What is Hackers' Pub?

Hackers' Pub is a place for software engineers to share their knowledge and experience with each other. It's also an ActivityPub-enabled social network, so you can follow your favorite hackers in the fediverse and get their latest posts in your feed.

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지난해 대통령 선거 직전, 수만 명으로 추정되는 한국교원단체총연합회(아래 교총) 관련 교원의 개인정보를 무단으로 빼돌려 당시 '국민의힘 김문수 대통령 후보 임명장'을 무더기로 발송한 혐의를 받는 교총 전 사무총장과 당시 국장급 인사가 재판에 넘겨진 것으로 확인됐다. 혐의는 개인정보보호법 위반이다.

지난해 대통령 선거 직전, 수만 명으로 추정되는 한국교...

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지난해 대통령 선거 직전, 수만 명으로 추정되는 한국교원단체총연합회(아래 교총) 관련 교원의 개인정보를 무단으로 빼돌려 당시 '국민의힘 김문수 대통령 후보 임명장'을 무더기로 발송한 혐의를 받는 교총 전 사무총장과 당시 국장급 인사가 재판에 넘겨진 것으로 확인됐다. 혐의는 개인정보보호법 위반이다.

지난해 대통령 선거 직전, 수만 명으로 추정되는 한국교...

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연친이 룰에 따른 전술요소를 이야기 하고 있다...

단장의 아그니야도 총을 업그레이드 하면서 총 옆에 최근에 달아둔 사이드캐리어 에 무슨 탄환이 몇 발씩 있는지, 탄창에는 지금 어떤 탄종이 몇 발씩 들어가 있는지를 머리굴려가며 진지하게 따져야 하게 되엇서요.....

가기에 방패들고 기동력으로 적에게 달라붙어서 싸우는 방식이다보니까 전장의 어느 위치에 붙어야 놈들의 사격을 효과적으로 막아내고 방해 할 수 있는지를 따져가며 해야하니 단장의 능지가 버틸 수 있을지 걱정해야하는거에오

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遲早會出現沒上網就無法使用的電視吧

海信(Hisense)電視在進入 live TV 前強制播放無法跳過的開機全螢幕廣告 https://www.guru3d.com/story/hisense-vidaa-tvs-reportedly-add-unskippable-startup-ads-before-live-tv/

多位 Hisense(海信)Smart TV 使用者回報,搭載 VIDAA(海信等品牌採用的 Smart TV 作業系統)的電視在開機後,會先強制播放一則全螢幕廣告,且在廣告播完前無法跳過;即使只是想看傳統的電視頻道(live TV),也得先「看完廣告」才能進到第一個頻道或訊源。類似抱怨也出現在同樣使用 VIDAA 的 Toshiba 與 JVC 品牌機種,顯示這比較像是平台層級的變更,而非單一型號的個案。對不少把「開機就能看電視」視為基本功能的買家來說,廣告被塞進開機必經路徑,等同改寫了使用體驗底線,因此引發強烈反彈。

文章也把這件事放進 VIDAA 更大的廣告版圖來看:Nexxen 將自己定位為 VIDAA 原生廣告庫存的程式化(programmatic,指以自動化系統即時購買與投放)合作夥伴,一旦作業系統層級開出固定版位,就能規模化、持續填滿,而不必仰賴各個 App 自行變現。隨著廣告更靠近作業系統核心,隱私疑慮也跟著升溫,因為有使用者聲稱即使關閉資料同意選項,仍出現開機廣告。VIDAA 的資料說明文件提到,電視可能產生包含裝置識別碼、地區/位置設定、網路連線資訊(如 WAN IP,對外網路 IP 位址),以及觀看/使用紀錄(例如開關機時間、觀看歷史)等資料,使外界更容易聯想到 UI(使用者介面)內的廣告投放可能走向更細緻的目標鎖定。報導指出目前未見明確、對消費者友善的總開關能完全關閉這種「開機插播」,若屬分批推送,後續是否變成可選、區域限制或擴大到更多介面區塊,將影響使用者是否轉而繞過內建平台,甚至拒買該生態系。

Hacker News 留言區的情緒大多是憤怒與疲乏,許多人直接把這類作法視為品牌黑名單;也有人感嘆「廣告必須用強迫的」代表廣告產業效益遞減卻仍硬塞。部分留言補充了為何市場會走到今天:除了確實有人寧願用更低售價換取廣告,還存在檸檬市場(Market for Lemons,因資訊不對稱導致劣幣驅逐良幣)問題,因為購買當下很難評估未來廣告會多惱人;更糟的是所謂 enshittification(產品為了變現而持續劣化的過程),廠商常在賣出、使用者被綁住後才透過韌體更新改條款、加塞廣告。討論也延伸到其他平台的「促銷即廣告」灰色地帶,例如 Apple 生態系裡的訂閱推播、部分電視自動裝新 App(如 Copilot)等,凸顯這不只是單一廠牌的問題。

