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CREATING STUNNING DISHES USING

GLOBAL RECIPE INTELLIGENCE

Dr Trevor Davis, IBM

Topics

Cognitive computing

Computational Creativity

Watson Chef v cooks – how can a bunch of

wires understand what is delicious?

Warning – science!

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Cognitive computing is a new paradigm

Understands

context and

natural language

More natural

interaction with

people

Adapts

and learns from

experience

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Cognitive isn’t AI

More active, more personal, better sensing, ubiquity, scalability

Supervised

learning

Unsupervised

learning

Weak AI Strong AI

Now 2020-2030 Mid Century 2080+

Many societal challenges ahead!

Multiple interpretations

Hundreds of answer

sources •Primary search

•Candidate answer generation

Tens of thousands of evidence

sources and scores •Answer scoring

•Evidence retrieval

•Deep evidence scoring

Learned models •Combine and weigh evidence

Inquiry analysis Decomposition Hypothesis generation Synthesis Hypothesis and

evidence scoring Final confidence

merging &ranking Question Answer

? !

At the heart of Watson is a learning system

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IBM Watson & computational creativity

2012 2013 2014

November 2012: first recipe created

and prepared by the team at the

Institute of Culinary Education

November 2011: project started in

Services Research department as

part of “What’s Our Watson” initiative

February 2013: first recipes

created by ICE Chefs and served

at IBM Investors Day

January 2014: Watson

Group announcement

March 2014: IBM Food

Truck at South by

Southwest

“To test its skill, we pitted IBM’s algorithm against go-to-

recipe resource Epicurious (owned by WIRED’s parent

company, Condé Nast). We searched the site for a

Caribbean plantain dessert and found a tasty concoction

with rum and coconut sauce. With the same

parameters, IBM’s computer generated a list of about 50

ingredients, including orange, papaya, and cayenne

pepper, from which IBM researcher and professional

chef Florian Pinel developed a mind-blowing Caymanian

parfait. While the IBM dessert tasted better, it was also

insanely elaborate, so we’ll call it a draw.”

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When an IBM algorithm cooks things get tasty

But isn’t creativity is a

purely human attribute?

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Formula for creativity?

Creativity

=

∫ (discovery, variety, combinations, novelty,

delight….)

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IBM Watson & computational creativity!

PEER PRODUCED INSPIRATION SET

COGNITIVE COOKING SYSTEM

NOVEL CUSTOMIZED RECIPE

FOOD KNOWLEDGE DATABASE

DYNAMIC PLANNER

COMBINATORIAL DESIGNER

COGNITIVE ASSESSOR

Recipe generation (discovery, variety)

Base Ingredient

Cuisines Dishes

Ingredient Pairings

Ingredient Types

New Recipes 𝑆 𝑅, ℬ = 𝐷 𝑃𝐵|𝑅||𝑃𝐵

= 𝑃𝐵|𝑅 log𝑃𝐵|𝑅

𝑃𝐵𝑑𝐵

ℬ

Creating a food knowledgebase

Recipe Recipe Step

Recipe Step

Input

Recipe Step

Output

Recipe Step

Property

Ingredient Flavor

Compound

Nutrition

Fact

Cuisine

Dish

Ingredient

Pairing

Ingredient

Type

Odor

Descriptor

Odor

Pleasantness

recipes.wikia.com

wikipedia

USDA nutrient DB

VCF, Atlas of Odor Character Profiles, research papers

Derived from above sources

Mixing it up (variety, combinations)

Ingredient Type Available

Ingredients

Meat

Vegetable

Spice

Fish

…

M1 M2

M3 M4

V1 V2

V3 V4

S1 S2

S3 S4

F1 F2

F3 F4

Recipe Constraints Target Dish

(constrains ingredient

type composition)

Target Cuisine

(constrains ingredients)

Base Ingredient

(constrains ingredients)

S1 S2 S3 S4 S1 S2 S3 S4 X X

…

Re

cip

e 1

M1 M2

V1 V2 V3

S1 S2

…

Re

cip

e 2

M3 M4

V1 V2 V4

S1 S3

Re

cip

e 3

M4

V1 V2 V3

S1 S2 S4

Re

cip

e 1

M1 M2

V1 V2 V3

S1 S2

X

X

Cognitive assessor (novelty, surprise)

Bayesian surprise: novelty can be quantified by considering a prior

probability distribution of existing recipes and the change in that

probability distribution after the new recipe is observed

M set of recipes known to the observer

M ϵ M recipe in this repository

A new recipe being observed

Cognitive assessor – pleasantness (delight)

Chemical Compound

Ingredient

Recipe

DATA

Chemistry: molecular properties

Psychology: human-labeled pleasantness rating

Linear Pleasantness Hypothesis:

If two compounds are mixed together and

smelled, the olfactory pleasantness of the

mixture is approximately a linear combination

of the pleasantness values of the individual

compounds

Olfactory pleasantness is predictable

from chemical compound properties

(topological polar surface area, heavy

atom count, complexity, rotatable bond

count, hydrogen bond acceptor count)

Flavor pairing hypothesis: foods combine well with one another when they share key

flavor compounds

[Y.-Y. Ahn, S. E. Ahnert, J. P. Bagrow, and A.-L. Barabási, “Flavor network and the principles of food pairing,” Scientific Reports, 15 Dec. 2011.]

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Cognitive pairing

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Add it all together!

http://www-935.ibm.com/services/us/gbs/thoughtleadership/cognitivefuture/

Where next?

You can contact Trevor at trevor.davis@uk.ibm.com