Meanwhile, over in the education space, Neil Fraser, Macquarie University director of information, said most successful AI tasks (be they supervised or unsupervised), are replacing activities beyond our human capability.
“Plenty of definitions are out there on AI but for me this is about the age of machine learning (supervised and unsupervised) which is where we’re applying statistical approaches and modelling to data. The transformational shift is the massive drop in the cost of computing in parallel with an unprecedented explosion in data volume and variety.”
He said the opportunities for the education space come “anywhere where this transformation shift threatens the underlying value chain of the business and data products can find a footing.”
Connecting the dots
No matter the industry, Lenovo’s Almeida said businesses need help putting the pieces together.
Asked how companies can prepare to get onboard the journey, he said businesses need to consider: How does AI benefit my business? How does it apply to my business? How can businesses use it? And how can they turn what’s typically considered a start-up scenario into a business outcome?
“We engage with customers, we show them examples of AI in businesses similar to them, then we develop that idea, which applies to their business, and customise it to show them how that would apply to their business, and then we help them deploy that by creating a system. Training the system and delivering a workload or a workflow, or a system that they can actually utilise.”
When looking at the AI workflow, he said several things come to light. “One is you need to have a lot of data because the data is used to train the system - that’s the training phase of AI. If you have unstructured information or unstructured data, or structured data, it doesn’t matter. Then you train the system.
“Then you have an inference point where you actually consume the information. The information from that trained system. And we stop right there. We help the customer create that training environment, create the model to train. Then when it comes to inference and utilising, that’s where we hand over to the business. That’s now part of the business to move along and create whatever it is that they want to be doing with it.”
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