Artificial intelligence (AI) not only delivers impressive performance but also demands significant energy. The more complex the tasks it undertakes, the greater the energy consumption. Scientists Víctor López-Pastor and Florian Marquardt from the Max Planck Institute for the Science of Light in Erlangen, Germany, have developed a method for more efficient AI training. Their method utilizes physical processes, diverging from traditional digital artificial neural networks.
Open AI, the company responsible for the development of GPT-3, the technology powering ChatGPT, has not disclosed the amount of energy needed for the training of this advanced and knowledgeable AI Chatbot.
According to the German statistics company Statista, this would require 1,000 megawatt hours – about as much as 200 German households with three or more people consume annually. While this energy expenditure has allowed GPT-3 to learn whether the word ‘deep’ is more likely to be followed by the word ‘sea’ or ‘learning’ in its data sets, by all accounts it has not understood the underlying meaning of such phrases.
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