Generative AI is reshaping creative industries, and music is no exception. With the Generative Music AI market valued at $440 million in 2023 and companies like Suno boasting a $500 million valuation and 12 million users, the industry is booming. And with an expected annual growth rate of 30.4% through 2030, the opportunities are limitless.

At the forefront of this exciting field is SongGen.AI, a trailblazer in AI-powered music creation. But innovation comes with challenges—training resource-heavy models, scaling infrastructure, and managing costs can be daunting.

That’s where GreenNode AI Platform comes in. More than just a cloud provider, GreenNode offers SongGen.AI the high-performance GPU infrastructure they need to train faster, scale effortlessly, and innovate without limits. By handling the technical complexities, GreenNode allows SongGen.AI to focus on what they do best: creating groundbreaking AI-powered music solutions.

In this blog, we’ll share how GreenNode supports SongGen.AI’s journey, helping them shape the future of music creation.

Let’s dive in!

SongGen.AI: Pioneering the Future of Generative AI in Music

SongGen.AI, a rising star in Vietnam’s tech landscape, is rewriting the rules of music creation. Born from the vision of a passionate team at the crossroads of music and technology, their mission is simple yet profound: to revolutionize how music is made and monetized. With an AI-powered platform trained on over 2 million licensed songs, SongGen.AI doesn’t just generate vocal and instrumental tracks; it creates custom, licensable masterpieces tailored to cultural and linguistic nuances.

Unlike global giants like Suno or Udio, who focus on broad-spectrum solutions, SongGen.AI takes a different path—localization. From the soulful melodies of Vietnamese Bolero to traditional folk harmonies, SongGen.AI delves deep into the heart of regional music, crafting songs that feel authentic and resonate deeply with local audiences.

Blog 36.jpg — SongGen.AI’s journey hasn’t been without its share of challenges

Their work not only bridges cultural gaps but also empowers content creators and music businesses with seamless tools to generate, distribute, and monetize music on platforms like YouTube, TikTok, and Spotify.

However, behind this innovation lies a story of grit and determination. SongGen.AI’s journey hasn’t been without its share of challenges.

Challenges in Building AI-Powered Music Solutions

When SongGen.AI embarked on its mission, the road was anything but smooth. There were no open-source frameworks or plug-and-play solutions for generating complete songs with vocals. The team had to build everything from scratch—laying the foundation for their AI models, brick by brick.

Data posed another challenge. While global datasets for popular genres abound, high-quality, localized music data—especially for niche styles like Bolero—was painfully scarce. It wasn’t just about sourcing; it was about curating a dataset that could truly represent the soul of the region.

Blog 39.jpg — The music industry is a labyrinth of copyrights and licensing

Then came the legal hurdles. The music industry is a labyrinth of copyrights and licensing. Securing permissions to use music catalogs meant navigating a maze of contracts and negotiations, a daunting task for any startup.

As if these weren’t enough, finding the right talent added another layer of complexity. Skilled AI/ML engineers with expertise in music technology are a rare breed, and the few available are often in high demand.

Finally, the backbone of SongGen.AI’s innovation—its computational infrastructure—presented its own set of obstacles. Training AI models from scratch requires immense computing power. For a startup, investing in traditional cloud GPU providers like AWS or Google Cloud meant facing prohibitive costs and overwhelming technical complexities. And with limited experience in large-scale AI deployment, the team needed more than just hardware; they needed guidance.

A Journey to Solve Infrastructure Challenges with GreenNode

Despite these barriers, SongGen.AI remained steadfast in its mission. They knew the answer lay not just in having the right technology but in having the right partners. Scalable, affordable GPU solutions combined with expert technical support would be the key to breaking through their constraints.

Blog 40.jpg — The answer lay not just in having the right technology but in having the right partners

With the right infrastructure, SongGen.AI could turn their challenges into opportunities—accelerating model training, scaling operations, and focusing their energy on what they do best: redefining music for the modern world.

Their goal was clear—ethical, scalable AI training with a platform that could support their ambitious growth plans while managing costs effectively.

A Detailed Comparison of Cloud Providers

The team has been presented with various option. When exploring GPU service providers, they used similar pre-existing models to conduct benchmarks, measuring and calculating the pros and cons of each solution. This process helped the team identify the most suitable solution based on both technical requirements and budget.

Feature/Criteria	Runpod	GreenNode	AWS	Google Cloud
Pricing	Low-cost	Competitive	Higher-end	Higher-end
GPU options	Wide range	Limited (H100, 4090)	Broad range	Broad range
Scalability	Low, mostly single-node (8xH100)	Medium, up to 11 nodes (88xH100)	Very High, up to 20,000xH100 (Ultra-cluster)	High, up to hundreds of H100
Performance	Good	High	High	High
Community/Support	Good but sometimes slow	Fast & supportive, provide in-person technical support	Basic to Enterprise	Basic to Premium
Customization	High	Moderate	High	Moderate
Availability	Low	Good	-	Low
Target Users	Small/mid-sized startups	Small/mid-sized startups	Enterprise & large-scale AI teams	Enterprise & research teams

Through testing and evaluation, SongGen found that the cost of using high-end providers like AWS or Google Cloud was 3 to 5 times higher in terms of GPU usage hours compared to other solutions. This motivated SongGen to seek more cost-effective options that still ensured high performance and scalability, helping to reduce operational costs while maintaining the quality of their AI models.