在做法上,留言區給了很多「把電視當螢幕」的自救方案:最常見是讓電視永久不連網,把所有連網與串流功能交給外接盒(如 Apple TV、NVIDIA Shield)或 Linux HTPC(家用劇院電腦);也有人建議用 AdGuard、Pi-hole(以 DNS 為核心的家用廣告攔截方案)等做 DNS(Domain Name System,網域名稱系統)過濾,或用 VLAN(Virtual LAN,虛擬區域網路)與防火牆白名單控管連線,甚至在 Android TV 上用 ADB(Android Debug Bridge,Android 除錯橋)停用預載 App、改用 Projectivy 等無廣告啟動器。另一派則警告貓捉老鼠會升級:廠商可能用更難攔的連線方式(例如 ECH,Encrypted Client Hello,TLS 握手資訊加密)或內建行動網路數據機來繞過家用網路管控,並把廣告與 DRM(Digital Rights Management,數位版權管理)綁得更深;因此也有人改推「商用顯示器/電腦螢幕」這類更接近純顯示器的產品,並呼籲用錢包投票,否則注意力與隱私只會變成需要額外付費才能保住的奢侈品。

👥 122 則討論、評論 💬
https://news.ycombinator.com/item?id=47322966
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'친구보다 친구 같은 AI' 손에 쥔 초등생‥"커도 사람 못 사귈 수도" imnews.imbc.com/replay/2026/... 전문가들은 특히 아동의 경우 AI에 과의존하기 쉽고 사회성 발달에도 악영향을 줄 우려가 크다고 경고합니다. [트리스탄 해리스/전 구글 윤리 최고책임자] '무조건적 공감'을 하는 AI, '의인화된 형태'의 AI도 어린이, 청소년에게 금지돼야 한다고 주장했습니다.

'친구보다 친구 같은 AI' 손에 쥔 초등생‥"커도 사...

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I'm writing this in English.

Not because English is my first language—it isn't. I'm writing this in English because if I wrote it in Korean, the people I'm addressing would run it through an outdated translator, misread it, and respond to something I never said. The responsibility for that mistranslation would fall on me. It always does.

This is the thing Eugen Rochko's post misses, despite its good intentions.

@GargronEugen Rochko argues that LLMs are no substitute for human translators, and that people who think otherwise don't actually rely on translation. He's right about some of this. A machine-translated novel is not the same as one rendered by a skilled human translator. But the argument rests on a premise that only makes sense from a certain position: that translation is primarily about quality, about the aesthetic experience of reading literature in another language.

For many of us, translation is first about access.

The professional translation market doesn't scale to cover everything. It never has. What gets translated—and into which languages—follows the logic of cultural hegemony. Works from dominant Western languages flow outward, translated into everything. Works from East Asian languages trickle in, selectively, slowly, on someone else's schedule. The asymmetry isn't incidental; it's structural.

@GargronEugen Rochko notes, fairly, that machine translation existed decades before LLMs. But this is only half the story, and which half matters depends entirely on which languages you're talking about. European language pairs were reasonably serviceable with older tools. Korean–English, Japanese–English, Chinese–English? Genuinely usable translation for these pairs arrived with the LLM era. Treating “machine translation” as a monolithic technology with a uniform history erases the experience of everyone whose language sits far from the Indo-European center.

There's also something uncomfortable in the framing of the button-press thought experiment: “I would erase LLMs even if it took machine translation with it.” For someone whose language has always been peripheral, that button looks very different. It's not an abstract philosophical position; it's a statement about whose access to information is expendable.

I want to be clear: none of this is an argument that LLMs are good, or that the harms @GargronEugen Rochko describes aren't real. They are. But a critique of AI doesn't become more universal by ignoring whose languages have always been on the margins. If anything, a serious critique of AI's political economy should be more attentive to those asymmetries, not less.

The fact that I'm writing this in English, carefully, so it won't be misread—that's not incidental to my argument. That is my argument.

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I'm writing this in English.

Not because English is my first language—it isn't. I'm writing this in English because if I wrote it in Korean, the people I'm addressing would run it through an outdated translator, misread it, and respond to something I never said. The responsibility for that mistranslation would fall on me. It always does.

This is the thing Eugen Rochko's post misses, despite its good intentions.

@GargronEugen Rochko argues that LLMs are no substitute for human translators, and that people who think otherwise don't actually rely on translation. He's right about some of this. A machine-translated novel is not the same as one rendered by a skilled human translator. But the argument rests on a premise that only makes sense from a certain position: that translation is primarily about quality, about the aesthetic experience of reading literature in another language.

For many of us, translation is first about access.

The professional translation market doesn't scale to cover everything. It never has. What gets translated—and into which languages—follows the logic of cultural hegemony. Works from dominant Western languages flow outward, translated into everything. Works from East Asian languages trickle in, selectively, slowly, on someone else's schedule. The asymmetry isn't incidental; it's structural.

