Zuckerberg’s Meta AI Chatbot: The Solution to ChatGPT in 13 Words or Less


Meta, formerly known as Facebook, has introduced a series of celebrity-inspired chatbots on its platforms such as Facebook Messenger, Instagram, and WhatsApp. These chatbots are based on famous figures like Paris Hilton, Snoop Dogg, and Mr. Beast. Users can interact with them through text-based conversations. The purpose of these chatbots is to provide entertainment and engage users in different ways, such as solving mysteries or playing a role-playing game. Meta also plans to release the tools used to create these chatbots for users and businesses to develop their own versions in the future.

One of the key aspects that sets Meta apart from its competitors is its approach to building AI products. While companies like Google and OpenAI keep their latest AI models proprietary, Meta has been open-sourcing its machine learning models. This includes the release of the Llama model, which has been downloaded 30 million times and has led to the creation of approximately 7,000 derivatives. Meta believes that allowing outsiders to adapt and use its open source AI code can provide valuable insights for the company’s own apps and services. This strategy shows how open-sourcing AI models can enable big companies to innovate at a faster pace.

However, Meta’s open source AI strategy has received some criticism. Concerns have been raised about the detailed versions of the Llama model. Some argue that the way Meta has released these versions may be in violation of an AI risk-management framework from the US National Institute of Standards and Technology. As a result, a protest has been organized outside Meta’s offices in San Francisco to call for the company to stop distributing the most detailed versions of the Llama model.

This latest launch of Meta AI is not the company’s first venture into the AI assistant space. In 2015, it introduced a virtual assistant named M to compete with the likes of Alexa and Google Assistant. However, M relied heavily on human workers to provide responses, with only a small portion coming from algorithms. The project was eventually discontinued in 2018.

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