🔥 Ah Long Dipukul
Petang semalam, berlaku kekecohan di belakang Wisma MCA Jinjang apabila sekumpulan ah long yang datang menuntut hutang pula dipukul.
Polis bertindak pantas dan telah menangkap 13 orang. Kes masih dalam siasatan.
Memang macam drama, tapi ini kejadian sebenar.
A toothpaste company has quietly killed the entire market research industry and nobody is talking about it.
Colgate published a paper showing you can predict real purchase intent at 90% accuracy by simply asking LLMs to roleplay customers.
And this is beyond insane.
If you ask an AI, "Rate this product from 1 to 5," it gives safe, middle-of-the-road garbage.
So researchers invented a method called Semantic Similarity Rating (SSR).
Instead of asking the AI for a number, they asked it to roleplay.
They gave the LLM a demographic profile. They showed it a product concept. And they asked it to write down its raw, unfiltered thoughts.
Then, they used a semantic model to translate those written thoughts into a numerical score.
The results are staggering.
Tested against 57 real corporate surveys and 9,300 actual human responses, the synthetic AI consumers matched real human buying behavior with 90% reliability.
They perfectly mirrored how different age brackets and income levels react to price changes.
And they provided detailed, qualitative feedback that was deeper and more critical than what actual humans wrote.
This destroys the economics of traditional market research.
You don't need to wait a month to see if a product will sell.
You can simulate 1,000 hyper-targeted customer interviews overnight.
You can A/B test pricing across every demographic instantly.
if Qin Shi Huang had ordered the extermination of the Baiyue, this HK fashion model with symmetrical eyes would be a 9/10 instead of a 7/10 … and then you would understand …
people will argue that KMT exiles made Taiwanese people better looking since they were social elites with better genes; meanwhile mainland Chinese billionaire heiresses look like this at … age 30
This Japanese dude complained that Chinese uses a single-character system for every element in the periodic table — yet this is precisely one of the reasons why Chinese students can learn chemistry with remarkably little effort.
Chinese employs a highly systematic phono-semantic strategy: the radical indicates the physical category, while the phonetic component hints at the pronunciation. Metal radical 钅 → metals (e.g., 镧 lanthanum, 铍 beryllium). Gas radical 气 → gases (e.g., 氩 argon, 氦 helium). An ordinary Chinese speaker can often guess an element’s basic properties at a glance with minimal memorization.
In contrast, Japanese primarily relies on katakana transliterations of international names in scientific contexts, especially for newer elements: oxygen → オキシゲン, hydrogen → ハイドロゲン, sodium → ナトリウム, beryllium → ベリリウム. This leads to longer names (often 4–7 syllables), no built-in clues about whether it’s a metal or gas, and a higher memory load for beginners.
Japanese does have intuitive native names for many common elements (酸素 for oxygen, 水素 for hydrogen, etc.), which are widely used in education and daily life. However, formal academic and IUPAC-style contexts lean heavily on katakana, forcing students to constantly switch between the two systems.
In short: what Chinese expresses efficiently in a single meaningful character, Japanese often renders with a longer string of syllables that carry no inherent information about the element’s properties. The efficiency and intuitiveness gap is real and immediately noticeable.
@uglyluhan Ok sure. But you’ve clearly been influenced by a narrative. And all I can say is, question all narratives. Why is it meaningful to you, what ends does it serve? Are you trying to subtly undermine Malay culture and why?
@Ogrehon I don't know if this is helpful but my social life changed completely when I realized people were judging me on my appearance and expected a certain personality with that appearance. So I changed my personality. It's now all easy. I like myself less, but others like me more.