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Product Evolution: Computer-aided Recombinant Design by Customer-driven Natural Selection Kamal Malek Noubar Afeyan MIT Media Lab / The Center For Bits.

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Presentation on theme: "Product Evolution: Computer-aided Recombinant Design by Customer-driven Natural Selection Kamal Malek Noubar Afeyan MIT Media Lab / The Center For Bits."— Presentation transcript:

1 Product Evolution: Computer-aided Recombinant Design by Customer-driven Natural Selection Kamal Malek Noubar Afeyan MIT Media Lab / The Center For Bits and Atoms Meeting on Emergent Engineering October 16, 2002

2 Confidential – Do not Duplicate Evolving New Products Step 1 Sequence the Product Genome “Featurize “/ code the product as a set of genes Step 2 Create Recombinant Designs and Expose them to “Natural Selection” Allow customers to interact and choose over the web Step 3 Evolve the “Fittest” Customers/ developers select, refine to produce optimal designs

3 Confidential – Do not Duplicate

4

5 So What’s the IDEA? IDEA: Interactive Design by Evolutionary Algorithms (patents pending) Featurize design into genes and define alleles Consumer votes through web on relative appeal of recombinant designs Preferences extracted through multiple generations Collective action – segmentation – preference extraction Results: Designs, Insights, Affinity, Innovation

6 Confidential – Do not Duplicate IDEA: Interactive Design by Evolutionary Algorithms A set of design direction candidates and a description of the underlying design intent Featurize candidates extracting significant design features and attributes, establishing an allowable range of variation, and identifying design constraints This “featurization” is encoded into the design genotype in a way that enables new design candidates to be generated automatically within the vast design universe defined around the stated design intent Recombinant Design

7 Confidential – Do not Duplicate Evolutionary Algorithms Evolve the “Fittest” Designs Initial Design Population Evolutionary Algorithm Fitness Assessment Fitness Weighted Breeding Mutations More Fit Population

8 Confidential – Do not Duplicate 10 Features of 10 Options Potential Design Population: 10 Billion Designs Discovery of preferred product designs and market segments Consumer Population 5,000 Heterogeneous Users

9 Confidential – Do not Duplicate Examples PACKAGING CONCEPT TESTING PROMOTIONAL DESIGN PRINT MEDIA PRODUCTS

10 Confidential – Do not Duplicate Model Logo Background Perfume Bottle Ad Layout

11 Confidential – Do not Duplicate Crossover

12 Confidential – Do not Duplicate Mutation

13 Confidential – Do not Duplicate 1,000+ Participants Explored A Design Space Rendered In Real-Time Potential Design Universe: Over 340,000+ Possible Advertisements!

14 Confidential – Do not Duplicate 1 2 5 4 3 1,000+ Participants Converged on 5 Major Design Themes from a Design Universe of 340,000+ 100%

15 Confidential – Do not Duplicate Summary First steps toward evolving products through computation, customer selection and web-based collectivism Insights into segmentation Enabling to designers, market researchers as well as product management


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