The challenge of real-time AI: How to drive down latency and cost

The challenge of real-time AI is significant due to the computational load and cost involved with large language models (LLMs). Latency, cost, and real-time access are interconnected, and reducing latency also reduces costs. The key challenges of real-time AI include computation, where LLMs require enormous computations, making them expensive, and actual applications requiring complex output. Cost is driven by the need for new infrastructures to handle the computational loads, adding up quickly as more data is fed into the model. Achieving real-time access while reducing latency and cost is essential for enhancing the value of AI in decision-making and actions.