BERT: Bidirectional Encoder Representations from Transformers

BERT stands for Bidirectional Encoder Representations from Transformers. 🧠

It’s Google’s AI-based natural language processing (NLP) model to help computers understand language more like humans.

BERT doesn’t replace RankBrain (Google’s first AI for search); it works alongside it to better understand search queries. 🤝

Discourse Integration

BERT uses context from surrounding sentences to understand the meaning of words and phrases.

Example:

Sentences:
"The man went to the store."
"He bought a gallon of milk."

Understanding: BERT recognizes that "He" refers to "The man", integrating discourse to comprehend the narrative flow.

🔍 How Does BERT Work?

BERT focuses on the nuances of language to better interpret:

• Relationships between words in a sentence.
• Context to understand the true meaning of queries.

Before vs After BERT

Query: "2019 Brazil traveler to USA need a visa."

• Before BERT: Google might return results for U.S. citizens traveling to Brazil. ❌
• With BERT: Google recognizes that the word “to” is critical and gives the correct result about Brazilians traveling to the USA. ✅

Standing at Work

Query: "Do estheticians stand a lot at work?"

• Before BERT: Matched “stand-alone” (completely unrelated). ❌
• With BERT: Understands “stand” refers to physical demands of the job. ✅

Medicine Query

Query: "Can you get medicine for someone pharmacy?"

• Before BERT: Misinterpreted the intent. ❌
• With BERT: Provides relevant results about getting medicine for someone. ✅

📈 Can You Optimize for BERT?

Nope! There’s no direct way to optimize for BERT or RankBrain.

Instead, focus on writing helpful, user-friendly content that answers real questions. 📝

Google’s AI systems aim to better understand natural language and match queries to the most relevant results.