An at-a-glance look at AI in action
The use of artificial intelligence (AI) is booming. In fact, the AI industry is set to be worth $1.2 trillion by the end of 2018, a 70% increase from 2017, according to the latest report released by Gartner last week. The global research firm predicts that by 2022 AI-derived business value is estimated to reach up to $3.9 trillion.
“AI promises to be the most disruptive class of technologies during the next 10 years due to advances in computational power, volume, velocity and variety of data, as well as advances in deep neural networks (DNNs),” said John-David Lovelock, research vice president at Gartner.
Many of the world’s largest tech companies including Google, Apple, Microsoft, IBM, and Nvidia are investing heavily in the development of AI-based products and services which are being used to improve customer experiences, drive new revenue streams, and as a way to reduce costs.
As AI begins to infiltrate its way into our lives, we take a look at the impact this tech is having on a range of industries:
Creating art: German researchers have used a convolutional neural network to render a photo they took of a town into the style of a famous artist. They created an algorithm which allowed them to combine Van Gogh’s Starry Night style with the photo they took creating a new form of AI-art.
Composing music: Alex Da Kid’s single ‘Not Easy’ featuring X Ambassadors, Elle King, Wiz Khalifa, which was released last year, used IBM Watson’s AI technology to help inspire him to write the lyrics and compose the music for the song. The single reached number four in the iTunes Hot Tracks chart, and number six in the alternative chart, within 48 hours of its release.
Cucumber farming: A Japanese cucumber farmer is using AI to sort and grade its produce. It introduced an AI-enhanced camera in 2016 that can identify shape, size and sort the cucumbers, saving the farmer many days labour.
Enhancing search: The success of search has been amplified by new AI-powered software that can intelligently guess what the user is looking for, despite spelling mistakes, typos or them not using specific keywords. For example, AI tools can now know when someone writes “season icket” into search that they mean “Season ticket”.
Giving financial advice & managing risk: The Australian company ANZ Global Wealth has been using IBM Watson to help manage its financial risk, using the Watson Engagement Advisor Tool, an NLP SaaS offering, to observe and field customer questions. Similarly, DBS bank in Singapore is using IBM Watson to support advisors in its wealth management business.
Intelligent vending machines: Coca-Cola is developing AI assisted vending machines to personalise the user experience in the US. Users will be able to ask the drinks dispenser for their favourite blend of drink (in the States users can add a ‘flavour shot’ to enhance their drink). Reportedly, the machines will also behave differently depending on where they are situated.
Recommending products: Amazon has been spearheading developments in product recommendations on its site for some time. Its ‘customers who bought this item also bought’ message has inspired other platforms to adopt this model including Netflix and Spotify.
Valuing second-hand cars: Autotrader, the online car marketplace, is using machine learning to generate accurate valuations of second-hand vehicles.