Recently, the AI research company Epoch AI released an interactive simulator designed to simulate the computational power required to train large language models. Through this simulator, researchers found that while a 2012 outdated graphics card (like the GTX580) could be used to train GPT-4, the cost would be ten times that of modern hardware today. Epoch AI's research indicates that the number of floating-point operations (FLOP) required to train GPT-4 is between 1e25 and 1e26.

In the vast universe of artificial intelligence, mathematics has long been considered the last bastion of machine intelligence. Now, a new benchmarking test named FrontierMath has emerged, pushing AI's mathematical reasoning capabilities to unprecedented limits. Epoch AI has collaborated with over 60 top minds in mathematics to create this challenge, which can be described as the 'Olympics of Mathematics' for AI. This is not just a technology test; it is the ultimate interrogation of artificial intelligence's mathematical wisdom. Imagine a laboratory filled with the world's top mathematicians, meticulously designing...

The Economist article highlights the 'data wall' challenge faced by AI companies due to the depletion of high-quality internet data, predicting that by 2028, all quality text data will be exhausted, hindering machine learning progress. Professor Stuart Russell from UC Berkeley warned that AI like ChatGPT could deplete textual content in the universe. However, Stanford's Professor Fei-Fei Li asserts that there is still a wealth of diverse data ava....