The challenge for AI developers is to find the right balance in steering AI systems while maintaining human oversight, as they navigate the complexities of this new technology.

The intelligence of AI models is becoming a commodity, and companies need to adapt by focusing on delivering software that solves real-world problems.

As AI technology evolves, we need to ensure that we responsibly scale its use to avoid unintended consequences, similar to the challenges faced with social media.

The challenge with agentic AI is balancing its capabilities with necessary guardrails to prevent misuse.

The challenge is ensuring that AI operates in the best interests of humanity, as it learns value judgments from people, but we must consider whose values are being represented.

Energy constraints are a significant challenge for AI development, as AI is creating a significant increase in demand for energy, leading to a need for innovative solutions to power data centers. The U.S. energy landscape is evolving to meet these growing demands of AI infrastructure.

The challenge in AI is that while the underlying technology is evolving rapidly, it complicates product development because you have to predict where the tech will be in a year.

As companies scale their AI applications, it's crucial to find the optimal balance across quality, cost, and speed to achieve sustainable growth.

AI as a general-purpose technology presents numerous opportunities, and our focus should be on building concrete use cases to harness its potential effectively.