In the future, the likelihood of a computer running a large GPT model such as GPT-4 or its successor depends on several key factors:
1.Technological advancements: Computing power and efficiency have increased over time, especially in processor technology such as GPUs and dedicated AI chips. If these technologies continue to evolve at the current rate, future computers may have enough processing power to run large models locally.
2.Model optimization: A key direction of AI research is to improve the efficiency of models and compression techniques, which may allow larger models to run on smaller, more power-efficient hardware.
3.Advances in cloud computing and edge computing: Despite the possibility of running large models locally, the development of cloud computing and edge computing technologies may still be a more practical and cost-effective solution. Cloud services allow users to remotely access powerful computing resources without having to have high-performance hardware on-premises.
4.Cost factor: The cost of a high-performance computer is an important factor. Even if technically possible, the high cost may make it difficult for the average user to afford a device to run such a large model at home.
In conclusion, while the future may technically allow local computers to run GPT large models, cloud computing may still be a more practical and economical option, especially for the average user and small business. As technology evolves, we may see more model optimization and efficient computing solutions that make it possible to run these advanced models in different environments.