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關於腦補。
先說我支持台灣獨立、台灣不是中國。
但我們有一些事,還是需要看到其本質,才不會走偏。
腦補,是我們腦袋的自然本能,它讓我們可以把離散的資訊想像成連續體,因而造就了這個世界。
所以說這個世界是腦補的集合,也不為過。
但,我想要指出一些腦補,以免怎麼死的都不知道。
把當時罷免案當作「給台灣添亂」的人,到現在,還有多少人是這麼想?
我認同人民不需要忠於任何黨派,可以更為自己的現在以及未來著想。真正看到民生以外的東西,並且搞清楚之間的相互影響,也許是目前台灣人民的標配。
大罷免不會再來一次。冷靜才能看清楚該怎麼決策。
James@_______.tw retweeted
【金正恩访中见不到习近平?中朝关系降级?】朝鲜领导人金正恩与中国政协主席王沪宁10月24日在丹东会面。这是金正恩第六次访问中国。与以往不同的是,这是金正恩访华期间首次未与习近平会面。外界对此次访问议论纷纷,出现各种解读。
#矢板明夫印太时事三分钟 youtube.com/playlist?list=PL…
James@_______.tw retweeted
有時候
只能傻傻呆呆的看著事情發生
然後各種唏噓
但有機會盡全力解決後
當事人們根本不知道原本他們應該已經不在世上
於是
很多事情就只有自己知道
歌舞昇平的世界
其實有一堆英雄拯救了世界🫡
James@_______.tw retweeted
這麼多年以後,
羅大佑歌裡很冷門但最讓我心水的一首.
『情絲』
我真的愛,她隨風飄泊
如真的夢,不願隨風而逝
我真的愛,她由我開始
有生以來,逐漸繞成情絲
天涯咫尺,形成她的名字
是非曲直,不過是他們凡俗的事
天涯咫尺,從來不會休止
交織的情絲不過是天荒地老的事
youtu.be/mbDPxUUBmzc?si=O8QY…
James@_______.tw retweeted
全部人都知道全部人在演戲,全在應付全部人,接下來人民幣誘因漸減
這可不是甘地的"非暴力不合作"
笑,支那人沒那行,這只是因為怕死貪生,最好別人去死,自己能活下來生存策略應對。
【全民进入纯过日子】中国人的躺平新高度 | 习近平的独角戏,没人陪他再唱下去了 youtu.be/uhd9Lgw_gGI?si=g1fm…
Same opinion. This leads to our anxiety and lack of empathy. Further we lost out passion.
This explains why in Taiwan, children are forced to grow up too fast doing things they couldn't care less about, while adults often regress into children. Stripped of the chance to think for themselves, they lose the ability to decide what's truly best for them.
In a way, I bet that's the secret recipe for $TSMC's success: when nobody knows what their true passions are, everyone just scrambles to get into the one company the entire nation reveres. 🤣
大家應該看到 ETToday 的民調結果了。我來看這一點,就是類似罷免時期的催票效應,你我都可以知道,這才是我們要面對的現實。
只是記得:激化對立不是現在可以使用的策略,只可反擊,並調整姿勢。這是我的看法。
人類學習語言就跟LLM 如出一轍,是線性的、是機率式的,而不是遵守文法。文法是歸納,卻不是運算的重要元素。
Chomsky was wrong.
Researchers found your brain doesn’t store language the way every textbook since 1957 claims.
For decades, the undisputed rule of linguistics, led by Noam Chomsky, was that human language is hierarchical.
We were told our brains process language using complex "grammar trees." That we secretly build deep, abstract, mathematical rules in our heads before we speak.
This new paper proves that is completely wrong.
Researchers at Cornell University analyzed how people actually process and produce language in real time.
They found sequences. Linear chunks.
When we speak, we aren't calculating deep syntactic rules. We are just predicting the next most logical sequence of words based on the context of the words right before it.
We string linear chunks together.
If this sounds familiar, it should.
This is exactly how Large Language Models like ChatGPT work.
For years, critics have dismissed AI as "just a next-token predictor." They said it isn't truly intelligent because it doesn't understand deep grammatical hierarchies like humans do.
But this paper suggests humans don't use those hierarchies either.
We are just predicting the next chunk.
Language isn't a rigid tree of mathematical rules. It's a linear stream of contextual predictions.
We thought we were building AI to mimic the complexity of the human brain.
It turns out, the human brain was just running a simpler algorithm all along.
James@_______.tw retweeted
哇
那我更要用語言習得的方式了
Chomsky was wrong.
Researchers found your brain doesn’t store language the way every textbook since 1957 claims.
For decades, the undisputed rule of linguistics, led by Noam Chomsky, was that human language is hierarchical.
We were told our brains process language using complex "grammar trees." That we secretly build deep, abstract, mathematical rules in our heads before we speak.
This new paper proves that is completely wrong.
Researchers at Cornell University analyzed how people actually process and produce language in real time.
They found sequences. Linear chunks.
When we speak, we aren't calculating deep syntactic rules. We are just predicting the next most logical sequence of words based on the context of the words right before it.
We string linear chunks together.
If this sounds familiar, it should.
This is exactly how Large Language Models like ChatGPT work.
For years, critics have dismissed AI as "just a next-token predictor." They said it isn't truly intelligent because it doesn't understand deep grammatical hierarchies like humans do.
But this paper suggests humans don't use those hierarchies either.
We are just predicting the next chunk.
Language isn't a rigid tree of mathematical rules. It's a linear stream of contextual predictions.
We thought we were building AI to mimic the complexity of the human brain.
It turns out, the human brain was just running a simpler algorithm all along.

















