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www.nyas.org | ||
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scorpil.com
In Part One of the "Understanding Generative AI" series, we delved into Tokenization - the process of dividing text into tokens, which serve as the fundamental units of information for neural networks. These tokens are crucial in shaping how AI interprets and processes language. Building upon this foundational knowledge, we are now ready to explore Neural Networks - the cornerstone technology underpinning all Artificial Intelligence research. A Short Look into the History Neural Networks, as a technology, have their roots in the 1940s and 1950s. |
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ischoolonline.berkeley.edu
Whether you know it or not, you've probably been taking advantage of the benefits of machine learning for years. Most of us would find it hard to go a full day without using at least one app or web service driven by machine learning. But what is machine learning? |
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bdtechtalks.com
The transformer model has become one of the main highlights of advances in deep learning and deep neural networks. |
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www.danstroot.com
Last week OpenAI published a report detailing why AI models hallucinate. The reason that AI models hallucinate is not because the model is "broken" or the math behind the models is wrong. Instead, the reasearchers claim that hallucinations are a predictable, systemic outcome of how we train and, more importantly, how we test these systems. In short, the models have been taught that it's better to guess than to admit they don't know the answer. |
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