The problem that I see with this analysis is that the author is trying to describe a curve in data that is kind of a punctuated equilibrium on steroids. Given that the takeoff event is when systems are capable of recursive self-improvement and that event will be a huge inflection point in the curve, it feels like they are trying to predict the second half of a biphasic graph based on data from the first half, when the second half is distinctly different than the first.
Thinking about how this might work, the slope of the first half does not predict the inflection point. Once the threshold for recursive self-improvement gets crossed, the curve changes drastically. From what I have heard MAYBE we are just starting to see the glimmers of possible recursive self-improvement in GPT-5.3 / Opus 4.6. If so, this discussion, while interesting, is trying to predict the new curve based on a single relevant data point.
The most recent quarter (Q1 2024) is one week shorter than the prior year. I think the comment you made would make sense if it were the reverse. Regardless, it is interesting to hear how analysts account for this kind of thing…
So I have given this some thought, and the legal issue is not fair use unless the new work is really clearly derivative. The concern is that the system was trained on content that was not purchased or licensed. The systems effectively need a license to CONSUME / LEARN FROM the content. The human equivalent would be purchasing a single copy of a work, or checking it out of a library. In one case the consumer purchased a license for a copy of the work, in the other the library did.
In the case of the generative AI companies, I think there is a good amount of content that has been consumed that was neither in the public domain or properly licensed.
Thinking about how this might work, the slope of the first half does not predict the inflection point. Once the threshold for recursive self-improvement gets crossed, the curve changes drastically. From what I have heard MAYBE we are just starting to see the glimmers of possible recursive self-improvement in GPT-5.3 / Opus 4.6. If so, this discussion, while interesting, is trying to predict the new curve based on a single relevant data point.