Pinterest Bets $4B on AWS for AI

Pinterest inks a $4 billion, multi-year deal with AWS to power its AI-driven visual discovery features for over 600 million users.

Daniel Singer

Editor, StartupHub.ai

Jun 4 at 2:01 PMUpdated Aug 22, 20262 min read

Pinterest and AWS forge a major AI infrastructure deal.· Amazon News

Visual TL;DR

Pinterest's AI NeedsDriver

powering AI-driven visual discovery for over 600 million users

From the article 9 mentionsPinterest is doubling down on Amazon Web Services (AWS) for its artificial intelligence ambitions, announcing a planned $4 billion commitment through 2031.

$4B AWS DealCore

From the article 7 mentionsThis marks the largest infrastructure deal in the visual discovery platform's history.

Conversational DiscoveryEffect

From the article 4 mentionsRecent advancements include the development of multi-turn conversational discovery via Pinterest Assistant, powered by open-source vision-language models.

AWS Custom SiliconCore

utilizing AWS Trainium and Graviton processors for AI models

From the articleThe expanded partnership, building on a relationship that began in 2010, will see Pinterest utilize AWS's custom silicon.

Scale AI ModelsContext

From the article 4 mentionsThis includes AWS Trainium and Graviton processors to train and run advanced AI models at scale.

Enhance Visual SearchEffect

From the articleThese models are crucial for powering visual search and personalized discovery features.

Accelerate AI InnovationOutcome

aims to accelerate AI innovation for its vast user base

From the article 2 mentionsThe company aims to accelerate AI innovation for its more than 600 million monthly users.

Pinterest is doubling down on Amazon Web Services (AWS) for its artificial intelligence ambitions, announcing a planned $4 billion commitment through 2031. This marks the largest infrastructure deal in the visual discovery platform's history. The company aims to accelerate AI innovation for its more than 600 million monthly users.

The expanded partnership, building on a relationship that began in 2010, will see Pinterest utilize AWS's custom silicon. This includes AWS Trainium and Graviton processors to train and run advanced AI models at scale. These models are crucial for powering visual search and personalized discovery features.

Scaling AI with Custom Silicon

Pinterest has long relied on AI to refine its recommendation systems and personalize user experiences. Recent advancements include the development of multi-turn conversational discovery via Pinterest Assistant, powered by open-source vision-language models. To support these demanding workloads, Pinterest is turning to AWS's specialized hardware.

The company plans to use AWS Trainium for large language and vision-language models that drive AI-assisted discovery. Pinterest is also increasing its use of Graviton processors, which already power approximately one-third of its compute infrastructure. This strategic shift targets enhanced efficiency and performance for AI-driven features.

According to Matt Madrigal, CTO at Pinterest, this commitment provides the necessary compute flexibility and infrastructure efficiency to advance their AI vision. He noted that the partnership will improve both consumer experience and advertiser performance.

The agreement also supports Pinterest's ongoing infrastructure modernization, including a transition to a Kubernetes-based architecture on Amazon Elastic Kubernetes Service (EKS). This move is expected to boost developer velocity and operational reliability.

Dave Brown, SVP of AWS Compute & ML Services, stated that AWS is the optimal environment for large-scale AI development, emphasizing their commitment to accelerating Pinterest's innovation.

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#AWS #Pinterest #Artificial Intelligence #Cloud Computing #Machine Learning #AI Chips #Infrastructure

Written by

Daniel Singer

Editor, StartupHub.ai

Daniel Singer is the editor of StartupHub.ai, a technology expert and thought leader on AI and its applications across sectors, from fintech and healthcare to developer tooling and consumer software. He writes and tests the tools covered here thoroughly and regularly, and built StartupHub.ai to give founders, operators and buyers a clearer read on what they are actually being sold.