Visualising AI spending: How does it compare with history's mega projects? World leaders and tech executives are convening in New Delhi for the India-AI Impact Summit 2026, focusing on the role of artificial intelligence in governance, job disruption and global collaboration. However, behind these discussions lies the financial reality. Over the past decade, AI has drawn one of the largest waves of private investment in modern history, totalling trillions of dollars. According to Gartner, a United States-based business and technology insights company, worldwide spending on AI is forecast to total $2.5 trillion in 2026, a 44 percent increase over 2025.

Moreover, the model tends to generalize well to unseen tasks that did not appear in the training data.

In a standard view of the reinforcement learning problem, an agent's goal is to efficiently identify a policy that maximizes long-term reward.

Most reinforcement learning (RL) algorithms hinge on the Markovian assumption, i.e. that the underlying system transitions and rewards are Markovian in some natural notion of (observable)