Researchers predicts that, with the right tools and collaborations, AI projects will soon be less artificial and more intelligent.

Instead of needing to rely on machine learning to think up different scenarios with swathes of backlogged data, future AI projects are likely to be faster and more intelligent, and require less data.

This may come as some relief to businesses struggling with data quality issues, or figuring out how best to fit different AI systems together.

Here are three ways AI is being fast-tracked to reveal a more human-led automated future.

• Personalisation from smart homes

Increasingly, smart homes will not just live up to but exceed our expectations. Your house is now able to use sensors, devices, applications and whole rooms to collect data on how you use it. Having learnt about your habits and consumption patterns using complex algorithms, your house will then personalise your experience at a granular level.

Late last year, Apple, Amazon, Google, and Zigbee, announced their push to develop standards for Internet-connected smart home devices that can interoperate – exciting news for many consumers frustrated with products working in isolation.

• Instant healthcare insights

With staff shortages and overwhelming workloads, AI tools are being fast-tracked to help speed up healthcare delivery and better manage patient outcomes.

New Zealand’s own global digital health provider, Aceso, with cloud-service partner Umbrellar, in 2018 created a first-of-its-kind instant data warehousing solution for medical imaging specialists, Mercy Radiology.

The dashboard delivered immediate insights to enable Mercy Radiology staff to rapidly understand and guide future decision-making for the business’ data strategy.

Aceso explains their ‘fast delivery’ mentality was key: get something up and running as quickly as possible, and then learn and iterate.

• Driverless cars

Autonomous vehicles use advanced AI capabilities, including automated vehicle guidance and braking, cameras and sensors for collision avoidance, and lane-changing systems. Sensors able to pick up on data in real-time allow vehicles to stick to their lane, avoid other vehicles, slow down and stop when needed – all doing so instantly to avoid accidents and ensure safety.

According to self-driving vehicle company Waymo – formerly the Google self-driving car project, their “self-driving sensor suite consists of LiDAR [light detection and ranging], cameras, and radar, as well as microphones to detect sounds such as sirens” that are meant to mimic a “person’s own five senses”.