What infrastructure is needed to train models and perform inference with the boom in Generative AI?

Cloud computing offers scalability, flexibility, and cost-effective pricing models, making it an ideal choice for startups in this space. However, with so many cloud providers and services available, it can be challenging for generative AI startups to navigate the landscape and choose the best solution for their needs.   

In this blog post, we'll discuss some of the key considerations that generative AI startups should keep in mind when it comes to cloud computing.  

Generative AI startups need to be able to scale their computing resources as AI models go through the phases of pre-training, training, and inference. Startups should choose a cloud provider with state-of-the-art resources to accommodate the entire development lifecycle. This will help them avoid downtime or service interruptions due to inadequate resources.   

For example, OpenAI leveraged Cirrascale Cloud Services (before Microsoft) to scale model training with large, tailored GPU configurations unavailable at the major cloud service providers. Cirrascale offers access to the newest GPUs and AI Accelerators (Cerebras, Graphcore, and SambaNova) in our AI Innovation Cloud so startups can try everything in one place.  

2. Latency and Speed
Generative AI models require significant computing resources to generate content in real-time. Startups should choose a cloud provider with low latency and high bandwidth networks to connect distributed training servers and transport data between storage and servers. This ensures that models can generate content quickly and efficiently.  

When GPUs in a cluster are located close to each other, communication is more seamless, and performance improves – like musicians in a symphony. Does the cloud service provider offer bare-metal servers with localized GPUs for enhanced performance? Do they only provide virtualized servers where performance deteriorates due to node distribution?  

3. Hardware Support / Maintenance and Cloud Provider Expertise  
Many AI startup teams do not have the interest or time to manage the infrastructure hardware behind the models they are training. Therefore, selecting a cloud provider with managed services and zero DevOps can be of enormous value. Cirrascale works with you to set up scheduling services, help with best practices, and provide superior support. This includes managing end-user access including private / public keys, whitelists, SSH access, and VPNs. We consider ourselves an extension of your team. AI leaders should select a cloud provider that is flexible in working with them and takes a hands-on approach.

4. Integration
Generative AI startups may use a variety of tools and frameworks to build their models, such as TensorFlow, PyTorch, or Keras. Startups need to ensure that their cloud provider supports these tools and provides seamless integration with their existing workflows. They should also consider using containerization technologies, such as Docker or Kubernetes, to ensure portability and ease of deployment across different cloud environments.   

5. Cost
One of the most significant considerations for generative AI startups is cost. Cloud computing can be expensive, especially when using high-performance GPUs for training generative models. Startups need to carefully evaluate their budget and choose a cloud provider that offers the most cost-effective pricing options for their needs. Is there flat-rating billing, or can the startup expect billing surprises? What ancillary charges will the startup incur, such as data egress and ingress?  

Cirrascale offers flat-rate billing, so you always know your bill. We don't nickel and dime you for ancillary fees.

6. Security
Generative AI startups often work with sensitive data, such as customer information or proprietary models. Startups need to choose a cloud provider that offers robust security measures. They should also ensure their cloud infrastructure is configured securely and follow best practices for securing cloud resources.   

By considering scalability, latency and speed, support, integration, cost, and security, startups can choose the best cloud provider for their needs and deliver high-quality generative content to their customers. 

If you're interested in working with Cirrascale, contact our team today.