From Single-node Training to Multi-node Training

Initially, they turned to RunPod, hoping to find a solution that could meet their needs for training AI models capable of generating custom music tracks. However, as they progressed with their experiments, SongGen quickly realized that while RunPod offered a functional service, it wasn’t delivering the performance or support they needed to scale effectively.

Blog 41.jpg — SongGen required not only a powerful GPU infrastructure but also a partner who could provide consistent, expert support

As a fast-growing startup, SongGen required not only a powerful GPU infrastructure but also a partner who could provide consistent, expert support. That’s when they found GreenNode. After assessing their requirements, the team at SongGen decided to transition to GreenNode, driven by several key factors.

One of the biggest advantages GreenNode brought to the table was the GreenNode AI Platform. It is cost-efficient, high-performance multi-node training model, which was specifically optimized for AI and machine learning workloads.

	RunPod	GreenNode
Configuration	Single node with 8xH100 SXM5	2 nodes with 16xH100 SXM5 with InfiniBand
Training time	9.3 hours	4.5 hours (x2)
Total costs	$289	$280

SongGen had the opportunity to test GreenNode’s multinode setup, and the results were striking. Thanks to GreenNode, SongGen was also able to dramatically accelerate their training timelines 106% faster with even better price. For instance, the fine-tuning of SongGen’s large language model (1.5B parameters) on a 36-hour dataset took just 9.3 hours on a single node with 8xH100 GPUs, and just 4.5 hours when they expanded to two nodes. This efficiency allowed SongGen to quickly iterate and improve its models, keeping pace with the fast-moving AI space.

But it wasn’t just the hardware that set GreenNode apart—it was the expert support that the team received. GreenNode provided not only the necessary resources but also guidance throughout the model training and deployment process.

The partnership with GreenNode allowed SongGen to focus on what truly mattered—innovation and creativity—without being bogged down by backend challenges. GreenNode’s reliable infrastructure and hands-on support allowed SongGen to push the boundaries of AI in music, helping them create an AI-driven platform that could generate custom, licensable music at scale.

Lessons Learnt from Songgen.AI’s Journey

As SongGen.AI embarked on its journey to revolutionize the AI-driven music industry, Khoa Tran, the company’s CTO, shared valuable lessons learned from their experience.

The first lesson centered around ethical AI practices in the music industry. As the team worked on their AI models, they realized that transparency and fairness were crucial. They weren’t just building a tool to generate music—they were entering a space heavily governed by copyright, and they needed to ensure that their models did not infringe upon the intellectual property of artists and labels. This meant being mindful of dataset selection and constantly checking for bias in their algorithms.

For startups aiming to follow a similar path, Khoa stressed the importance of market research and product positioning. “Before we dived into developing the platform, we had to understand the market and what real problems we could solve,” he explained.

Blog 42.jpg — AI is complex, especially when models need to be trained from scratch

Another critical lesson Khoa shared was about investment in R&D. AI is complex, especially when models need to be trained from scratch. It requires a significant commitment of time, money, and resources. Khoa emphasized the importance of staying connected to the latest research, as the field of AI evolves quickly. “In AI Music alone, by early 2024, many different teams released papers with new architectures to solve the same problem. We had to keep learning, experimenting, and implementing new ideas to stay ahead.”

Khoa also discussed the importance of building a diverse team. “AI development is not a solo effort. To move quickly, you need a team with diverse skill sets. Encourage your team to think outside the box, experiment, and be prepared to learn from failures,” he explained.

Khoa’s final piece of advice for any startup looking to break into AI was this: “Focus on solving real problems with technology, and find partners who can help you scale efficiently. For us, GreenNode was that partner.” With this guidance, SongGen continues to innovate in the music industry, driven by the belief that AI can change the way music is created, shared, and experienced.

Final Thoughts

As AI/ML continues to reshape industries, the need for scalable, efficient infrastructure is more important than ever. GreenNode provides the high-performance GPU solutions and expert guidance that startups and enterprises need to overcome the technical challenges of AI development. By leveraging GreenNode's infrastructure, you can focus on your core mission—driving innovation and creating impactful solutions.

For those working on AI-driven projects, whether you're building generative models or tackling complex machine learning challenges, GreenNode AI Platform offers more than just infrastructure. With tailored support and a deep understanding of AI’s evolving landscape, GreenNode helps ensure that your technical resources align with your vision, empowering you to achieve your goals faster and more efficiently.

Reach out today to explore how GreenNode can support your journey in building the future.

Revolutionizing Music Creation with AI application: A Practical Use Case from SongGen.AI