Behind the DeepSeek Hype, AI is Learning to Reason

When Chinese AI company DeepSeek announced they had built a model that could compete with OpenAI at a fraction of the cost, it sent shockwaves through the industry and roiled global markets. But amid all the noise around DeepSeek, there was a clear signal: machine reasoning is here and it's transforming AI.

In this episode, Aza sits down with CHT co-founder Randy Fernando to explore what happens when AI moves beyond pattern matching to actual reasoning. They unpack how these new models can not only learn from human knowledge but discover entirely new strategies we've never seen before – bringing unprecedented problem-solving potential but also unpredictable risks.

These capabilities are a step toward a critical threshold - when AI can accelerate its own development. With major labs racing to build self-improving systems, the crucial question isn't how fast we can go, but where we're trying to get to. How do we ensure this transformative technology serves human flourishing rather than undermining it?

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Clarification: In making the point that reasoning models excel at tasks for which there is a right or wrong answer, Randy referred to Chess, Go, and Starcraft as examples of games where a reasoning model would do well. However, this is only true on the basis of individual decisions within those games. None of these games have been “solved” in the the game theory sense.

Correction: Aza mispronounced the name of the Go champion Lee Sedol, who was bested by Move 37.

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