Businesses can get carried away with the idea that they need an advanced deep learning system that can do it all, according to Alan Pelz-Sharpe. However, if they want to tackle a targeted use case, like automating an invoicing process, they don’t need an advanced system. These systems are expensive and use a lot of data, which means they have a high carbon footprint.

A specialized system will have been trained on a much smaller amount of data while still being capable of fulfilling a specific use case just as well as a more general system.

“Because it is highly specialized, this AI has been trained on the most precise data possible” while keeping a small set of data, says Alan Pelz-Sharpe. A deep learning model , on the other hand, has to stir up massive amounts of data to achieve anything.

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Work Intelligence Market Analysis 2024-2029