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Form Generative AI Product Team to Compete in Chatbot Market

The Meta product group, formed last week by Mark Zuckerberg, brings together dozens of employees from across the company to develop AI-based chatbots and other products using the new LLaMA language model.

Mark Zuckerberg, CEO of Meta Platforms, announced on Monday that the company is creating a new top-level product group focused on generative AI to accelerate their work in the chatbot battle. This AI technology will be used in Meta’s messaging apps WhatsApp and Messenger, as well as Instagram’s visual filters for photos and videos. The goal is to develop AI personas that can help people in various ways. Zuckerberg is excited about the possibilities of this technology and the new things that Meta will build along the way.

Meta, a social media giant, has announced the formation of a new product group that will focus on artificial intelligence and machine learning. The group will be led by Ahmad Al-Dahle, a machine learning and artificial intelligence executive, and will report directly to Meta chief product officer Chris Cox. This move is part of Meta’s effort to integrate AI and machine learning technology into its range of products. The news follows similar test releases from other tech giants such as Microsoft and Google. The new product group will help Meta stay competitive in the AI and machine learning space, and will help the company provide better services to its users.

Mark Zuckerberg, CEO of Meta, recently announced the launch of a large language model called LLaMA, a research tool for building AI-based chatbots and other products. This technology will be available to AI researchers, allowing them to see how the system works, tweak it to their needs and collaborate on related projects. Zuckerberg has also expressed his focus on infusing AI in messaging, the advertising business and its algorithm that decides what content people see on Facebook and Instagram. He is also committed to streamlining the company to ensure that these priorities are executed efficiently.

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