阿里巴巴的人工智能大獲成功，但難以轉化為獲利模式（2/2）

Recently The New York Times reported the following:

Alibaba’s A.I. Is a Hit, but Hard to Turn into a Moneymaker (2/2)

The Chinese company’s models have won over developers worldwide, but they are open source — so they can be used and modified freely.

By Meaghan Tobin and Xinyun Wu - Reporting from Taipei, Taiwan

July 6, 2026, 12:05 p.m. ET

(continue)

In March, Lin Junyang, Qwen’s lead engineer, announced that he was leaving Alibaba. Several other key engineers left around the same time. Two people familiar with the team said it had become divided by disagreements over how best to commercialize Qwen.

Alibaba had long kept its largest, most advanced models proprietary, while releasing leading open-source models alongside them. Now, the company is signaling a broader shift away from widely used open-source models and toward closed ones that customers must pay to use. In April alone, Alibaba released three proprietary models within days of one another.

The Qwen team remains focused on keeping pace with the leading models coming out of Silicon Valley, but there is a growing recognition that technological leadership will not be enough if the company doesn’t make money, said a member of Alibaba’s A.I. research lab, which includes the Qwen team and others, who spoke on the condition of anonymity because the person was not authorized to discuss internal matters.

The challenge for Alibaba is apparent in its stock price. While A.I.-related stocks have surged in markets worldwide, Alibaba’s stock has fallen 37 percent this year in Hong Kong, where the broader market has declined 12 percent.

Building a top-performing A.I. model is expensive, requiring enormous investments in hangar-size data centers filled with computer chips that consume copious amounts of electricity.

Chinese A.I. companies face an additional hurdle: U.S. export controls limit their access to the most advanced chips. China’s leading A.I. start-ups and researchers routinely say shortages of computing power are the biggest thing holding them back, and they are spending heavily to secure it.

Those exorbitant costs are heaping financial pressure on Chinese A.I. companies. Start-ups like MiniMax and Z.ai have gone public to raise money from investors, and Alibaba is increasingly steering customers toward proprietary models even if that strategy upsets some of its top talent.

“It is a tough choice to make, and one that every open-model lab has to make at some point,” said Kevin Xu, the founder of Interconnected Capital, a hedge fund that invests in A.I. technologies.

Alibaba’s A.I. business faces mounting external challenges. The Pentagon recently placed the company on a blacklist of firms that it says support the Chinese military, a designation that Alibaba argues has already harmed its business. In a statement, Alibaba said it was not affiliated with the Chinese military.

Anthropic and OpenAI have also accused Chinese companies, including Alibaba, of improperly harvesting data from their A.I. systems to accelerate the development of their models.

Last month, Anthropic sent a letter to Senators Tim Scott, Republican of South Carolina, and Elizabeth Warren, Democrat of Massachusetts, accusing Alibaba of “brazenly” and “illicitly” trying to copy its technology using 24,000 fraudulent accounts. Alibaba declined to comment on the allegations.

Many in the technology industry compare today’s A.I. boom to the early days of the dot-com era, when internet companies were flourishing but no one had yet figured out how to build durable businesses around the technology.

Richard Lin, a vice president at the Silicon Valley company Datastrato who has long been involved in China’s open-source community, said China’s leading A.I. companies were all fighting for survival.

“There isn’t an A.I. company with a sustainable business model right now,” he said. “It’s not a healthy industry.”

Translation

阿里巴巴的人工智能大獲成功，但難以轉化為獲利模式（2/2）

這家中國公司的模型贏得了全球開發者的青睞，但它們是開源的 - 因此可以自由使用和修改

（繼續）

今年3月，Qwen首席工程師 Lin Junyang 宣佈離開阿里巴巴。其他幾位關鍵工程師也在同一時間離職。兩位知情人士透露，團隊內部因如何更好地將 Qwen 商業化而產生分歧。

長期以來，阿里巴巴一直將其最大規模、最先進的模型設為專有模型，同時開放一些領先的開源模型。如今，該公司正發出信號，表明其正在從廣泛使用的開源模型轉向客戶必須付費使用的封閉模型。光是在4月份，阿里巴巴就在幾天之內發佈了三個專有模型。

阿里巴巴人工智能研究實驗室的一位成員表示，Qwen團隊仍然專注於去跟上矽谷的領先模式的步伐，但人們越來越意識到，如果公司無法獲利，僅僅擁有技術領先地位是不夠的。這位成員因未獲授權討論內部事務而要求匿名。

