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UNT professors detail how AI training works Community Impact spoke with four computer science and artificial intel- ligence experts from the University of North Texas to discuss how data Responses have been edited for length, clarity and style. sophisticated things. Fu: I did a quick search on
roughly 0.75 words. How do data centers factor into AI? Why do we need them for AI? Rattani: AI models are very large scale, so they can have up to trillions of parameters which we adjust or optimize by using the training data. The number of data points requires large computing resources, large networking, everything. This is why data centers are coming into play. Chen: I think data centers provide a high-performance GPU [Graphics Processing Unit] like computing resource and accelerators that can specialize in AI computing. We need massive storage to save the data set to train the model. Also, the data center provides reliable
ChatGPT to ask how much data was used to train you, and for the GPT 3 model, it’s used about 400 billion tokens of text, so that’s millions of books. For the new model, like GPT 4 and 5, the number of tokens reaches about 10 trillion tokens. That’s proba- bly 10,000 times larger. What is a token? Feng: You can look at tokens as the smallest unit of measurement, like a word count. For example the word “strawberry” can be split into multiple tokens instead of one token. Maybe “straw” is one token and “berry” is another token. For English tokens, one token is equivalent to
Can you explain in simple terms how large-language AI models like ChatGPT work? Feng: The model learns from test data to recognize patterns. We can put in articles and papers and the language model can learn patterns from it to train. When we query it, it predicts the words to the answer based on the patterns it recognized when we put in the data. Rattani: The [large language mod- els] keep on adapting to new queries whenever users interact. They can learn with text as well as images, audio, all that. They can learn richer context and they can do far more
centers and AI function, and why Denton is attracting the technology. Community Impact spoke with: • Song Fu , a professor of computer science and engineering and the director of the Applied Artificial Intelligence and Data Science Institute • Haihua Chen , a professor of data science • Ajita Rattani , a professor of computer science and engineering • Yunhe Feng , a professor of com- puter science and engineering
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