Feng-Chun Ben Chou

Graduate student @chenlab4, National Taiwan University.

[Yu Togashi @yutogashi158722]

Excited to share our new preprint w/@yukoyy, Chihiro Hiramatsu, @NaoTsuchiya & @oizumim! We present the first empirical evidence supporting that "my red" is "your red", through an unsupervised alignment of color qualia structures at the individual level. https://t.co/n8tKVrFDJ9

[蒼藍鴿 @bluepigeon0810]

減重到底能不能吃代糖？最新研究給了答案。

許多人都聽過：「減重別吃代糖，那會讓你更胖、還會破壞腸道菌！」
但最新發表在《Nature Metabolism》的研究，正式替代糖平反。

研究追蹤了 341 位過重或肥胖者，先讓他們減重5%，再分成兩組維持十個月：
一組不能用代糖（可吃一般糖），另一組以代糖取代一般糖。

結果發現，使用代糖的人平均多瘦了 1.6 公斤，在健康飲食前提下，代糖確實有助維持體重。
更意外的是，他們的腸道菌相也更好，��短鏈脂肪酸好菌」增加，有助代謝與飽足感。

結論是，不用過度懼怕代糖。重點不是多吃，而是「取代添加糖」。只要使用得當，還能成為減重過程中的好幫手。

[Feng-Chun Ben Chou @FengChunChou]

邀請回歸開拓者綁定邀請碼並登入遊戲，贏星瓊、禮物卡等驚喜獎勵

[Feng-Chun Ben Chou @FengChunChou]

@Kana_Momonogi @grok translates

[Feng-Chun Ben Chou @FengChunChou]

@IEObserve 其實也是相當不錯呢

[Fang-Pen Lin 🇺🇸 @fangpenlin]

Just published my new article, "Marketplace": my first attempt at efficient GPU training without backprop
😄🎉

I've been considering eliminating backprop for a while. I had an idea, experimented for two weeks, and it worked! Here's how it works:

[Shruti @heyshrutimishra]

This paper didn’t go viral but it should have.

A tiny AI model called HRM just beat Claude 3.5 and Gemini.

It doesn’t even use tokens.

They said it was just a research preview.

But it might be the first real shot at AGI.

Here’s what really happened and why OpenAI should be worried: 🧵

[marianne @MarianneReddan]

Check out our latest work in @NatureComms - we show that others’ feelings and our inferences can both be predicted from our brain activity, and that we are more accurate when these brain patterns align.

feat. @zakijam @torwager d. ong, s. mattek, & @IsabellaKahhale

[Ziming Liu @ZimingLiu11]

Interested in the science of language models but tired of neural scaling laws? Here's a new perspective: our new paper presents neural thermodynamic laws -- thermodynamic concepts and laws naturally emerge in language model training!

AI is naturAl, not Artificial, after all.

[Sam Altman @sama]

today we are introducing codex.

it is a software engineering agent that runs in the cloud and does tasks for you, like writing a new feature of fixing a bug.

you can run many tasks in parallel.

[Hudson Golino @GolinoHudson]

Are you interested in hierarchical dimensionality analysis? Here's our new "Taxonomic Graph Analysis" used to model the IPIP-NEO Personality Hierarchy. The project is led by Andrew Samo and Alexander Christensen, with the collaboration of Luis Garrido, Paco Abad, Sam McAbee, and me!

In our preprint (link in the comments) we introduce a new approach to understanding personality structure: Taxonomic Graph Analysis (TGA), is a comprehensive network psychometrics approach that identifies hierarchical personality structures from the bottom up rather than imposing existing theoretical models. We applied TGA to the open-source 300-item IPIP-NEO dataset with over 149,000 participants and reveal a three-level structure of personality:

28 first-level dimensions (facets)
6 second-level dimensions (traits)
3 third-level dimensions (meta-traits)

What makes this approach very interesting is how it addresses longstanding methodological challenges in personality assessment:

Local independence violations
Wording effects
Dimensionality assessment
Structural robustness

While some dimensions aligned with traditional IPIP-NEO structure, we found significant deviations. The emergence of novel dimensions like "Sociability," "Integrity," and "Impulsivity" at the second level and a "Disinhibition" meta-trait at the third level represents a major departure from the traditional five-factor model.

Our research effectively integrates empirical findings scattered across personality literature into a coherent hierarchical structure. This data-driven framework demonstrates TGA's value for investigating complex psychological constructs and offers a rigorous new perspective on personality taxonomy.

