Reasons Behind AI Development Needing Billions of Money and Huge Hardware Quantities
Businesses that are investing into artificial intelligence (AI) are spending a lot of money to create, teach, and maintain resource-intensive content generators like ChatGPT. These generators, along with the big language models (LLMs) they learn from, need a lot of power. OpenAI’s GPT-4, for instance, uses big sets of data, neural networks, and LLMs that use up a lot of resources.
A big problem in the AI industry is getting enough graphics processing units (GPUs). These are needed for making images, mining cryptocurrencies, and running AI programs. Many companies want GPUs for gaming, cryptocurrencies, and AI, so there aren’t enough affordable GPUs around.
To get more GPUs, companies like Nvidia are having trouble making enough. Some people who like cryptocurrencies are changing their mining machines to use for AI learning. Google uses special units called tensor processing units (TPUs) for this.
Even before the demand went up, GPUs were already expensive. The boss of OpenAI, Sam Altman, said a lot of the company’s costs were from the powerful computers they need to train and use LLMs. The computers needed for training, like GPUs and TPUs, can cost millions of dollars.
AI programs use a lot of energy, which worries people about how much energy they use. Altman said many times that making AI takes a lot of money. So, OpenAI might charge for its popular ChatGPT to help pay for these costs.
The biggest tech companies do best in AI because they have lots of money and keep getting more. Smaller companies have a hard time catching up. OpenAI gets help from Microsoft and uses special supercomputers, which is a big advantage.
Even though AI programs like GPT-4 are more powerful and known now, we don’t really know how they work. They don’t tell us all the details about how they’re made, how big they are, or how they’re trained. This lack of information makes people worry about how much these AIs affect the environment and use up energy.
Even though the AI field is changing fast, there’s still a lot to understand about how it affects the Earth. Spending more money and using energy better are important things to think about to fix these worries and make AI that’s good for the Earth.