woensdag 24 december 2014

Chef Watson: reciparrhea

Earlier I wrote about IBM's attempt at computational gastronomy, finding it a bit of a trainwreck. Recently I have been accepted as a Beta-tester for their Chef Watson, an online program that helps you create novel recipes calculated from ingredient relationships culled from 1000ands of recipes. The exact mechanisms are kept under wraps. Every time I read their description of it as "a system that could reason about flavor the same way a person uses their palate by capturing tens of thousands of existing recipes through natural language processing techniques to understand ingredient pairings, ingredient-cuisine pairings and dish composition" I can't stop giggling like a second rate Jonathan Creek but still, I can't help being fascinated.


Here is how you start, let's see what we can do with broccoli.



Watson suggests matching ingredients, dishes and cuisines. It seems that the style is optional but the dish mandatory to proceed to the recipe. Notice that these suggestions are in classic mode and the top matching ingredient is butter. Open the creativity notch a bit and the suggestions change with it:



What happens I think is that it works on frequency counts of ingredient pairs. Whatever you do with your broccoli it will involve butter at some point making it the most associated ingredient and therefore the most classic. It begs the question if butter really is an ingredient you would use as a key component of a dish. Further proof of Watson selecting ingredients on frequency comes when we are selecting for 'surprise' as much as possible:


Now there is some weird vinegar at top but look at the second one: first it was black pepper and now it is black peppercorns. This is the same ingredient but named slightly different which eludes the program. Mustard will be used in conjunction with broccoli often but rare are the recipes suggesting Dijon mustard and consequently it becomes a novelty ingredient for experimental chefs. If you would force all these variations into one the number of possible recipes would shrink enormously. I have checked if these suggestions are explainable by foodpairing based on aroma compounds and the answer is: no. So this based on recipe predominantly.

While you are selecting the ingredients, styles and dishes Watson gives you plenty of info, as you can see.




Add a few more ingredients and generate the recipe:



This is not all, the steps go on after the screenshot. It is a lot of text and by changing the slide at the top there are a number of variations of this recipes (50? 100?) to be explored. I think you will need the patience and the free time of a monk to evaluate them all and that is just for one set of ingredients. Wisely IBM has added the following disclaimer:

"Remember that Chef Watson eats data, not real food. The ingredients and steps are suggestions, so be sure to use your own judgement when preparing these dishes. And, give us feedback to make the Chef smarter."

If you want a bit of fun it can create recipes for things like: Indian lemongrass bouillabaisse, Korean turnip stroganoff cheesecake and French almond milk tiramisu pancake. The biggest problem with Chef Watson is that food is not about data but about memory and place, company and good times. It generates data but it fails to translate into an experience. It only goes to show that every Watson needs a Livingstone.

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