Today CAST AI introduced a series of new features into its platform, designed to dramatically reduce cloud costs for organizations which are building, training and running AI models and applications in the cloud. This comes at a pivotal moment, as a new poll by Gartner estimates 70 percent of organizations are currently in exploration mode with generative AI.

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Tech leaders face a rush of demand for AI apps. Yet AI comes with high compute requirements and demands specialized hardware equipped with Graphics Processing Units (GPUs), an industry standard for training AI models. Provisioning these resources is expensive; analysts estimate that systems like ChatGPT cost as much as $700,000 a day to operate. The result is that – while AI is primed to transform applications across virtually every industry – training and running models is largely limited to well-funded organizations which dedicate significant IT spend to cloud providers out of necessity.

Gartner’s senior director analyst Chirag Dekate has noted: “IT leaders responsible for AI are discovering ‘AI pilot paradox,’ where launching pilots is deceptively easy but deploying them into production is notoriously challenging.” And while Dekate finds that scaling infrastructure resources is pivotal to success, and that AI is one of the top cloud services, nearly half of businesses struggle with cloud costs.

So, to support teams that are building, training, and running AI models, CAST AI has expanded its platform with the following features:

  • Automated provisioning, selecting, and scaling of cost-effective GPU machines across AWS, Google and Microsoft Azure.
  • Automated decommissioning of GPU instances and replacement with more cost-efficient alternatives once the process is completed.
  • Automated optimization of Amazon Inferentia machines used for executing AI models.
  • Use of high performance Graviton processors for performance and cost balance.
  • Automated management of spot instances – CAST AI identifies the optimal pod configuration for the model’s computation requirements and automatically selects machines that meet these criteria cost-effectively.

“Our new features are game-changing for businesses looking to reduce the cost of AI model training,” said Laurent Gil, co-founder and Chief Product Officer at CAST AI. “We have generated cloud cost savings of 76 percent for one of our customers who used Amazon EKS to train and run advanced AI models. Thanks to these new features, teams can streamline their AI workflows, saving time and resources while driving better results.”

“As AI models continue to grow in size and power, the cost of computation to train and run them also increases,” said Bobby Yazdani, Founder and Partner of Cota Capital. “By significantly reducing these costs, CAST AI can enable wider experimentation, deployment and adoption of these powerful new technologies.”

About CAST AI:

CAST AI is a cloud optimization platform that cuts cloud bills in half for AWS, GCP, and Azure customers. Powered by AI, it analyzes multiple data points to find an optimal cost-performance ratio. The platform delivers a cost-efficient, high-performing, and resilient infrastructure for all types of Kubernetes workloads. Headquartered in Miami, US, CAST AI has a European branch in Vilnius, Lithuania.

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