Just received early access to IBM's Chef Watson Beta this past week. I have been testing, not for recipe development, but with an eye to how it's structure could be adapted to other advisory systems. Also, how it really differs from other search style systems. How does, it adapt, learn, and support creativity? Still trying to understand those dynamics. Also, how this form of expert system is different, and makes it more likely to be successful than those of the 90s. Click the Chef Watson tag for more I have written and will write about this topic.
IBM writes about how it is different:
" ... In contrast to a search engine that simply sifts through existing data to serve up a list of already published recipes, Chef Watson is not programmed to come up with a defined answer to a defined question - it understands, learns, and considers not just the data behind recipes and flavor compounds, but also human perception to design highly creative recipe ideas.
Using the app, users can create novel recipes by selecting ingredients, dish type and dish styles, as well as any ingredients to exclude in the final recipe. Once the user has entered in their choices, the app will generate a list of never before seen recipe suggestions. .... "
Subscribe to:
Post Comments (Atom)
No comments:
Post a Comment