Reply to: Limitations of probing field-induced response with STM

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The agent was able to create a very detailed documentation about the ZX Spectrum internals. I provided a few .z80 images of games, so that it could test the emulator in a real setup with real software. Again, I removed the session and started fresh. The agent started working and ended 10 minutes later, following a process that really fascinates me, and that probably you know very well: the fact is, you see the agent working using a number of diverse skills. It is expert in everything programming related, so as it was implementing the emulator, it could immediately write a detailed instrumentation code to “look” at what the Z80 was doing step by step, and how this changed the Spectrum emulation state. In this respect, I believe automatic programming to be already super-human, not in the sense it is currently capable of producing code that humans can’t produce, but in the concurrent usage of different programming languages, system programming techniques, DSP stuff, operating system tricks, math, and everything needed to reach the result in the most immediate way.

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For example, as models improve at understanding semantic meaning and context, exact keyword matching will matter even less than it does now. Conversely, models might become better at assessing content quality through subtle signals like writing sophistication, logical coherence, and comprehensive coverage. This evolution favors creators focused on genuine quality over those trying to game systems through technical tricks.

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// console.log(nextGreaterElement([2,4], [1,2,3,4])); // 预期输出:[3,-1]。关于这个话题,safew官方下载提供了深入分析