Billions of searches are conducted every day. Google stands as the unrivaled gatekeeper to a wealth of information. Have you ever wondered how this tech giant deciphers the complexities of human language and consistently returns relevant search results?
The answer lies in a sophisticated interplay of Artificial Intelligence (AI) models, each with its own unique role in making Google Search a linguistic genius.
In this article, we'll unpack the inner workings of these AI models, shedding light on their functions and how they work in harmony to make our online searches more precise than ever.
Google's Pioneering AI Google's journey into the realm of AI-powered search began with RankBrain in 2015.
This AI system plays a pivotal role in organizing search results by ranking them according to relevance.
Imagine it as the conductor of a symphony, harmonizing the intricate relationships between words in a search query and real-world concepts.
For instance, when you search for "the top consumer in a food chain," RankBrain understands that you're seeking information about an "apex predator." This deep learning model continues to be instrumental in today's search landscape.
Neural Matching: Thinking Beyond Keywords
Neural Matching entered the scene in 2018, introducing a new way of understanding queries and web content. Unlike conventional keyword analysis, neural matching comprehends the broader concepts encapsulated in search queries and web pages.
This ability enables Google to cast a wider net when searching its index for content related to a query.
For instance, a query like "insights on how to manage a green" may appear perplexing, but neural matching interprets it as a quest for management advice linked to a color-based personality guide.
BERT: Enhancing Contextual Understanding
BERT (Bidirectional Encoder Representations from Transformers) emerged in 2019, revolutionizing the search experience.
Its primary role is to retrieve relevant content and rank it accurately.
What sets BERT apart is its intricate understanding of word relationships within a sequence. Even tiny prepositions like "for" no longer go unnoticed. For example, when you search for "can you get medicine for someone at a pharmacy," BERT discerns your intent—to determine if you can collect medicine on someone else's behalf—resulting in more contextually relevant search outcomes.
MUM: Google's Multi-Modal Marvel
Google's most recent AI marvel, Multitask Unified Model (MUM), made its debut in 2021. MUM is a thousand times more potent than BERT and boasts a comprehensive understanding of information and world knowledge.
Trained across 75 languages and various tasks, MUM operates across text and images, earning its "multi-modal" designation.
While its full potential is still unfolding, MUM was used to improve searches for COVID-19 vaccine information.
Google's Ever-Evolving Grasp of the Human Language
Google's commitment to understanding human language stands unrivaled. Its AI systems—RankBrain, Neural Matching, BERT, and MUM—collaborate seamlessly to decipher search queries, identify relevant content, and deliver a more precise and satisfying search experience.
As users, we reap the benefits of these groundbreaking technologies every time we seek information or answers on the internet.