AI models trained by Big Tech firms such as OpenAI, Meta, and Google heavily rely on online data for their learning. However, the rapid pace at which AI models learn poses a challenge: the depletion of available data by 2026. To ensure continuous learning, Big Tech companies are exploring innovative solutions. Stay informed about the latest market, tech, and business news by signing up for our newsletter. Preview the content before signing up and access personalized topics on the go with our mobile app. Simply provide your email address to get started. By clicking "Sign Up, " you agree to our Terms of Service and Privacy Policy.

You can unsubscribe at any time. Advertisement For AI, quantity matters. The more data AI systems are exposed to during training, the more powerful their capabilities become. Yet, as the competition in AI intensifies, companies like Meta, Google, and OpenAI are confronted with an imminent shortage of data to train their models with. Leading AI systems have historically relied on vast reserves of online data. However, according to Epoch, an AI research institute, the availability of high-quality data could be exhausted by 2026. In response, major tech players are actively exploring alternative data sources to ensure the continuous learning of their AI systems. Let's take a closer look at some of the imaginative options being considered by these companies.