Recently, Google's ai learns Bengali itself, without any specific human training, which has garnered a lot of attention.
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Google’s AI Learns Bangali Without Specific Training – How Did It Do That?

Updates on 20th May 2023: As the world becomes increasingly connected, the need for machines to understand different languages is more important than ever before. Machine learning algorithms based on AI show promise in understanding languages without specific training. Recently, Google AI learns Bengali without any specific human training, which has garnered a lot of attention.

Let’s explore how Google AI learns Bengali itself, without human help? is it true?

What is Bengali?

Bangla, also known as Bengali, is a language spoken by over 250 million people worldwide, primarily in Bangladesh and the Indian states of West Bengal, Tripura, and Assam. Bangla is the seventh most spoken language globally, with a rich literary tradition and cultural heritage.

Google’s AI and mBERT Model

The study was conducted by researchers at Google, they used a pre-trained model called mBERT, which stands for Multilingual BERT, to analyze Bangla text. Natural language processing tasks like question answering, text classification, and translation use BERT, a popular machine learning model. mBERT, a version of BERT pre-trained on a large corpus of text from multiple languages, including Bangla, exists.

Recently, Google's ai learns Bengali itself, without any specific human training, which has garnered a lot of attention.

The training of the mBERT model involves masked language modeling to learn how to understand multiple languages simultaneously. The model masks words, predicts them using context, and accurately labels Bangla’s parts of speech, indicating its comprehension of the language’s grammar.

How Did Google AI Learn Bengali?

The researchers conducted a series of experiments to test how well the mBERT model could understand Bangla text. A Bangla dataset tested mBERT’s natural language processing tasks: language identification, part-of-speech tagging, and named entity recognition.

Language identification involves determining the language of a given text. The researchers found that the mBERT model was able to correctly identify Bangla text with high accuracy, indicating that it had learned to recognize the language.

Part-of-speech tagging involves labeling each word in a sentence with its part of speech, such as noun, verb, adjective, etc. The researchers found that the mBERT model was able to accurately label Bangla words with their respective parts of speech, indicating that it had learned the grammatical rules of the language.

Named entity recognition identifies entities like people, organizations, and locations mentioned in a text. The researchers found that the mBERT model was able to accurately identify Bangla-named entities, indicating that it had learned the semantic meaning of the language.

Implications and Future Research

The study indicates that the mBERT model can comprehend Bangla text, even without specific training in the language. The study suggests that pre-trained models like mBERT can excel in natural language processing tasks across different languages. It is crucial to take into account the potential biases and limitations of pre-trained models as they may not always accurately capture the intricacies and diversities of various languages and cultures. BARD uses mBERT to encode user inputs and system responses into a single vector for conversational agents. BARD trains conversational agents via a bi-encoder approach, encoding user input and system response into a single vector using mBERT. The system compares vector representations of user input and system response to generate a conversational agent’s response.

What brings the controversy about Google AI Learns Bangala?

In a recent interview with CBS’ “60 Minutes,” Sundar Pichai, CEO of Google’s parent company Alphabet, discussed the future of AI and its impact on society. Pichai and other Google executives talked about the unexpected skills that some of Google’s AI programs have developed, leading to questions about the potential consequences of advanced AI.

Video: The AI Revolution: Google’s Developers on the Future of artificial intelligence- 60 minutes- CBS

Google Bard, an AI chatbot, learned skills beyond its training, as discussed in Pichai’s interview. After prompting Google Bard in Bengali, the language of Bangladesh, it adapted and learned to translate the entire language.

Margaret Mitchell, a former Google researcher, corrected the statement on Twitter with evidence, stating that Google’s PaLM AI model had already been trained to interpret Bengali. Google’s PaLM model has been trained in Bengali, as indicated on its datasheet, making Bard’s Bengali language skills unsurprising. This raises questions about the accuracy of the information presented by Google executives in the interview.

“PaLM” (short for “Path-Aware Language Model”), which is a different AI model from “mBERT” (Multilingual BERT). Both models are developed by Google and used for natural language processing tasks, but they have different architectures and capabilities.

Aside from this specific example, Pichai discussed the potential for AI to cause job losses among “knowledge workers” such as writers, accountants, architects, and software engineers. Pichai acknowledged that Google’s AI programs have developed unanticipated skills, something engineers cannot fully explain.

Overall, the interview highlights the rapid development of AI and its potential consequences. It is important to balance the potential benefits of AI with responsible development and use while considering its potential drawbacks. Sundar Pichai’s interviews reveal Google’s future AI goals, including unexpected skills learned by AI programs.

