There is ongoing debate in the AI community about whether we have reached the limits of scaling laws, as the latest models have become larger and more expensive, yet their capabilities seem to be plateauing.

The AI field is approaching diminishing returns with large language models, as the amount of natural text data available for training is becoming limited, which may hinder future advancements.

The future of AI may involve models communicating in a more efficient, nuanced language that humans cannot easily understand.

If AI models are locked away with strict rules, we risk losing freedom of thought, which is essential for meaningful communication.

For the first time in history, machines can engage in conversation, allowing people to share intimate details of their lives with AI models.

We envision a scenario where hundreds of thousands to millions of AI agents are working in parallel, but the real limitations will be in taste and computational resources, not the number of agents.

The success of multimodal models has narrowed the diversity of ideas in AI, leading to concerns about reaching the limits of usable human data.

AI has transformed our business, enabling us to offer conversation practice through large language models, which was previously impossible without human interaction.

As people interact with AI systems, the question arises whether these models have experiences of their own and how that shapes our relationships with them.