MinIO

MinIO delivers Exascale Object Store for AI Data, Agentic Computing, and Analytics with unmatched enterprise performance.

[MinIO @Minio]

MinIO MemKV is a new class of infrastructure. ✨

For years, we’ve focused on the data foundation for AI. Today, we’re extending that foundation into the inference layer, where efficiency and performance define success.

What does this mean for the stack and the future of AI? Co-CEO and co-founder Garima Kapoor explains.

[MinIO @Minio]

Autonomous driving runs on data. Lots of it.

A leading North American automobile manufacturer built a global AI data platform with MinIO AIStor to support autonomous driving, simulation, and analytics at an extraordinary scale.

The result: a high-performance, cost-efficient foundation for AI that can grow with the business.

👉 Find out how they did it: https://t.co/OvB5IUYVNw

[MinIO @Minio]

MinIO AIStor and MemKV now support NVIDIA Vera BlueField-4 STX, delivering a secure AI data path from persistent S3 object storage to in-context GPU memory.

Together, MinIO and @nvidia help enterprises build secure-by-design AI factories where every byte moving through the AI data pipeline is protected, governed, and delivered without compromise.

Learn more about the announcement from #GTCTapiei at #COMPUTEX. https://t.co/OhImmw9Qkb

[MinIO @Minio]

If the recompute tax is the problem, why hasn’t anyone solved it yet?

Because AI infrastructure was never designed to preserve context at GPU scale.
So every follow-up request forces the system to rebuild the state repeatedly, wasting expensive GPU cycles.

MinIO MemKV creates space in GPU memory, offloads the KV cache, and instantly recalls context when it’s needed again. The result is less recompute, more decoding, and higher effective GPU utilization.

👇 See how MemKV helps eliminate the recompute tax.

[MinIO @Minio]

We're excited to join the global data and AI community at @databricks #DataAISummit. From sessions and demos to technical deep dives and meetups, it's going to be an incredible week on the future of AI, analytics, and data architectures. 🚀

Stay tuned for a full lineup of activities. https://t.co/czlEDg3Ct9

[MinIO @Minio]

📣 This week at @starburstdata AI + Datanova: CTO Ugur Tigli is helping financial services build AI-ready data infrastructures.

From governance and federated data models to scaling AI across complex, regulated environments, this panel discussion, alongside Citizens Financial and TIAA, will offer insights into what it takes to move AI from experimentation to enterprise-scale deployment.

👉 See the full agenda: https://t.co/BG8j2b2khg

[MinIO @Minio]

Federal agencies are in a new phase of AI adoption, where infrastructure decisions will define long-term success.

As VP of Public Sector Deep Grewal writes for @FederalNewsNet, scalable federal AI demands modern architectures built for resilience, portability, and operational independence across hybrid environments.

The path to trusted AI starts with the foundation. https://t.co/fBc2iyMlAV

[MinIO @Minio]

Try it for yourself 👉https://t.co/N5aChXIOS3

[MinIO @Minio]

Most vendors approach “context memory” by adapting general-purpose caching systems originally designed for file servers. We’re not most vendors.

MinIO MemKV is the first purpose-built context memory store for AI inference. It’s built differently and delivering results 🧵

[MinIO @Minio]

Runs as one ARM64-native binary embedded in the NVIDIA STX, not a separate cluster connected over the network.

[MinIO @Minio]

It’s been one week of MinIO MemKV out in the world.

Successful AI inference at scale requires making sure that no GPU resources are wasted, and only a purpose-built context store like MemKV can do that.

Find out what all the talk is about. 👇

[MinIO @Minio]

MinIO is a proud sponsor of @starburstdata AI + Datanova in Miami 🌇

AIStor is the only on-premises object store with a built-in Apache Iceberg REST catalog, giving Starburst a single system for data and metadata, with fewer moving parts and scalable performance for AI and analytics.

Let’s connect. https://t.co/BG8j2b2khg

[MinIO @Minio]

Safely reclaim storage AI-assisted operations in our upcoming webinar with Curriculum Engineer Ravind Kumar.

Through live demonstrations and a simple framework, you'll see how administrators can confidently manage versioned object storage at scale.

This is a must-watch session for administrators working with modern AI data workloads.
📅 Tomorrow, May 20,
⏰ 10 AM PDT
🔗: https://t.co/kE2BGyaWhb

[MinIO @Minio]

From co-founder and co-CEO AB Periasamy: As GPU density and context windows grow, recomputing prior work becomes a constraint on throughput, power, and economics.

What’s emerging now is a new layer in the stack centered around shared context and inference efficiency. That's MinIO MemKV.

[MinIO @Minio]

The biggest threat to a live stream? Storage that can’t keep up. 👀

From live sports to on-demand entertainment, this global streaming platform needed to deliver low-latency experiences at massive scale, especially during peak traffic.

Viewers never missed a second because MinIO AIStor powered fast, reliable streaming across 10+ data centers worldwide.

👉 https://t.co/BPxNQBz8q2

[MinIO @Minio]

AI infrastructure depends on treating context as a persistent shared state, improving efficiency, lowering inference costs, and helping enterprises scale AI workloads more effectively.

MinIO MemKV is designed to make that possible. Go deeper with CTO Ugur Tigli in @thenewstack. https://t.co/AbHd82KHvN

[MinIO @Minio]

Most organizations still rely on broad lifecycle rules or manual cleanup processes that either miss reclaimable capacity or introduce operational risk.

Join our upcoming webinar to see how AI-augmented administration enables safer, more precise storage reclamation in AIStor environments.

Live demos + practical workflows included. https://t.co/kE2BGyaWhb

[MinIO @Minio]

Your GPUs are busy. But are they generating value?

MinIO MemKV turns context into a shared, persistent resource across the GPU cluster — eliminating recomputation and dramatically improving inference efficiency.

Real throughput. Real utilization. Real ROI.