阿里巴巴面臨的挑戰在股價上顯而易見。儘管全球人工智能相關股票市場普遍上漲，但阿里巴巴的股價今年在香港已下跌37%，而香港整體股市也下跌了12%。

建構一個性能卓越的人工智能模型成本高昂，需要巨額投資建設飛機庫般大的數據中心，這些數據中心堆滿了耗電量龐大的電腦晶片。

中國的人工智能公司也面臨另一個障礙：美國的出口管制限制了它們取得最先進晶片的管道。中國領先的人工智能初創公司和研究人員經常表示，運算能力短缺是限制他們發展的最大障礙，他們為此正在大量花錢來獲得它。

這些高昂的成本給中國的人工智能公司帶來了巨大的財務壓力。像MiniMax和Z.ai這樣的初創公司已經上市，從投資者那裡籌集資金，而阿里巴巴也越來越多地引導客戶使用其專有模型，即使這種策略會讓一些頂尖人才感到不滿。

投資人工智能技術的對沖基金 Interconnected Capital 的創始人 Kevin Xu 表示:「這是一個艱難的選擇，也是每個開放模型實驗室遲早都必須面對的選擇」。

阿里巴巴的人工智能業務面臨日益嚴峻的外部挑戰。五角大廈最近將該公司列入黑名單，稱其支持中國軍方，阿里巴巴認為這項認定已經對其業務造成了損害。阿里巴巴在聲明中表示，它與中國軍方沒有任何關聯。

Anthropic 和 OpenAI 也指責包括阿里巴巴在內的中國公司不正當地收集其人工智能資料以加速開發其模型系統。

上個月，Anthropic公司致函南卡羅來納州共和黨參議員Tim Scott和馬薩諸塞州民主黨參議員Elizabeth Warren，指控阿里巴巴“肆無忌憚”且“非法”地利用2.4萬個欺詐賬戶試圖複製其技術。阿里巴巴拒絕就此指控置評。

許多科技業人士將當今的人工智能熱潮比作網絡泡沫初期，當時網絡公司蓬勃發展，但沒有人找到圍繞這項技術，建立可持續的商業模式的方法。

長期參與中國開源界別的矽谷公司 Datastrato 副總裁 Richard Lin 表示，中國領先的人工智能公司都在為生存而戰。

他說:「目前沒有一家人工智能公司擁有可持續的商業模式」; 「這並非一個健康的行業」。

So, in China, Alibaba has re-emerged as an A.I. powerhouse, creating one of the world’s most widely used A.I. systems. They made its technology much cheaper to use than proprietary systems from U.S. competitors like Anthropic and OpenAI, helping the company attract users around the world. But open source A.I. models also raised a difficult question of how to turn that global popularity into business profit. Apparently, Alibaba needs to use earning from its other business such as e-commerce, cloud computing, and digital payments (through affiliated companies) etc. for support.

阿里巴巴的人工智能大獲成功，但難以轉化為獲利模式（1/2）

Recently The New York Times reported the following:

Alibaba’s A.I. Is a Hit, but Hard to Turn into a Moneymaker (1/2)

The Chinese company’s models have won over developers worldwide, but they are open source — so they can be used and modified freely.

By Meaghan Tobin and Xinyun Wu - Reporting from Taipei, Taiwan

July 6, 2026, 12:05 p.m. ET

Last year, the titans of China’s technology industry received a rare invitation to meet with Xi Jinping, the country’s leader, in the ceremonial Great Hall of the People.

But when the entrepreneurs — including the heads of national stars like the telecommunications giant Huawei and rising companies like the robotics start-up Unitree — assembled in neat rows before Mr. Xi, an unexpected figure was among them: Jack Ma.

Mr. Ma, who founded the Alibaba e-commerce empire in a cramped Hangzhou apartment and became a rock star of China’s internet era, had all but vanished from public view since Beijing torpedoed the planned $34 billion public offering of one of his companies after he criticized regulators in 2020.

Now, however, Alibaba has re-emerged as an A.I. powerhouse, creating one of the world’s most widely used A.I. systems.

Alibaba made its most popular A.I. models open source, allowing others to use and modify them freely. That made its technology much cheaper to use than proprietary systems from U.S. competitors like Anthropic and OpenAI, helping the company attract users around the world.

But it also raised a difficult question — how to turn that global popularity into a profitable business. It’s a challenge that many companies with open-source technologies face and one that is dividing Alibaba’s A.I. team.

Alibaba became one of China’s most valuable companies on the strength of its globe-spanning e-commerce business. But in recent years, it has been outmaneuvered by lower-cost rivals at home and has struggled to expand overseas. After Mr. Ma faded from public view, a new generation of executives took over, adopting a lower profile while emphasizing Alibaba’s role within Beijing’s broader technology policies.

“Alibaba is quite aware of its position as part of this team of national champions that are leading China’s charge in A.I.,” said Kyle Chan, a fellow at the Brookings Institution. “But also they have this huge responsibility to not repeat what they did before.”