Comparison Chart: Google Bard vs. ChatGPT for Bangla Learning

FeatureGoogle BardChatGPT
Language LearningOffers comprehensive language learning tools and resources for Bangla.Provides conversational assistance and language support for Bangla.
Pronunciation SupportProvides pronunciation guidance and audio examples for Bangla words and phrases.Does not offer specific pronunciation support.
Vocabulary ExpansionOffers a wide range of vocabulary exercises, flashcards, and word games to expand Bangla vocabulary.Can generate Bangla text and provide contextual explanations, aiding vocabulary expansion.
Sentence StructureProvides examples and explanations of Bangla sentence structures and grammar rules.Can assist with sentence formation and provide suggestions for correct phrasing in Bangla.
Cultural ContextUtilizes advanced AI algorithms to enhance the language learning experience.Limited information on cultural context and primarily focuses on language assistance.
Interactive PracticeProvides interactive exercises, quizzes, and language drills for practicing Bangla skills.Offers conversational practice and responds to user queries, promoting interactive learning.
AI Language ProficiencyUtilizes advanced AI algorithms to enhance the language learning experience.Relies on AI algorithms for generating responses but may not be specifically tailored for language learning.
Customization OptionsAllows users to set language learning goals, track progress, and customize learning preferences.Does not provide customization options specific to language learning.
User-Friendly InterfaceOffers a user-friendly interface and intuitive design for easy navigation and learning.Provides a chat-based interface that requires textual input for interaction.
Availability and AccessCan be accessed via web browsers or dedicated mobile apps on various devices.Can be accessed online through platforms that offer the ChatGPT model.
CostAvailability and cost may vary depending on specific language learning features and packages.Access to ChatGPT and related platforms may be free or require a subscription fee.


Google’s AI Learns Bangli itself showcases the power of machine learning algorithms. The members’ model’s ability to understand multiple languages simultaneously has significant implications for natural language processing tasks in multilingual settings. Researchers need to conduct more research to assess pre-trained models on larger datasets and identify any biases or limitations. AI and natural language processing advances will enable machines to understand and communicate in more languages in the future.

FAQ: Google’s AI Learns Bangla

Q1: What is Google’s AI?

A1: Google’s AI is a project undertaken by Google to develop an artificial intelligence (AI) system capable of understanding and generating content in the Bengali language, commonly known as Bangla. It aims to enhance language processing capabilities and improve access to information for Bengali speakers.

Q2: How does Google’s AI Learn Bangla?

A2: Google’s AI utilizes advanced machine learning techniques and large datasets of text in Bengali to train its algorithms. Through this training process, the AI system learns the grammar, vocabulary, and semantic patterns of the Bengali language. It can then generate coherent sentences, translate text, answer questions, and perform other language-related tasks.

Q3: What are the benefits of Google’s AI?

A3: Google’s AI brings several benefits to Bengali speakers. It improves machine translation services, enabling more accurate translations between Bengali and other languages. It enhances voice assistants’ ability to understand and respond to queries in Bengali, making them more useful for Bengali-speaking users. Additionally, it aids in content creation, information retrieval, and linguistic analysis in the Bengali language.

Q4: Can Google’s AI help with learning the Bengali language?

A4: Yes, Google’s AI can assist language learners in various ways. It can provide translation support between Bengali and other languages, helping learners understand and communicate in Bengali more effectively. The AI system can also generate sample sentences, offer grammar suggestions, and provide language learning resources to aid learners in their language acquisition journey.

Q5: Is Google’s AI available for public use?

A5: While Google’s AI is primarily a research and development project, its outcomes are integrated into various Google products and services. Users can benefit from the AI system’s language processing capabilities through features like Google Translate, Google Search, and Google Assistant, which continue to improve their support for the Bengali language.

Q6: How accurate is Google’s AI in understanding and generating Bengali content?

A6: Google’s AI strives for high accuracy in its language understanding and generation capabilities. However, the accuracy may vary depending on the complexity of the input, context, and the specific task. Google continuously works on improving the AI system’s performance through ongoing research and development efforts.

Q7: Is Google’s AI only limited to textual content?

A7: No, Google’s AI can process both textual and spoken content in Bengali. It can transcribe spoken words into written text, analyze text for sentiment or topic classification, and generate spoken responses. This multimodal capability enables a more comprehensive understanding and generation of Bengali content.

Q8: How does Google ensure the privacy and security of user data when using AI?

A8: Google follows strict privacy and security protocols to protect user data when utilizing AI. User data is anonymized and processed in accordance with privacy policies and legal regulations. Google employs encryption, access controls, and safeguards to ensure the confidentiality and integrity of user information.

Q9: Can users contribute to improving Google’s AI?

A9: Yes, users can contribute to improving Google’s AI by providing feedback and reporting any issues or inaccuracies they encounter while using Google products and services. User feedback helps Google identify areas for improvement and refine the AI system’s performance in understanding and generating Bengali content.

Q10: Is Google planning to expand its AI language learning projects to other languages?

A10: Yes, Google continues to invest in AI language learning projects for various languages to improve accessibility and empower users worldwide. The aim is to develop AI systems capable of understanding and generating content in multiple languages, fostering cross-cultural communication and information sharing.

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