Google has used word frequency, word distance, and world knowledge based on co-occurrences to connect the many relations between words to serve up answers to search queries. But now, due to the recent breakthroughs in language translation and image recognition, Google has turned to powerful neural networks that have the ability to connect the best answers to the millions of search queries Google receives daily.

1. RANK BRAIN
By. Jeff Pickle
Digital Marketing Specialist

2. GOOGLE’S ARTIFICIAL INTELLIGENCE

3. RANK BRAIN EXPLAINED
 Google has used word frequency, word distance, and world
knowledge based on co-occurrences to connect the many
relations between words to serve up answers to search
queries.
 But now, due to the recent breakthroughs in language
translation and image recognition, Google has turned to
powerful neural networks that have the ability to connect
the best answers to the millions of search queries Google
receives daily.

4. GOOGLE’S NEURAL NETWORK
 Rank Brain:
● Is the name of the Google neural
network that scans content and is
able to understand the relationships
between words and phrases on the
web.
 Google’s neural network:
Larry Page stated ;
● “The ultimate search engine will
understand everything in the
world.”
● Google intends to carry this plan
out using computer science
algorithms and their vast database
of human knowledge.

5. WHY IS THIS BETTER THAN PREVIOUS METHODS?

6. HOW IS IT BETTER?
 RankBrain is a better
method because it is a
deep learning self-
improving system.
 It trains itself on pages
within the Google index
 It looks for relationships
between the search queries
and content contained
within the Google index.

7. HOW DOES IT DO THIS?

8. INNER WORKINGS OF RANKBRAIN
 RankBrain works because
of Neural Networks
 These networks are good
at conducting reading
comprehension based on
examples and detecting
patterns
 Thanks to Google’s vast
database of website
documents it is able to
provide a large-scale level
of training sets.

9. INNER WORKINGS OF RANKBRAIN

10. HOW DOES GOOGLE CONDUCT TRAINING?
 Google changes key phrases or words into mathematical
entities called vectors which act as signals.
 RankBrain then runs an evaluation similar to the cloze test.
● Cloze test: is a reading comprehension activity where words are emitted from a
passage and then filled back in.

11. CLOZE TEST
 With a cloze test, there
may be many possible
answers,
● But on-going training from a vast
data set allows for a better
understanding of the linguistic
relationships of these entities.

12. HERE’S AN EXAMPLE:
 The movie broke all
(entity1) over the
weekend.
 Hollywood’s biggest stars
were out on the red carpet
at the (entity2) premiere.
 After deciphering all of the
intricate patterns of the
vectors, RankBrain can
deliver an answer to a
query such as “Which
movie had the biggest
opening at the box office?”
 By using vector signals
from entities that point to
the search result entity
receiving the most
attention.

13. IN CONCLUSION
 It does this without any specific coding, without rules, or
semantic markup.
 Even for queries that may be vague in nature, the neural
network is able to outperform even humans.
 With RankBrain, meaning is inferred from use.
 As training and comprehension improves, it can focus on
the best content that it believes will answer a search query.
 As a result, RankBrain can understand search queries never
seen before.