Over the past year, the global data centre industry has witnessed the start of a truly transformative era, driven by the widespread accessibility and adoption of large language models (LLMs).
Adopting Generative AI (GenAI) is becoming a competitive necessity for many, yet with all forms of IT solutions, there is no one-size-fits-all option. For those organisations that prefer the security and control of colocation, many will now need to make sure their providers have adequate infrastructure and expertise to help them support their AI ambitions.
If you're thinking about deploying any form of AI with your colocation provider, make sure they're hitting this criteria.
Training models
In the GenAI realm, an AI model serves as a virtual brain, employing sophisticated algorithms to process data, recognise patterns, and make informed decisions. Training an AI model involves exposure to extensive data sets for learning and pattern recognition. With popular open source models like Llama2, this is typically done in two stages. Firstly, on a wide corpus of internet data, and then fine tuned on private data. It also requires a huge amount of power to get it to this point.
The training process empowers the AI model to think through situations, adapt over time, and enhance its decision-making capabilities. Subsequently, the inference process applies the trained model to new, unseen data, allowing it to make predictions or decisions based on its training on specific data.
Preparing for GenAI Implementation in Data Centres
Before deploying GenAI, IT leaders must address foundational tasks such as identifying a suitable model, gathering relevant data, and training the model. Data privacy is high on the agenda for many decision makers. Although OpenAI has said it is not sharing inputted data with other users, many remain wary about what happens to the data shared with a black box model like ChatGPT that's running on a third-party hyperscaler.
What is just as key as the model for data privacy however is choosing where it should be deployed. Organisations in highly regulated industries like finance and healthcare must consider the infrastructure implications of deploying GenAI. Colocation can offer the preferred solution, with greater control, security, and compliance with industry standards than many public cloud alternatives.
GenAI and the data centre
As GenAI creates a massive shift in the data centre landscape, there are two key criteria to make sure your data centre provider is adhering to fully capitalise on this technological revolution.
Capacity: The accessibility of publicly available GenAI models has triggered a surge in demand for supporting infrastructure. You'll want to make sure your provider can scale up to meet your requirements as GenAI continues to evolve as ServerChoice did with its latest data hall expansion.
Power: With some estimates suggesting that AI's power requirements will be more than that of a small country, data centre providers can help to alleviate these costs by making sure their infrastructure is as energy efficient as possible. Find out about ours here.
To help support the AI ambitions of their customers, data centre providers are making sure they're adjusting their services to the new AI reality. If you're wondering how to best deploy AI in a colocation environment, find out how we can support you.
