![]() ![]() This included everything from scientific articles to Wikipedia pages. ![]() To get half a terabyte of useful information, data engineers fed ChatGPT web text databases. Until then, those in data engineering are responsible for spoon-feeding handpicked data to their AI. Perhaps one day AI can vet its own datasets. But the end result would likely be an unrecognizable monster. It would be easy enough to unleash an AI onto the Internet and allow it to consume endless quantities of data. Choosing Good Datasets for AIĮvery data engineer knows well that high-quality data is better than large quantities of data. And there's no better place to source it than from web scraping.įollow along as we explain how you can train your AI model on web data. The key to ChatGPT's success lies in curating good data. These projects came to an early close when engineers "lost control" of their artificial intelligence. The Internet is replete with stories of chatbots gone rogue thanks to troublesome information bases. The question then becomes how to source this training data. And unsurprisingly, it took about 570 GB worth of datasets to train this revolutionary chatbot. ChatGPT is among the latest instances of artificial intelligence to wow the crowds. AI models need a massive glut of data to learn, iterate, and improve. ![]()
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