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Top technology companies, including Microsoft, Google, and Meta, are turning to synthetic data to obtain the large amounts of data needed to train their artificial intelligence (AI) models. Synthetic data, also known as fake data, is created by AI systems and can be used to train future versions of those same systems. This approach eliminates the need for licensed content and reduces legal, ethical, and privacy concerns. However, experts raise concerns about the risks associated with synthetic data, such as model collapse and the amplification of biases and toxicities. Despite the advantages, human intelligence is still crucial in creating and refining artificial datasets. Additionally, a mysterious chatbot called gpt2-chatbot has appeared, exhibiting performance similar to industry leader OpenAI's GPT-4. The developer's identity remains unknown.
By Dr. Tony Hoang4.6
99 ratings
Top technology companies, including Microsoft, Google, and Meta, are turning to synthetic data to obtain the large amounts of data needed to train their artificial intelligence (AI) models. Synthetic data, also known as fake data, is created by AI systems and can be used to train future versions of those same systems. This approach eliminates the need for licensed content and reduces legal, ethical, and privacy concerns. However, experts raise concerns about the risks associated with synthetic data, such as model collapse and the amplification of biases and toxicities. Despite the advantages, human intelligence is still crucial in creating and refining artificial datasets. Additionally, a mysterious chatbot called gpt2-chatbot has appeared, exhibiting performance similar to industry leader OpenAI's GPT-4. The developer's identity remains unknown.

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