In recent years, large language models (LLMs) have made significant progress in the field of natural language processing (NLP), widely applicable in scenarios such as text generation, summarization, and question answering. However, these models rely on a token-level processing method that predicts word by word, which struggles with contextual understanding and often leads to inconsistent outputs. Moreover, when scaling LLMs to multilingual and multimodal applications, the computational costs and data requirements tend to be relatively high. To address these issues, Meta AI has proposed a novel approach.

Recently, Meta announced on its WhatsApp channel that its AI chatbot Meta AI has officially launched in six new countries, including Brazil, the UK, the Philippines, Bolivia, Guatemala, and Paraguay. This marks a further internationalization of Meta AI, aiming to provide a smarter interaction experience for users worldwide. Meta also revealed that, in addition to these six countries, the company plans to gradually roll out Meta AI to more countries in the future, particularly in the Middle East. With this expansion,

Recently, Meta began testing a new feature that will insert AI-generated content into Facebook and Instagram feeds based on users' interests and current trends. Meta states that these AI-generated images will be tailored to each user's preferences. Users can click on suggested prompts to guide the content in new directions. Interestingly, users can simply swipe the screen to have AI create more personalized content in real-time. As Meta pushes forward...

Recently, a wave of 'Goodbye, Meta AI' has swept across social media platforms. Many users, including high-profile figures such as Tom Brady and musician Cat Power, have taken to Instagram to publish statements aimed at preventing Meta from using their data to train AI models. This phenomenon reflects users' deep concerns about data privacy and the application of AI technology, posing new challenges for tech giants in balancing technological innovation with user rights. Although these statements have no legal binding force, they highlight the growing sentiment among users.

At the recently held Meta Connect 2024 conference, Meta's founder and CEO Zuckerberg excitedly announced that Meta AI's monthly active users have nearly reached 500 million and is expected to become the most used AI assistant globally. During his speech, Zuckerberg mentioned, 'We are currently close to 500 million monthly active users and have yet to launch in some major markets, such as the European market.' This news undoubtedly fills people with anticipation for the future of Meta AI.

Meta AI has become the most used platform in India, receiving billions of queries just months after its launch, particularly excelling on WhatsApp. After overcoming cultural challenges and making algorithm adjustments, the AI now supports multiple languages and is available in 22 countries. The training computational requirements for the new model Llama4 are ten times that of its predecessor. Meanwhile, the user base for the Threads social app is nearing 200 million, and Facebook's usage among young adults in the U.S. is showing positive trends.

Meta's success with AI products in the Indian market is largely due to the widespread use of WhatsApp, which boasts 500 million users in India. Since their launch, AI products have processed billions of queries, demonstrating exceptional user retention and engagement. Despite challenges in adapting to local cultures, addressing sensitive religious topics, and mitigating image generation biases, Meta has adjusted algorithms to ensure fairness and supports multiple languages, including Hindi. Furthermore, Meta has announced it is developing the next generation of computing capabilities that are 10 times more powerful than Llama3.

Meta's AI assistant falsely reported a nonexistent assassination attempt on former President Trump, leading to widespread discussion and regret from Meta executives. The misleading response was caused by programming limitations initially set to avoid addressing questions about Trump's assassination, but after these restrictions were removed, the AI still provided incorrect information in some instances. This phenomenon, known as 'hallucination,' is a common challenge faced by generative artificial intelligence. Similar issues have also plagued Google, whose search autocomplete feature was criticized for censoring Trump-related queries.

Meta AI's latest project, Llama 3, focuses on training with synthetic data rather than human-written answers to optimize model performance in areas such as code generation, mathematical reasoning, multilingual processing, and long text handling. Llama 3 generates synthetic data for code generation through three methods, employs research methods for mathematical reasoning, and collects high-quality human annotations for multilingual pre-training. Furthermore, Llama 3's training is enhanced using Brave Search, Wolfram Alpha, and Python interpreter.

In the realm of artificial intelligence, the competition between open-source and closed-source models has never ceased. The recent release of Meta AI's Llama 3.1 model, however, seems to have drawn a watershed line in this contest. This is not merely the launch of a new model; it is a sign of the maturation of open-source AI, heralding the arrival of a new era.Llama 3.1, developed by Meta AI's team, is a new generation of large-scale language models. In over 150 benchmark tests, its 405B paramet