MinIO Blog

AI/ML

A collection of 119 posts tagged with "AI/ML"

Turbocharged Storage: MinIO, KIOXIA, and AMD team up to take on AI

Turbocharged Storage: MinIO, KIOXIA, and AMD team up to take on AI

MinIO, the leader in high-performance AI storage, has once again raised the bar in the AI infrastructure industry with its groundbreaking MinIO AIStor platform. Leveraging next-generation AMD hardware, KIOXIA NVMe™ SSDs, and cutting-edge software optimizations, MinIO AIStor delivers unmatched performance, scalability, and efficiency for AI-driven and other data intensive workloads. Today, we are excited to share benchmark results that demonstrate

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Introducing Model Context Protocol (MCP) Server for MinIO AIStor

Pavel Anni Pavel Anni on AI/ML |
Introducing Model Context Protocol (MCP) Server for MinIO AIStor

GenAI is entering the agentic phase, with software agents collaborating with humans and other agents to reason and achieve complex goals. Agents are already demonstrating incredible intelligence and are very helpful with question answering, but as with humans, they need the ability to discover and access software applications and other services to actually perform useful work. The creators of such

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AIStor Integration with NVIDIA NIM™

AIStor Integration with NVIDIA NIM™

Building upon AIStor's robust AI capabilities, MinIO's PromptObject has been enabling users to interact with their data through natural language queries as described here. PromptObject transforms how users interact with stored objects by allowing them to ask questions about their data's content and extract information using natural language—eliminating the need to write complex

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Enterprise AI Infrastructure Made Easy with AIStor and NVIDIA GPUs

Enterprise AI Infrastructure Made Easy with AIStor and NVIDIA GPUs

Modern enterprises seeking to leverage AI capabilities often face a significant hurdle: the complex deployment and management of GPU infrastructure in their Kubernetes environments. MinIO's AIStor addresses this challenge head-on by integrating the NVIDIA GPU Operator, revolutionizing how organizations deploy and manage GPU resources for AI workloads. Through automated GPU setup, driver management, and resource optimization, this integration

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MLflow Model Registry and MinIO

MLflow Model Registry and MinIO

MLflow Model Registry allows you to manage models that are destined for a production environment. This post picks up where my last post on MLflow Tracking left off. In my Tracking post I showed how to log parameters, metrics, artifacts, and models. If you have not read it, then give it a read when you get a chance. In this

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Unlocking AI/ML Performance with AMD + MinIO

Unlocking AI/ML Performance with AMD + MinIO

In the rapidly-evolving world of artificial intelligence (AI) and machine learning (ML), speed and scalability are paramount. The ability to process massive amounts of data in real-time is a critical requirement for organizations looking to leverage AI/ML for competitive advantage. Whether it's training large machine learning models, running complex inference tasks, or scaling data pipelines, the performance

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Mitigating Geopolitical Concerns with a Sovereign Private Cloud

Mitigating Geopolitical Concerns with a Sovereign Private Cloud

2025 has inherited a slew of geopolitical concerns that started years ago. U.S. Foreign policy, U.S. - China Relations, China’s geopolitical maneuvers, Conflicts in the Middle East, Russian Ukraine war, and cybersecurity threats. Additionally, new leadership in the United States adds to the uncertainty created by these concerns. And, as if all this were not enough, the

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Model Checkpointing using Amazon’s S3 Connector for PyTorch and MinIO

Model Checkpointing using Amazon’s S3 Connector for PyTorch and MinIO

In November of 2023, Amazon announced the S3 Connector for PyTorch. The Amazon S3 Connector for PyTorch provides implementations of PyTorch's dataset primitives (Datasets and DataLoaders) that are purpose-built for S3 object storage. It supports map-style datasets for random data access patterns and iterable-style datasets for streaming sequential data access patterns.  The S3 Connector for PyTorch also includes

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The Innovations from AWS re:Invent

The Innovations from AWS re:Invent

Earlier this month, Amazon held their re:Invent conference in Las Vegas, Nevada, from December 1st to 5th - a 5-day event.  If you have never been to a re:Invent conference, then the word that describes it best is “huge” - not just in terms of the number of attendees (60,000) but also the breadth of topics covered.

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Iterable-Style Datasets using Amazon’s S3 Connector for PyTorch and MinIO

Iterable-Style Datasets using Amazon’s S3 Connector for PyTorch and MinIO

In November of 2023 Amazon announced the S3 Connector for PyTorch. The Amazon S3 Connector for PyTorch provides implementations of PyTorch's dataset primitives (Datasets and DataLoaders) that are purpose-built for S3 object storage. It supports map-style datasets for random data access patterns and iterable-style datasets for streaming sequential data access patterns.  In a previous post, I introduced the

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