Re:Eli Lilly CEO pushes back on Dario Amodei's ludicrous med...
by svcrunch on Friday November 13, 2026 @12:09PM
(#50486473)
I'm more on Dario's side here. Putting aside Anthropic as a company, which I would short if I played the stock market, I do believe AI has the potential to do the things he's saying within ten years.
Many people working within AI, myself included, are (still) having a hard time predicting how quickly it moves, despite years of calibration. I met two of my friends, both PhD mathematicians, in June this year, and asked them for predictions on what AI might achieve in math over the next twelve months. The boldest prediction we ventured was that it might solve a frontier-level problem (but probably towards the end of the time window).
Although I have been working exclusively in NLP and NLU since 2012, the capabilities of ChatGPT in 2022 caught me by surprise, despite the fact that I had intimate knowledge of progress within Google Research until my departure in 2020.
For experts in other knowledge fields, their ability to predict AI is much worse. The tweets presented by Gary Marcus are from an industry still traumatized by Theranos, where progress has been slow and painstaking and is measured in decades. I bet if you told those same tweeters in 2015 that a group of upstart computer scientists believed protein folding could be solved in ten years, they would dismiss it as the fantasies of non-experts.
One difference between the two situations is that Theranos could never provide evidence of its technical progress, because there was none. In contrast, AI's progress is happening in the open and is available for anyone to verify.
Had Dario claimed that the cure to cancer in ten years would depend on "Anthropic's secret sauce", then the derision and dismissal would be well-earned. But read as a claim about what AI can accomplish, I find it realistic.
Many people working within AI, myself included, are (still) having a hard time predicting how quickly it moves, despite years of calibration. I met two of my friends, both PhD mathematicians, in June this year, and asked them for predictions on what AI might achieve in math over the next twelve months. The boldest prediction we ventured was that it might solve a frontier-level problem (but probably towards the end of the time window).
Although I have been working exclusively in NLP and NLU since 2012, the capabilities of ChatGPT in 2022 caught me by surprise, despite the fact that I had intimate knowledge of progress within Google Research until my departure in 2020.
For experts in other knowledge fields, their ability to predict AI is much worse. The tweets presented by Gary Marcus are from an industry still traumatized by Theranos, where progress has been slow and painstaking and is measured in decades. I bet if you told those same tweeters in 2015 that a group of upstart computer scientists believed protein folding could be solved in ten years, they would dismiss it as the fantasies of non-experts.
One difference between the two situations is that Theranos could never provide evidence of its technical progress, because there was none. In contrast, AI's progress is happening in the open and is available for anyone to verify.
Had Dario claimed that the cure to cancer in ten years would depend on "Anthropic's secret sauce", then the derision and dismissal would be well-earned. But read as a claim about what AI can accomplish, I find it realistic.