Perfect storm of compute, data sets, algorithms

Particularly in the digital era, where organisations have access to volumes of data, there is a growing realisation that for enterprises to remain competitive, progressing an artificial intelligence and machine learning agenda — and using it to draw insight from the data — is not an option but rather a business imperative. Failing to do so would mean falling behind the competition and consequently being at a significant disadvantage in the market.  

The potential of artificial intelligence and machine learning is being unleashed by the combination of access to compute power, never previously possible through GPU technology, continually advancing algorithms and most importantly access to data at a volume and velocity that is absolutely staggering.

What we find is that many artificial intelligence and machine learning proof of concept initiatives start in the public cloud, benefiting from a low financial commitment and a fast time to deploy. But as the value is proven and the environment needs to scale, we see many organisations moving the workload on-premises where costs can be controlled and the environment optimised.  

The applications for artificial intelligence and machine learning are broad and we are seeing use-cases in just about every industry from insurance and telcos to finance and on to utility providers. But perhaps the most impactful area is healthcare. 

The ability to provide more accurate, faster and scalable medical diagnoses through the power of artificial intelligence and machine learning changes the entire dynamic in a world which is facing increasing pressure to deliver better patient outcomes, faster and at lower costs. 

Artificial intelligence and machine learning have been through several false dawns. That being said, because of the coming together of compute, algorithms and massive data sets, there is now a feeling that artificial intelligence and machine learning is here to stay. 

Taking AI from concept to actual production is based on several key aspects — having access to large high-quality data sets that have the potential to provide insights demanded by the business, a technology platform that provides exceptional performance, is easy to set up, deploy and manage and finally people with the required skills in data science to own and deliver the desired business outcome.

What will also be crucial in the evolution of artificial intelligence and machine learning will be public perception and the potential for governance. The ethics associated with artificial intelligence and machine learning is a growing conversation and one that needs to be had. 

At Pure Storage, the focus is on building solutions that deliver the modern data experience and enable businesses to accelerate adoption of artificial intelligence and machine learning. With Pure Storage, customers can deploy a reference architecture consisting of compute, networking and the data platform together with a curated set of software. 

Key takeaways

• Artificial intelligence and machine learning have been through several false dawns. 

• With compute, algorithms, data sets, there is a feeling that artificial intelligence, machine learning are here to stay. 

• Crucial in the evolution of artificial intelligence and machine learning will be public perception and potential for governance. 

By Patrick Smith, Field CTO EMEA, Pure Storage.