This work exemplifies how innovative psychometric methods can reshape our understanding of fundamental psychological constructs. Its implications extend beyond personality assessment to potentially revolutionize how we conceptualize and measure human traits across psychology.

[Intl Econ Observe @IEObserve]

美國新公布的對等關稅豁免清單，把大多數的電子產品包含手機、筆電、伺服器和主要零組件都豁免了

大街罵人，小巷豁免，打完假球可能就要和解了

[Pin-Hao Andy Chen @elvandy1515]

What will the spontaneous facial behaviors look like under a large-scale stressor, such as #BlackMonday #sotckmarketcrash or #COVID_19? A new paper from @chenlab4 published in Technology, Mind, and Behavior can tell you more! @FengChunChou

[Feng-Chun Ben Chou @FengChunChou]

@sama good

[Feng-Chun Ben Chou @FengChunChou]

Introducing Perplexity Deep Researchhttps://www.perplexity.ai/hub/blog/introducing-perplexity-deep-research

[OpenAI @OpenAI]

Updated chain of thought in OpenAI o3-mini for free and paid users, and in o3-mini-high for paid users.

[Manny Li @MannyNewsletter]

(1/4)

來自中國的 DeepSeek 事件昨晚擊沉了 NVIDIA 15% 股價。以下是一早起來速讀完一些雜食閱讀後，我目前還放在心中的 memo。
​
1. DeepSeek 令人印象深刻之處是它的訓練跟推論成本都極低，而高成本一直是過去三年來人們講到 AI 時最顧慮的，因為成本（以及連帶的電力需求）是發展的瓶頸，且突破瓶頸的方式似乎只有一個：跟 NVIDIA 買東西，因為 Jensen 說「買越多才會越便宜」（更大的叢集）。
​
2. 因此，DeepSeek 在價格上帶來的破壞，對所有其他產品與服務業者而言都是超級利多。例如，原本以為一年要花 100 億美元才能提供的服務，可能突然變成只要一半、甚至十分之一。
​
3. 承上，我一直認為一定規模的產品與服務業者會是這波 AI 革命的最大贏家。技術變化很快，但人性以及基於人性的僵化組織則變化很慢。掌握通路與銷售關係是關鍵。
​
4. 然而，DeepSeek 帶來的價格破壞也讓更多人有了彎道超車的機會，不論是新創，或是想要做 AI 升級的既有公司。

[Manny Li @MannyNewsletter]

(1/2)

不誇張，一集 podcast 就讓你搞懂遊戲發行。

自從知道 Sam（飛鳥涼不涼的遊戲營運觀察小站）開始寫粉專後，我最常做的事情就是私訊他一則新聞然後說：「我等你的分析」，因為我認定他是台灣最擅長分析遊戲市場及產業的人。

2024 年 3 月，Sam 第一次跟我提到想開一門「行銷與營運」的線上課程。當時我非常想勸���他。��畢竟朋友一場，還是介紹他跟知識衛星認識，沒想到最後真的開課了。

最近 Sam 在推廣課程，想說乾脆找他來上 podcast。非常感謝他撥空參與，成果也讓我很滿意，甚至有點驕傲地說：「如果你完全不懂遊戲發行的商業模式，這集就能讓你搞懂。」短短一小時，我們聊了以下這些話題：

● 遊戲發行的商業模式
● 遊戲行銷的變與不變
● 為什麼爆款遊戲也可能賠錢？
● 假廣告為什麼奏效？
● 如何培養遊戲營運新鮮人？
● 未來 2～3 年的市場趨勢
● 用私域流量對抗演算法 ​

不論你本身是玩家、是遊戲開發者、是遊戲營運行銷人員，或甚至以上皆非但就是對遊戲產業感興趣，這集 podcast 絕對值得一聽，收聽連結在���文。

[Karina @karinanguyen]

We're excited to introduce Tasks! For the first time, ChatGPT can manage tasks asynchronously on your behalf—whether it's a one-time request or an ongoing routine. Here are my favorite use cases:

1/ ChatGPT checks stock price every morning!

[蒼藍鴿 @bluepigeon0810]

最近晚上下診後都想吃消夜。如果家中有蘋果或芭樂，我可以一次吃掉半顆到一顆，吃完超級飽；如果沒有，我可能會吃桌上的蛋捲或餅乾，連吃好幾塊，只獲得一點飽足感，攝取熱量還是前者的好幾倍。
懂得如何吃水果，不但可以幫助減重、補充營養素，還可以減低第二型糖尿病風險。