AI case studies from the real-world

Deschutes Brewery decreases beer fermentation cycle time using machine learning to optimise scheduling and monitoring of brewing processes

Farmers are able to track cows and monitor their activity and optimise food production through machine learning

Kewpie, a Japanese food manufacturing company, used deep machine vision that identified defective potato cubes on the production line with the same level as accuracy as humans

Ocado has automated delivery product picking by building robotic warehouses

University of Melbourne researchers achieve 94% accuracy identifying grape vine varieties using leaf images and neural networks

Deep Stack's poker AI delivered statistically significant wins in Texas Hold 'Em poker games through deep learning.

The International Gymnastics Federation plans to implement AI technology to assist judges with scoring at the Tokyo 2020 Olympic Games

The XiaoIce chatbot automatically generates poems based on images using neural networks

Abellio London claims it reduced bus collisions and injuries by 29% and 60% respectively with collision avoidance technology

CARFIT is offering real time issue detection on tires, wheels, shocks and brakes with machine learning

CCC Information Services predicts repair requirements from vehicle collision photos using AI

Driverless street sweepers able to clean a park in less than 20 minutes employed for trial run in Shanghai's Tus-Caohejing Science Park

Tesla falls more than 15% short of Model 3 production goal due to over-automation of the production line

TuSimple successfully completed a 200-mile level 4 test drive of a driverless truck passed from San Diego to Yuma, Arizona.

Big River Steel maximises energy consumption at off-peak times to minimise energy costs using an AI powered optimisation model

Big River Steel predicts and optimises the maintenance of its machinery and equipment using machine learning.

Newcrest Mining prevents mill downtime at its Lihir mine using machine learning to predict when an overload is about to occur

Roy Hill iron ore project is developing a transportation vehicle maintenance prediction and prevention recommendation platform

South32 trials first fully autonomous drone system from Airobotics for mine surveillance

Abundant Robotics device autonomously harvests apples using machine vision to identify appropriate fruit

Alibaba Group detects pigs' pregnancy seven times quicker using facial recognition technology

Blue River Technology offers deep learning technology which is aspiring to reduce herbicide usage by offering a more precise and targeted spray application

Farmers are able to quickly identify issues such as crop stress and disease and pest infestation on heatmaps enabled by drones and machine learning

ICRISAT and Microsoft advise farmers on when to sow crops resulting in a 10-30% yield per hectare increase by using machine learning

Iron Ox fully automates the growing process end-to-end with the potential of 30 times more produce than traditional farms

Makoto Cucumber Farm automatically sorts cucumbers based on shape, length and distortion using deep machine vision

McCain will test Resson's image recognition algorithms for crop condition monitoring to optimise potato yields and reduce costs

PEAT identifies 400 diseases and pests from farmers' uploaded photos on their new mobile app

Researchers from the University of Lincoln have built a learning computer system to early detect potentially harmful flaws in production and packaging of potatoes

Slantrange aims at measuring crop populations and detecting weeds with machine vision