The paper: https://ysymyth.github.io/The-Second-Half/
This analysis describes the transition of the AI field from a focus on creating novel algorithms and models in its "first half" to a new era where the emphasis shifts to defining problems and evaluation methods in the "second half." The author argues that the success of large-scale language models and reinforced learning has provided a "universal recipe" that can solve many existing benchmarks, making the creation of new models less central. The new challenge lies in developing innovative assessment strategies and real-world tasks that can effectively measure and drive further progress in AI's utility beyond current benchmarks. The piece suggests that success in this new phase will require rethinking fundamental assumptions about evaluation and moving towards a product-oriented mindset.