Elon Musk to Launch ChatGPT Competitor for Tucker Carlson

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Elon Musk is diving into the world of artificial intelligence chatbots by announcing he plans to create his own chatbot, TruthGPT. This chatbot intends to challenge the hugely popular chatbot software ChatGPT, created by OpenAI. During his interview with Tucker Carlson, Musk revealed that not only did he help jumpstart development of ChatGPT, but that he thought up the name and concept himself and held numerous dinners around the Bay Area with top figures in AI. He also remarked that he aimed to create OpenAI as a sort of counterweight to Google but that the company is now closed-source and connected with Microsoft.

Musk noted that training an AI with deceptive intent could lead to a dystopia, so he is initiating the creation of TruthGPT, an AI that is attempting to understand the nature of the universe, while not taught to lie, to avert the possibility of civilizational destruction. The Tesla CEO has even started pushing to recruit AI researchers from Google to begin working on the rival. To further demonstrate his dedication to the project, he has even incorporated a company, named X.AI Corp, in Nevada.

OpenAI is a technology company based in San Francisco that focuses on artificial intelligence research and development. Founded in 2015, the company is backed by a host of world-renowned technology investors and business professionals. Elon Musk was a high-profile early funder and co-chair of OpenAI whose primary aim was to serve as a counterweight to Google. He helped to recruit Ilya Sutskever, who is now an OpenAI co-founder and is attributed as “fundamental to the success of OpenAI.”

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Ilya Sutskever has a strong background in the field of AI. He received a doctorate from the University of Toronto and held a research leadership position in Google Brain. He was named a research professor at Stanford University before moving to OpenAI, where he is the Chief Scientific Officer. Sutskever is renowned for developing technologies such as Generative Adversarial Networks, semi-supervised learning, deep reinforcement learning and more. His research has contributed significantly to the advancement of AI technologies and he has also achieved a higher level of recognition and acclaim in the field of AI.

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