Gordon Rams-AI! Scientists develop a robot CHEF that can recreate recipes by watching cooking videos
- Researchers programmed a robot to make a meal by following a cooking video
- Over time, it is then able to identify which ingredients work best together
Gordon Ramsay better watch his back as there’s a new top chef in town – in the form of a robot.
The robo-chef can learn how to create the perfect dish, simply from watching cooking videos.
Researchers at the University of Cambridge have programmed a machine to make a meal by following how a human makes it.
Using sophisticated AI, the robot is able to work out from every frame which objects it is looking at – such as a vegetable, hand, or knife – and how it is being used.
Over time, it is then able to identify which ingredients work best together – and even point out when the human chef may have used the wrong amount.
Researchers at the University of Cambridge have programmed a machine to make a meal by following how a human makes it
Gordon Ramsay better watch his back as there’s a new top chef in town – in the form of a robot
£240,000 robot chef can whip up the perfect CHEESE FONDUE – READ MORE
A Swiss team has been working away on Bouebot, the robotic creation putting a futuristic twist on an Alpine tradition
Robotic chefs have been featured in science fiction for decades, but in reality, cooking is a challenging problem for a robot.
Several commercial companies have built prototype robot chefs, although none of these are currently commercially available, and they lag well behind their human counterparts in terms of skill.
Study author Grzegorz Sochacki, a PHD student from Cambridge’s Bio-Inspired Robotics Laboratory, said: ‘We wanted to see whether we could train a robot chef to learn in the same incremental way that humans can – by identifying the ingredients and how they go together in the dish. It’s amazing how much nuance the robot was able to detect.’
He added: ‘Our robot isn’t interested in the sorts of food videos that go viral on social media – they’re simply too hard to follow.
‘But as these robot chefs get better and faster at identifying ingredients in food videos, they might be able to use sites like YouTube to learn a whole range of recipes.’
It is hoped the findings – published in the journal IEEE Access – will enable easier and cheaper deployment of robot chefs.
The researchers first created a ‘cookbook’ of eight simple salad recipes and filmed themselves making them.
Using sophisticated AI, the robot is able to work out from every frame which objects it is looking at – such as a vegetable, hand, or knife – and how it is being used. Over time, it is then able to identify which ingredients work best together – and even point out when the human chef may have used the wrong amount
The robot chef – which was trained on neural networks, which essentially mimics how the human brain works – then watched 16 of these videos.
By identifying the ingredients and the actions of the human chef, it was then able to correctly determine 93 per cent of the time what was being prepared.
It was also able to detect slight variations in the recipe, such as a double portion.
The robot was also able to recognise a completely new ninth salad, add it to its cookbook and then make it.
The research was supported in part by Beko plc and the Engineering and Physical Sciences Research Council (EPSRC), part of UK Research and Innovation (UKRI).
WILL YOUR JOB BE TAKEN BY A ROBOT? PHYSICAL JOBS ARE AT THE GREATEST RISK
Physical jobs in predictable environments, including machine-operators and fast-food workers, are the most likely to be replaced by robots.
Management consultancy firm McKinsey, based in New York, focused on the amount of jobs that would be lost to automation, and what professions were most at risk.
The report said collecting and processing data are two other categories of activities that increasingly can be done better and faster with machines.
This could displace large amounts of labour – for instance, in mortgages, paralegal work, accounting, and back-office transaction processing.
Conversely, jobs in unpredictable environments are least are risk.
The report added: ‘Occupations such as gardeners, plumbers, or providers of child- and eldercare – will also generally see less automation by 2030, because they are technically difficult to automate and often command relatively lower wages, which makes automation a less attractive business proposition.’
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