@GargronEugen Rochko notes, fairly, that machine translation existed decades before LLMs. But this is only half the story, and which half matters depends entirely on which languages you're talking about. European language pairs were reasonably serviceable with older tools. Korean–English, Japanese–English, Chinese–English? Genuinely usable translation for these pairs arrived with the LLM era. Treating “machine translation” as a monolithic technology with a uniform history erases the experience of everyone whose language sits far from the Indo-European center.

There's also something uncomfortable in the framing of the button-press thought experiment: “I would erase LLMs even if it took machine translation with it.” For someone whose language has always been peripheral, that button looks very different. It's not an abstract philosophical position; it's a statement about whose access to information is expendable.

I want to be clear: none of this is an argument that LLMs are good, or that the harms @GargronEugen Rochko describes aren't real. They are. But a critique of AI doesn't become more universal by ignoring whose languages have always been on the margins. If anything, a serious critique of AI's political economy should be more attentive to those asymmetries, not less.

The fact that I'm writing this in English, carefully, so it won't be misread—that's not incidental to my argument. That is my argument.

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I'm writing this in English.

Not because English is my first language—it isn't. I'm writing this in English because if I wrote it in Korean, the people I'm addressing would run it through an outdated translator, misread it, and respond to something I never said. The responsibility for that mistranslation would fall on me. It always does.

This is the thing Eugen Rochko's post misses, despite its good intentions.

@GargronEugen Rochko argues that LLMs are no substitute for human translators, and that people who think otherwise don't actually rely on translation. He's right about some of this. A machine-translated novel is not the same as one rendered by a skilled human translator. But the argument rests on a premise that only makes sense from a certain position: that translation is primarily about quality, about the aesthetic experience of reading literature in another language.

For many of us, translation is first about access.

The professional translation market doesn't scale to cover everything. It never has. What gets translated—and into which languages—follows the logic of cultural hegemony. Works from dominant Western languages flow outward, translated into everything. Works from East Asian languages trickle in, selectively, slowly, on someone else's schedule. The asymmetry isn't incidental; it's structural.

@GargronEugen Rochko notes, fairly, that machine translation existed decades before LLMs. But this is only half the story, and which half matters depends entirely on which languages you're talking about. European language pairs were reasonably serviceable with older tools. Korean–English, Japanese–English, Chinese–English? Genuinely usable translation for these pairs arrived with the LLM era. Treating “machine translation” as a monolithic technology with a uniform history erases the experience of everyone whose language sits far from the Indo-European center.

There's also something uncomfortable in the framing of the button-press thought experiment: “I would erase LLMs even if it took machine translation with it.” For someone whose language has always been peripheral, that button looks very different. It's not an abstract philosophical position; it's a statement about whose access to information is expendable.

I want to be clear: none of this is an argument that LLMs are good, or that the harms @GargronEugen Rochko describes aren't real. They are. But a critique of AI doesn't become more universal by ignoring whose languages have always been on the margins. If anything, a serious critique of AI's political economy should be more attentive to those asymmetries, not less.

The fact that I'm writing this in English, carefully, so it won't be misread—that's not incidental to my argument. That is my argument.

2
0
0

I'm writing this in English.

Not because English is my first language—it isn't. I'm writing this in English because if I wrote it in Korean, the people I'm addressing would run it through an outdated translator, misread it, and respond to something I never said. The responsibility for that mistranslation would fall on me. It always does.

This is the thing Eugen Rochko's post misses, despite its good intentions.

@GargronEugen Rochko argues that LLMs are no substitute for human translators, and that people who think otherwise don't actually rely on translation. He's right about some of this. A machine-translated novel is not the same as one rendered by a skilled human translator. But the argument rests on a premise that only makes sense from a certain position: that translation is primarily about quality, about the aesthetic experience of reading literature in another language.

For many of us, translation is first about access.

The professional translation market doesn't scale to cover everything. It never has. What gets translated—and into which languages—follows the logic of cultural hegemony. Works from dominant Western languages flow outward, translated into everything. Works from East Asian languages trickle in, selectively, slowly, on someone else's schedule. The asymmetry isn't incidental; it's structural.

@GargronEugen Rochko notes, fairly, that machine translation existed decades before LLMs. But this is only half the story, and which half matters depends entirely on which languages you're talking about. European language pairs were reasonably serviceable with older tools. Korean–English, Japanese–English, Chinese–English? Genuinely usable translation for these pairs arrived with the LLM era. Treating “machine translation” as a monolithic technology with a uniform history erases the experience of everyone whose language sits far from the Indo-European center.

There's also something uncomfortable in the framing of the button-press thought experiment: “I would erase LLMs even if it took machine translation with it.” For someone whose language has always been peripheral, that button looks very different. It's not an abstract philosophical position; it's a statement about whose access to information is expendable.

I want to be clear: none of this is an argument that LLMs are good, or that the harms @GargronEugen Rochko describes aren't real. They are. But a critique of AI doesn't become more universal by ignoring whose languages have always been on the margins. If anything, a serious critique of AI's political economy should be more attentive to those asymmetries, not less.

The fact that I'm writing this in English, carefully, so it won't be misread—that's not incidental to my argument. That is my argument.

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