As the capabilities of Generative AI models like Chat GPT, DALL-E continues to grow, there is an increasing temptation to use their AI-generated outputs as training data for new AI systems. However, recent research has shown the dangerous effects of doing this, leading to a phenomenon called “model collapse.” In a study published in July 2023, scientists at Rice and Stanford University concluded that training AI models exclusively on the outputs of generative AI is not a good idea. They titled their report: “Self-consuming generative models go MAD.”#Binance #Aİ #tranding #OPN

The possibility of #AI models tainting themselves may be a bit analogous to a certain 20th-century dilemma. After the first atomic bombs were detonated at World War II’s end, decades of nuclear testing spiced Earth’s atmosphere with a dash of radioactive fallout. When that air entered newly-made steel, it brought elevated radiation with it. For particularly radiation-sensitive steel applications, such as Geiger counter consoles, that fallout poses an obvious problem: it won’t do for a Geiger counter to flag itself. Thus, a rush began for a dwindling supply of low-radiation metal. Scavengers scoured old shipwrecks to extract scraps of prewar steel. Now some insiders believe a similar cycle is set to repeat in generative AI—with #training data instead of steel.#Binance #OPN

In the world of artificial intelligence (AI) and large language models (LLMs), finding appropriate training data is the core requirement for building generative solutions. As the capabilities of Generative AI models like Chat GPT, DALL-E continues to grow, there is an increasing temptation to use their AI-generated outputs as training data for new AI systems. However, recent research has shown the dangerous effects of doing this, leading to a phenomenon called “model collapse.” In a study published in July 2023, scientists at Rice and Stanford University concluded that training AI models exclusively on the outputs of generative AI is not a good idea. They titled their report: “Self-consuming generative models go MAD.”#Binance #Aİ #tranding #OPN

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