As a developer of a calorie tracking service, also with an iPhone app in the App Store, I would point out that the example with calorie tracking does not work in RL.
1. There are hundreds of food chains in the US, with widely varying recipes, serving sizes, and nutritional contents. Even being familiar with the subject area, I generally won't be able to recognize a food. Even if I see a burger photo - how would I know the brand, flavor, whether it has cheese in it, etc. The error rate will be huge, rendering the service useless, and even worse - misleading.
2. You cannot estimate portion size on a photo, not having anything to compare with. This also results in significant errors.
I am not arguing against other uses of MT, just pointing out that this is a not very well thought through example.
MT is applicable only for very rudimentary tasks, requiring absolutely zero qualifications and training. There are fewer such tasks around than it looks at the first glance, as this example demonstrates.
1. There are hundreds of food chains in the US, with widely varying recipes, serving sizes, and nutritional contents. Even being familiar with the subject area, I generally won't be able to recognize a food. Even if I see a burger photo - how would I know the brand, flavor, whether it has cheese in it, etc. The error rate will be huge, rendering the service useless, and even worse - misleading.
2. You cannot estimate portion size on a photo, not having anything to compare with. This also results in significant errors.
I am not arguing against other uses of MT, just pointing out that this is a not very well thought through example.
MT is applicable only for very rudimentary tasks, requiring absolutely zero qualifications and training. There are fewer such tasks around than it looks at the first glance, as this example demonstrates.