3) reinvention - conversation between users and team
- treat everything as a prototype to be iterated upon
- two ways of working:
1) split into teams aka "work squads", "work-streams"
2) split into phases aka "sprints"
"observe, reflect, make"
keys of ibm design thinking - ANSWERS1) hills
- align as teams
2) playbacks
- align across time
3) sponsor users
- align with user's reality
, - bringing on someone who knows more onto the team
corpus of knowledge - ANSWERS- loading the relevant body of literature into Watson
curating the content - ANSWERS- human intervention that discards anything that is out of date, poorly
regarded, or not important to the domain
ingestion - ANSWERS- data is preprocessed by Watson, building indices and other metadata that make
working with that content more efficient
- may create knowledge graph to answer more precise questions
machine learning - ANSWERSthe extraction of knowledge from data based on algorithms created from
training data
- training data aka question/answer pairs
- teaches linguistic patterns of meaning
Watson - ANSWERS- basically is a cognitive system that can be trained with large amounts of information
and gain information from it
- Watson is constantly adapting to shifts in knowledge
- Watson can respond to complex questions and come up w/ answers backed by evidence
how Watson builds and enhances expertise - ANSWERS- after identifying parts of speech in a question, it
generates hypothesis. then looks for evidence to reject/support. scores each passage based on statistical
modeling, aka weighted evidence scores
- basically: runs analytics on a body of data to gain insights which Watson can turn into human
inspiration
Watson and Under Armor - ANSWERS- working with wearable tech manufacturers (i.e. Under Armor) to
integrate Watson's machine learning technology with real world data to develop cognitive apps that can
act as health consultants and fitness trainers (personalized, real-time advice)
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