non-expert humans comfortably exceed 60%
【洞察】120 倍的人机差距意味着:当前 AI 推理能力的提升是「在已知模式上的优化」,而非「真正的归纳推理泛化」。这对所有声称「AI 已接近人类」的产品宣传都是正面挑战——AGI 时间线的预期需要重新校准,而非渐进式调整。
non-expert humans comfortably exceed 60%
【洞察】120 倍的人机差距意味着:当前 AI 推理能力的提升是「在已知模式上的优化」,而非「真正的归纳推理泛化」。这对所有声称「AI 已接近人类」的产品宣传都是正面挑战——AGI 时间线的预期需要重新校准,而非渐进式调整。
The human's job is to curate sources, direct the analysis, ask good questions, and think about what it all means. The LLM's job is everything else.
【启发】这句话是对未来知识工作分工的最清晰定义:人负责「品味、方向、意义」,AI 负责「执行、维护、连接」。这不是「AI 替代人」的叙事,而是「AI 承担所有繁琐工作,人专注于真正重要的判断」。对团队 AI 工具设计的启发:最好的 AI 工具设计应该让人的时间 100% 用在「只有人才能做的事」上——而这个边界,正在随着 AI 能力的提升不断向内收缩。
for - from - LinkedIn post - AI LLM judgment vs human judgment - https://hyp.is/UdbScM05EfC_JWs5FhG-Mg/www.linkedin.com/posts/walterquattrociocchi_ive-never-had-two-editorials-in-top-tier-activity-7399375954743123968-Sn9Y/?rcm=ACoAACc5MHMBii80wYJJmFqll3Aw-nvAjvI52uI
for - natural language acquisition - Automatic Language Growth - ALG - youtube - interview - David Long - Automatic Language Growth - from - youtube - The Language School that Teaches Adults like Babies - https://hyp.is/Ls_IbCpbEfCEqEfjBlJ8hw/www.youtube.com/watch?v=984rkMbvp-w
summary - The key takeaway is that even as adults, we have retained our innate language learning skill which requires simply treating a new language as a new, novel experience that we can apprehend naturally simply by experiencing it like the way we did when we were exposed to our first, native language - We didn't know what a "language" was theoretically when we were infants, but we simply fell into the experience and played with the experiences and our primary caretakers guided us - We didn't know grammar and rules of language, we just learned innately
human beings don't do that we understand that the chair is not a specifically shaped object but something you consider and once you understood that concept that principle you see chairs everywhere you can create completely new chairs
for - comparison - human vs artificial intelligence
question - comparison - human vs artificial intelligence - Can't an AI also consider things we sit on to then generalize their classifcation algorithm?
the brain is Islam Islam is it is lousy and it is selfish and still it is working yeah look around you working brains wherever you look and the reason for this is that we totally think differently than any kind of digital and computer system you know of and many Engineers from the AI field haven't figured out that massive difference that massive difference yet
for - comparison - brain vs machine intelligence
comparison - brain vs machine intelligence - the brain is inferior to machine in many ways - many times slower - much less accurate - network of neurons is mostly isolated in its own local environment, not connected to a global network like the internet - Yet, it is able to perform extraordinary things in spite of that - It is able to create meaning out of sensory inputs - Can we really say that a machine can do this?
you're going to have like 100 million more AI research and they're going to be working at 100 times what 00:27:31 you are
for - stats - comparison of cognitive powers - AGI AI agents vs human researcher
stats - comparison of cognitive powers - AGI AI agents vs human researcher - 100 million AGI AI researchers - each AGI AI researcher is 100x more efficient that its equivalent human AI researcher - total productivity increase = 100 million x 100 = 10 billion human AI researchers! Wow!
if I met a robot that looked very much like a beautiful girl and everything went fine together with her and me but
for - comparison - human vs AI robot - Denis Noble
But is it a good idea to outsource critical feedback to a machine?
Side note: When I flagged yours as a dupe during review, the review system slapped me in the face and seriously accused me of not paying attention, a ridiculous claim by itself since locating a (potential) dupe requires quite a lot of attention.
Yes, autoexpect is a good tool, but it is used just to automatically create TCL-expect scripts, by watching for user. So it’s can be equal to writing expect-scripts by hand.
You can now distribute your add-on. Note, however, that your add-on may still be subject to further review, if it is you’ll receive notification of the outcome of the review later.
that can be partially automated but still require human oversight and occasional intervention
but then have a tool that will show you each of the change sites one at a time and ask you either to accept the change, reject the change, or manually intervene using your editor of choice.