D A T A C E N T R E P R E D I C T I O N S

Robin Ferris , Enterprise Architect , AI Lead at Pulsant

In the science industry in particular , scientists would generally have used a supercomputer – if they could access it – to run their trials of data through to try and find out the information they ’ re processing and gather information from their data . However , now what we ’ re seeing is that if you shift that same process and do it on AI , you save days of time . What a supercomputer can do in three days , AI can do in three hours . The AI is still using a lot of power , but to get to the same answer that we would have traditionally done with a supercomputer , it ’ s far more efficient . As we ’ re transitioning to newer , faster and more efficient technologies , we ’ re saving power .

What steps should organisations take when planning for scaling ?

This is a really hot topic for us at Pulsant because when working with our existing clients who are on their AI journey , as well as with new clients , it ’ s really key to understand that if you ’ re running AI workloads , you ’ re fundamentally running a GPU which uses a lot of electricity .

Organisations must question the level of scalability they desire and how much power they require to get there , as well as the length of the journey .

We have AI , we have some amazing data scientists , but it ’ s understanding what the impact is going to be – one of the fundamentals is how much power is going to be needed to drive your AI going forward , and when I say power I mean electricity because that ’ s essentially what we ’ re talking about .

What best practices can companies implement to ensure AI inference is as environmentally friendly as possible ?

It all comes down to electricity . If you were to take a country that is predominantly generating electricity from coal or heavy polluting processes like fossil fuels , you could suggest that an AI model developed in a country like that is going to be more environmentally unfriendly than a model developed in a country with a more environmentally friendly electricity infrastructure . I ’ m not claiming it would have zero environmental impact , but it ’ s certainly possible to draw some conclusions there .

Once we can process AI faster , we ’ re going to give it bigger programs and bigger problems to solve . But for now , it ’ s definitely moving in the right direction . �

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