Question: I'm looking for a cloud computing platform that can handle high-performance computing and AI projects, what are my options?

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Google Cloud

If you're looking for a cloud computing foundation that can power high-performance computing and AI workloads, Google Cloud is a great option. It's got a rich set of developer tools, including generative AI models, prepackaged solutions and Vertex AI for training and deploying AI agents and generative AI services. Compute services include customizable virtual machines, containerized computing and storage, and data analytics tools like BigQuery, real-time data processing and Looker. Google Cloud also has a range of security tools like Cloud Armor and Cloud CDN, so it's a good option for companies trying to modernize their businesses.

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Lambda

Another good option is Lambda, a cloud computing foundation geared for AI developers. It lets you provision on-demand and reserved NVIDIA GPU instances and clusters for training and inferencing AI. It's got preconfigured ML environments for popular frameworks, scalable file systems and pay-by-the-second pricing, which makes it a good option for developers who need fast and cheap ways to tackle big AI jobs.

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Bitdeer

If you need a foundation for high-performance computing and AI that's got a more accessible interface, Bitdeer is a good option. It's got an AI cloud instance for fast setup, a powerful data center management interface and support for complex AI workloads with custom NVIDIA software stacks and high-speed networking. It's also got flexible pricing options and cloud mining support, so it's good for people who need high-end computing power.

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Anyscale

Last, Anyscale is a foundation for developing, deploying and scaling AI applications. It's got the highest performance and efficiency with features like workload scheduling, heterogeneous node control and GPU and CPU fractioning to get the most out of your resources. It's based on the open-source Ray framework, so it supports a broad range of AI models, and it's got strong security and governance features, too, which makes it a good option for big businesses that need high-end AI.

Additional AI Projects

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RunPod

Spin up GPU pods in seconds, autoscale with serverless ML inference, and test/deploy seamlessly with instant hot-reloading, all in a scalable cloud environment.

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IBM Cloud

Supports high-performance AI workloads with a secure, resilient, and scalable foundation, enabling responsible AI workflows and integration of all data sources.

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Cerebras

Accelerate AI training with a platform that combines AI supercomputers, model services, and cloud options to speed up large language model development.

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NVIDIA

Accelerates AI adoption with tools and expertise, providing efficient data center operations, improved grid resiliency, and lower electric grid costs.

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NVIDIA AI Platform

Accelerate AI projects with an all-in-one training service, integrating accelerated infrastructure, software, and models to automate workflows and boost accuracy.

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Scaleway

Scaleway offers a broad range of cloud services for building, training, and deploying AI models.

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Gcore

Accelerates AI training and content delivery with a globally distributed network, edge native architecture, and secure infrastructure for high-performance computing.

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Salad

Run AI/ML production models at scale with low-cost, scalable GPU instances, starting at $0.02 per hour, with on-demand elasticity and global edge network.

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Cerebrium

Scalable serverless GPU infrastructure for building and deploying machine learning models, with high performance, cost-effectiveness, and ease of use.

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Google AI

Unlock AI-driven innovation with a suite of models, tools, and resources that enable responsible and inclusive development, creation, and automation.

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dstack

Automates infrastructure provisioning for AI model development, training, and deployment across multiple cloud services and data centers, streamlining complex workflows.

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HPE

Unlock the full potential of your data with HPE's edge-to-cloud solutions and AI technology.

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Aethir

On-demand access to powerful, cost-effective, and secure enterprise-grade GPUs for high-performance AI model training, fine-tuning, and inference anywhere in the world.

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JuliaHub

Collaborate in real-time on complex computing projects with limitless power, reproducibility, and AI-driven code assistance, all in a secure and compliant environment.

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Mystic

Deploy and scale Machine Learning models with serverless GPU inference, automating scaling and cost optimization across cloud providers.

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Together

Accelerate AI model development with optimized training and inference, scalable infrastructure, and collaboration tools for enterprise customers.

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AIxBlock

Decentralized supercomputer platform cuts AI development costs by up to 90% through peer-to-peer compute marketplace and blockchain technology.

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DEKUBE

Scalable, cost-effective, and secure distributed computing network for training and fine-tuning large language models, with infinite scalability and up to 40% cost reduction.

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Numenta

Run large AI models on CPUs with peak performance, multi-tenancy, and seamless scaling, while maintaining full control over models and data.

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Teradata

Unifies and harmonizes all data across an organization, providing transparency and speed, and enabling faster innovation and collaboration.