TLDR:
In a few years, AI models like GPT-4 may exhaust all publicly-available text data on the internet, prompting the need for alternative data sources such as private information. The shortage of quality data could lead to stagnation in AI advancements, but companies are exploring solutions like using synthetic data or private information. Legal and ethical challenges may arise from using private data without permission.
Key Points:
- AI models could consume all internet text data by 2026, leading to a need for alternative data sources.
- Shortage of quality data may cause stagnation in AI advancements, prompting exploration of solutions like synthetic data.
- Companies may face legal and ethical challenges if using private data without permission for AI training.
A new study has warned that AI models, like GPT-4, could deplete all of the internet’s free knowledge by 2026. These models rely on vast amounts of online text data to improve, but projections indicate that publicly-available data may run out within the next decade. To overcome this challenge, tech companies may need to explore alternative data sources, including synthetic data or private information stored on servers.
The scarcity of quality data could result in a slowdown in the field of AI, with models improving at a slower pace as new data becomes scarce. Some companies are already considering using private data to train their AI models, which raises legal and ethical concerns regarding privacy and consent. Additionally, using synthetic data or harvesting private information without permission may lead to legal challenges as content creators seek fair compensation for their work.
Despite the potential challenges posed by a lack of quality data, companies are actively exploring solutions to ensure the continuous advancement of AI technology. By adopting alternative data sources and addressing legal and ethical concerns, AI models may continue to evolve and innovate in the coming years.