BERT stands for Bidirectional Encoder Representations Transformers.
It is an open-source program that any Python lover can train his question-answer system.
Github: https://github.com/google-research/bert
BERT is bidirectional that makes it unique than other algorithms that are usually unidirectional.
But, Alim, please explain with an example of what is a unidirectional and bidirectional approach.
Okay!
In the unidirectional approach, Google evaluates the previous context of a sentence only, not the next context.
The word “Bank” has different meanings: the river bank and the money bank.
When we say, “I accessed the bank account.” In the unidirectional approach, Google judges the word BANK based on the “I accessed” only.
In the bidirectional approach, Google looks at the “account” as well to understand its true relevance.
Still, didn’t get it?
Let’s take another example.
Example
Sentence A: The man went to the store.
Sentence B: He bought a gallon of milk.
Label: IsNextSentence
In this example, BERT knows “the man bought a gallon of milk.” from the previous and the next sentence.
Sentence A: the man went to the store.
Sentence B: penguins are flightless.
Label: NotNextSentence
In this example, Google knows the second sentence is not linked with the first sentence; that is why Google has labeled it, “It is not the next sentence.”
BERT is better than human beings in understanding the content as per Google research.
Human being has an accuracy of 91.221, but BERT achieves 93.160!
What Do I Believe?
BERT is aimed at content. You should write grammatically correct English to make sense of content.
The flow from one sentence to another is essential than ever before to get a featured snippet and overall ranking of your article.
We should wait for a week until the update is fully rolled out.
Before that, I will not make a major hypothesis about the update because I haven’t seen a big change in traffic on my and client sites: one saw a significant improvement in traffic.
SOURCES TO LEARN MORE ABOUT BERT: