In the world of artificial intelligence, one term that has been making waves is “BERT.” Developed by Google, this language model predates the likes of Google Bard and OpenAI’s ChatGPT, and it plays a unique role in the AI landscape. Google has long been at the forefront of AI integration, with AI-driven features permeating into Android, Nest smart speakers, and various other products. When you interact with Google Assistant, you’re engaging with AI technology.
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But what exactly is BERT, and what sets it apart? Let’s dive into the world of BERT, understand its inner workings, and distinguish it from Google Bard.
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Decoding BERT: Unveiling the Acronym BERT stands for Bidirectional Encoder Representations from Transformers. While the full name may seem daunting, breaking it down sheds light on its functionality:
- Bidirectional: BERT’s uniqueness lies in its bidirectional approach. Instead of focusing solely on left-to-right word associations (as typical language models do), BERT scans text in both directions. It comprehends that related words can exist on either side, mirroring the way humans understand language.
- Encoder: BERT employs an encoder to encapsulate information efficiently. This encoding method aligns with BERT’s distinct purposes.
- Transformers: This term is pivotal in the realm of AI. Transformers encompass a neural network with two layers: attention layers and feed-forward layers. Attention layers assign weights to the most relevant data, guiding the focus, while feed-forward layers facilitate the learning of complex patterns.
BERT vs. Bard: Setting the Record Straight Google has a storied history in AI, and BERT was one of its initial forays into language models that were released as open source, following the advent of OpenAI’s GPT-1. BERT, however, operates behind the scenes, optimizing Google Search results, and doesn’t accept direct user input.
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On the other hand, Google Bard, introduced in February 2023, is a full-fledged chatbot that interacts with users, responding to questions and commands. Unlike BERT, Bard is not an open source project and operates as a closed system.
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The Training of BERT: Behind the Scenes Google trained BERT using a dataset comprising Wikipedia articles and the Toronto BookCorpus, consisting of free online books. This data falls under the category of unlabeled text, and BERT learned through unsupervised learning. It processed raw text without human guidance, understanding nuances, meanings, and structures on its own. Google fine-tuned BERT for natural language processing tasks, such as question-answering, sentiment analysis, and entity recognition.
BERT’s Impact on Google Search Google now deploys BERT, powered by Google Cloud TPUs, to enhance the understanding of user queries in Google Search. BERT’s bidirectional comprehension helps decipher long, conversational questions that include prepositions like “for” and “to.” It considers the influence of surrounding words, ensuring more accurate and contextually relevant search results.
For instance, if you input a query like “2019 Brazil traveler to USA need a visa,” BERT recognizes the importance of the preposition “to” and tailors the results to reflect information about a Brazilian traveler requiring a visa for the USA. Previous search results might have erroneously shown details related to a U.S. citizen seeking a visa for Brazil. BERT’s bidirectional understanding significantly refines the search process.
The Road Ahead: Google’s AI Evolution Google’s AI journey doesn’t stop with BERT. The company introduced the Multitask Unified Model (MUM), claimed to be 1,000 times more potent than BERT, in 2021. Multisearch arrived in 2022, allowing users to enhance image searches with text keywords.
The recent introduction of Bard, a chatbot, and the AI-powered Search experience (SGE) mark the latest advancements in Google’s AI offerings. Generative AI panels at the top of search results now provide text summaries, images, and videos, enhancing the search experience.
Google’s AI innovations are accessible across a range of devices, including Android phones, iPhones, computers, and Chromebooks, thanks to its cloud-based infrastructure. While new AI models emerge, BERT remains a crucial component of Google Search, ensuring that the quest for delivering precise and context-aware search results continues.