Google might be the most intelligent technology we are yet to witness on the internet. It’s smart, fast, and reliable. But, have you ever wondered how Google can understand human language and provide us with relevant search results?
It’s all thanks to a couple of AI models that collaborate to provide us with answers to our queries. To help us better understand how Google can decipher the human language, Google’s Vice President Pandu Nayak expounded further on this topic in an article posted on the company’s blog.
Pandu introduces us to the four AI models that enable Google to understand human language; MUM, BERT, Neural Matching, and RankBrain. All these AI models work hand in hand to match your questions to relevant answers on the web. These AI models were launched on different dates. This shows us that Google constantly innovates new learning technologies to improve user experience.
An Overview of the Four Google AI Models
1. RankBrain
Let’s start with the first AI model that Google developed. If you have been doing online marketing for a while now, you can testify that this search engine isn’t what it was seven years ago. Developed in 2015, RankBrain revolutionized how Google showed search results. This AI model can crawl through content on the internet and give you the most relevant answer.
It may be the oldest AI model, but it still plays a critical role in Google’s performance. RankBrain can understand the words in a search query and relate it to real-life solutions. For example, when you enter the following search query, ‘who is the king of the jungle?’ RankBrain understands that by Jungle, you refer to the wilderness, and by king, you intend to know who rules this environment. As a result of this AI model’s performance, Google will give answers related to lions.
2. Neural Matching
This AI model came later in 2018, and it improved Google’s understanding of human language. Neural Matching enables Google to relate search queries to broader topics and concepts. Instead of just providing an answer to a specific search phrase, Neural Matching digs deeper to identify all aspects surrounding the phrase.
It is this AI model that makes Google a genius. For instance, if you ask a colleague in the finance sector about ‘link building’, they may not make much sense of what this is. But, thanks to Google’s neural matching, it will understand that you are interested in search engine optimization, and the results will touch on tips, how-to, and benefits of link building. In summary, Neural Matching makes sense of any search query that you type on Google.
3. BERT
Bert was developed a year later, and it serves two purposes. The first one is that it obtains relevant information and assists with ranking it. Bert is more intelligent than the other AI models because it deciphers how words in a search query relate to one another. Bert can understand even the most complex languages, which is why it’s tasked with ranking content in terms of relevance.
A good example of how BERT works is when you search for phrases such as ‘can you get medicine for someone pharmacy’. It immediately understands that you are interested in knowing whether it’s possible to collect medicine for another person at a pharmacy. BERT can comprehend search queries even when used in short form.
4. MUM
Developed and launched in 2021, MUM is Google’s latest AI model. It is short for Multitask Unified Model. MUM is an upgrade for BERT. Not only is it capable of understanding language, but it can generate it.
MUM has been trained in more than 75 languages. It is very powerful and can perform several tasks at once. It also has a much better understanding of language and images. Because it’s still in its early development stages, we can expect more from this AI model.
With RankBrain’s ability to relate keywords to real-life concepts. Neural Matching broad understanding of various aspects. BERT’s understanding of search queries when used in varying sequences. And MUM’s comprehension of information in several languages. Google can understand, provide and rank information relevant to your search queries.
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