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After a summer consumed by fears of an AI bubble, the conversation online has turned contrarian. Maybe it's not a bubble after all? Or maybe it is, but not the bubble we thought it was? Maybe it's something else altogether? This week we share thoughts from Substackers weighing in on the state of AI valuations, with opinions ranging from, "The AI Bubble Narrative is Stupid, Wrong and Dangerous" to the suggestion that this conversation is beside the point because at least one AI company might be making itself too big to fail.

As AI has become more powerful, medical researchers are using it to predict future health conditions. Some models have predicted heart failure with 79 percent accuracy from an ECG, while others predict risk of thousands of diseases. So far, research has been confined to the lab, but now that’s starting to change.

Scientists are creating AI models built on huge amounts of past path weather data to create prediction tools that could far surpass the abilities of prediction methods used today. The difference could minimize weather disruptions and save lives.

A new social media platform from OpenAI promises a world in which any thought can be turned into a wholly realistic 10-second video. What will this do to our sense of reality? How will it change our relationship to art and creativity? What will the company do next? Substackers weigh in with reactions ranging from anger to cautious hope.

This week we spoke with Joel Mokyr, one of the three winners of this year's Nobel Prize in Economics. Mokyr is best known for demonstrating the way scientific insight and technical know-how combined to fuel unprecedented economic expansion during the Industrial Revolution, all sparked by the invention of the steam engine. Will artificial intelligence prompt a similar cycle of prosperity today? Mokyr weighs in on the promise of AI, how we are mis-measuring GDP and the three existential crises he believes pose the greatest threat to humanity. (AI is not on that list, by the way.)

Despite becoming significantly more reliable in the past five years — and winning over lots of skeptics in the process — driverless cars still face daunting obstacles on the path to ubiquity. What will it take to reduce both costs and mistakes enough so that driverless taxis become a reality in a city like, say, Boston?