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Notes on video lecture:
Search and Basic Indexing
Choose from these words to fill the blanks below:
genomic, business, correcting, intent, learning, computer, hash, find, binary, sensors, party, Googles, Map, Turing, man, intelligent, documents
Turing Test
based on 1950s            game where a person takes type-written answers to questions and tries to determine if it was written by a        or a woman
human tries to determine if text is written by human or                 
a CAPTCHA is an example of a              Test in reverse
examples of successful artificial intelligence
instant translations of hundreds of texts
object recognition of by e.g. Google               
machines recognizing faces e.g. on Facebook
big data
billions of Facebook pages
hundreds of million tweets a day
millions of servers, petabytes of data
old-style business intelligence
databases, clean the data, data warehouse, more database, statistics
new-style business intelligence (Google, Facebook, etc.)
massive parallelism
      -Reduce paradigm
this is the heart of big data technology
relationship between data and intelligence
the difference between data and intelligence is with intelligence, you can predict
applications that use big data to achieve predictive intelligence
online advertising predicting our              and interest
gauging consumer sentiment and predicting behavior
detecting adverse events and predicting their impact
recognizing places and faces
personalize                medicine
medicines actually have different affects on each person
intelligent public services for energy, water
deep analytics
securing ourselves from criminals
big data analytics
fusing social intelligence with                  intelligence
data-driven business models and processes
how to predict the future with artificial intelligence and big data
the purpose of looking is to          stuff
on the web
on one's computer
in one's memories
finding stuff is essential to                        behavior
on the web, finding stuff is about finding                   
we type in words and expect to find documents
if we type in "large bird" we want documents which contain both "large" and "bird" sorted by those on top which have both "large" and "bird"
we do this via indexing
in a              tree, looking up a document takes O(log m)
using a          might be faster
in multiple-term queries, you would also need to sort them
the time it takes is O(r q) if r = number of intermediate results in all


Kryder's Law, n. A theory that states that the density of data storage devices increases by a factor of 1,000 every 10.5 years (doubling every 13 months), a pace faster than Moore's Law, or the doubling in semiconductor chip performance every 18 months.  "Kryder's Law has held for three decades, surely it is good for another decade or two."
Search and Basic Indexing