developers can deploy and fine-tune Hugging Face models directly in SageMaker.
  • The partnership includes access to Hugging Face's model hub and tools.
HHugging Face Blog#model-integration#cloud-ai#partnerships