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Hãy viết đoạn tóm tắt về nội dung bằng tiếng việt kích thích người mua: What is the BERT language model and how does it work?

BERT is an AI language model Google developed before Bard. It serves a different purpose and was operational years before OpenAI launched ChatGPT. Google is a leader in artificial intelligence, building AI into Android, Nest smart speakers, and more. Every time you access Google Assistant, that’s an AI answering.

What does BERT stand for?

BERT stands for Bidirectional Encoder Representations from Transformers. The full name isn’t very helpful unless you’re familiar with AI terminology. The easiest way to explain it is to break it down one term at a time.

• Bidirectional means the process works in two directions. When scanning a sentence, BERT looks for word associations to the left and the right. While we read left to right, we understand that related words can exist on either side. BERT knows that also.
• An encoder is a way of encapsulating information in a compact and useful way. BERT encodes data in a way that makes sense for its unique purposes.
• BERT uses an internal representation of language to simplify and speed up processing. Google Translate uses a similar process when translating between more than a hundred natural languages. The AI creates an internal language that facilitates this process.
• Transformers are a critically important AI concept. It’s a neural network consisting of two layers. Attention layers identify what to focus on by assigning weights to the most relevant piece of data. Feed-forward layers pass data ahead to learn complex patterns.

How is BERT different from Bard?

Google has used AI for many years, but BERT was one of the first language models released as open source, following OpenAI’s GPT-1. OpenAI’s Generative Pre-trained Transformer 1 used Google’s 2017 AI transformer concept. BERT doesn’t accept user input. It works behind the scenes to improve Google Search results.

Bard is Google’s latest AI, a chatbot that responds to questions and follows user commands. It’s a large language model similar to OpenAI’s GPT-4 or Microsoft’s Bing. Google launched Bard in February 2023. Unlike BERT, Bard is not an open source project. If you want to learn more about Google Bard and how it works, we have an article that explains what Bard can do.

How was BERT trained?

Google trained BERT on Wikipedia articles and Toronto BookCorpus, a collection of free online books. This type of data is known as unlabeled text, and BERT uses unsupervised learning. The AI sees the text in a raw form without human input or hints about the meaning or structure. Google fine-tuned the model for natural language processing (NLP), such as answering questions, understanding sentiment, and recognizing people and organizations.

When Google released BERT in 2018, it surpassed previous models by a large margin. Google gave BERT a significant update in October 2019 and began using it to improve search results.

How does Google use BERT?

Google now uses BERT running on Google Cloud TPUs to improve Google Search’s ability to understand your query and deliver the most relevant search results. Google Search can understand long, conversational questions that contain prepositions like “for” and “to,” thanks to BERT’s bidirectional understanding that considers the influence of surrounding words.

Google Search collects and indexes data from billions of diverse websites. Understanding language, context, and the subject is critical to finding relevant listings and surfacing the most important details. Google gave an excellent example in its blog post about integrating BERT into search.

Source: Google

In a search for “2019 brazil traveler to usa need a visa,” BERT recognizes the preposition “to” suggests the results should show listings about a Brazilian getting a visa to visit the U.S. Previous search results incorrectly show information for a U.S. citizen getting a visa to go to Brazil. Now, Google Search understands the whole query rather than simply identifying keyword matches.

Source: Google

Another example, “do estheticians stand a lot at work,” shows awareness of the context of keywords. Previously, Google Search matched the term “stand-alone,” but BERT correctly recognizes the question is about estheticians standing on their feet while at work. Google ends that blog post by acknowledging that “Search is not a solved problem.”

Which AI is next for Google Search?

Google’s Shopping Graph, introduced in 2020, uses AI to improve product searches. In 2021, Google introduced the Multitask Unified Model (MUM), describing it as 1,000 times more powerful than BERT. Multisearch arrived in 2022, letting you refine an image search with text keywords.

The latest and biggest news about Google AI is Bard, a chatbot you can access at bard.google.com. However, Bard’s results might not be accurate, so you still need Google Search. To learn more about chatbots, check out our guide to large language models. This year, Google also brought generative AI to search with its new AI-powered Search experience (SGE). You might see a Generative AI panel at the top of search results featuring a text overview, images, and video.

Since Google’s AI advances live in the cloud, you can access this powerful technology with an Android phone, iPhone, computer, or a nice Chromebook. However, BERT is still in use and continues to serve an important role in Google Search.

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