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Fine-tuning pre-trained AI models is a challenging task in itself. What strategy should you use and what resources do you require? This article presents a comprehensive overview of the AI model fine-tuning process.

We’ve had a very productive first quarter of 2025 at Nebius AI Studio, shipping major features, adding powerful new models and significantly expanding our infrastructure. This comprehensive roundup covers everything we’ve launched and where you can find us next.

If you work with personal data and need to store it in the cloud, you have to choose a cloud provider that offers appropriate storage. If you’re wondering whether our cloud can store and process personal user data, the answer is yes. Our platform ensures the secure storage of personal data, in full compliance with applicable regulations. But what does that mean in practice? Let’s break it down.

The increasing adoption of AI cloud solutions highlights the need for efficient, vendor-independent orchestration tools. dstack provides an open-source, AI-focused orchestration platform that emphasizes flexibility and ease of use for AI development. We are announcing an integration with dstack to enhance the developer experience for professional ML teams. You can now choose Nebius in dstack and start managing dev environments, executing training jobs and deploying models on our AI infrastructure.

Nebius AI Cloud is collaborating with NVIDIA Inception, a leading program for AI startups with over 22,000 members, to accelerate AI startup innovation. Nebius’ AI Lift program — announced at NVIDIA GTC 2025 — offers eligible NVIDIA Inception members up to $150,000 in cloud credits, access to AI technical expertise and support and a range of other exclusive benefits.

The end of the quarter is a great time to reflect and share a kind of changelog with you, highlighting what’s improved in Nebius AI Cloud over the past three months. This quarter, we launched new regions, released new services for MLOps and enhanced our existing product lineup to minimize your infrastructure concerns even further.

We wrapped up our first series of technical meetups with stops in Paris, London and San Francisco — each time providing a deep dive into our cloud. Here, you can watch all the talks from the first event in the series.

NVIDIA GTC was the highlight of last month for us. Our extensive participation included being a platinum sponsor, a strong presence with the booth, two tech talks, interviews with our leaders, partners and customers, and much more.

We’re excited to announce our integration with SkyPilot, an open-source framework that simplifies running AI and batch workloads across cloud platforms. This collaboration enables direct access to Nebius AI Cloud resources via SkyPilot.

Managed Service for MLflow becomes generally available — which means it gains more stability, a newer version of the platform, service level agreements and a service fee.

Today, we’re excited to announce that JupyterLab is now available in our Standalone Applications service, running on NVIDIA GPUs on our cloud platform. This fully managed offering eliminates infrastructure complexities, allowing you to focus entirely on your AI and machine learning (ML) projects.