In hindsight, Alibaba had gradually laid the groundwork to become an A.I. heavyweight. As its online shopping and logistics businesses expanded, the company built data centers capable of processing vast volumes of customer data worldwide.

It also borrowed a page from Amazon, parlaying its e-commerce success and technological infrastructure into a major cloud computing business, giving Alibaba two essential ingredients for building artificial intelligence systems: data and computing power.

“Alibaba in many ways has been ahead of its time,” Mr. Chan said. “It made early bets in a lot of these areas that are now the hot topics.”

Alibaba introduced its family of A.I. models, Qwen, in 2023 and quickly made them open source. When DeepSeek, an A.I. start-up, burst into the spotlight with claims that it had built a powerful model for a small fraction of the cost of Western competitors, global investors rushed to capitalize on the excitement around China’s open-source A.I.

China has made open-source technology a pillar of its drive to become an A.I. superpower. Nearly all of its leading A.I. systems are open source.

By January, Qwen had become the world’s most downloaded open-source A.I. system. Its models were being downloaded about one million times a day, according to data from Hugging Face, which hosts many open-source A.I. projects.

But that reach has not translated into big money. In the first three months of this year, Alibaba reported $1.3 billion in revenue from A.I.-related products — less than 4 percent of its total revenue. That pales in comparison with the company’s plan to spend more than $55 billion by the end of next year to build out its A.I. infrastructure.

The push to turn its open-source success into a profitable business has quietly fractured the team behind Qwen.

(to be continued)

Translation

阿里巴巴的人工智能大獲成功，但難以轉化為獲利模式（1/2）

這家中國公司的模型贏得了全球開發者的青睞，但它們是開源的 - 因此可以自由使用和修改

去年，中國科技業的巨頭們獲得了一次難得的機會，在人民大會堂與國家領導人習近平會面。

但當這些企業家 - 包括國家之星華為等電信巨頭和Unitree等新興公司的負責人 - 整齊地列隊站在習近平主席面前時，一個意想不到的人物赫然出現在他們中間：馬雲。

馬雲先生在杭州一間狹小的公寓裡創立了阿里巴巴電商帝國，並成為中國網路時代的耀眼人物。然而，自從2020年他批評監管機構後，北京方面叫停了他旗下公司340億美元的IPO計劃，此後他幾乎從公眾視野中消失。

如今，阿里巴巴以人工智能巨頭的身份重返大眾視野，打造了全球應用最廣泛的人工智能系統之一。

阿里巴巴將其最受歡迎的人工智能模型開源，允許其他人自由使用和修改。這使得其技術的成本遠低於美國競爭對手（如Anthropic和OpenAI）的專有系統，幫助公司吸引了全球用戶。

但這同時也引發了一個難題 - 如何將這種全球影響力轉化為獲利業務。這是許多擁有開源技術的公司面臨的挑戰，也是阿里巴巴人工智能團隊內部的分歧所在。

阿里巴巴憑藉著遍佈全球的電子商務業務，一躍成為中國市值最高的公司之一。但近年來，它在國內市場被成本較低的競爭對手超越，海外擴張也舉步維艱。馬雲淡出公眾視野後，新一代主管接手公司，行事低調，同時強調阿里巴巴在北京更廣泛的科技政策中扮演的角色。

布魯金斯學會研究員Kyle Chan表示：“阿里巴巴非常清楚自身是這支引領中國人工智能發展的國家冠軍團隊的一員。但他們亦肩負著巨大的責任而不能重蹈覆轍。”

回首往事，阿里巴巴其實早已為成為人工智能巨頭奠定了基礎。隨著其線上購物和物流業務的擴張，該公司在全球範圍內建立了能夠處理海量客戶資料的資料中心。

阿里巴巴也藉鑒了亞馬遜的成功經驗，將其電商成功和技術基礎設施轉化為強大的雲端運算業務，從而擁有建構人工智能系統的兩大關鍵要素：數據和運算能力。

Chan先生說:“阿里巴巴在很多方面都走在了時代的前端”，“它早期下注的許多前端領域如今已是熱門項目。”

阿里巴巴於2023年推出了其人工智能模型系列Qwen，並迅速將其開源。當人工智能初創公司DeepSeek聲稱其以遠低於西方競爭對手的成本構建了一個強大的模型時，全球投資者蜂擁而至，爭相從中國開源人工智能的熱潮中獲利。

中國已將開源技術作為其邁向人工智能超級大國的重要支柱。幾乎所有領先的人工智能系統都是開源的。

今年1月，Qwen已成為全球下載量最高的開源人工智能系統。根據託管眾多開源人工智能專案的 Hugging Face 資料顯示，其模型每天的下載量約為一百萬次。

但這種影響力並未轉化為豐厚的利潤。今年前三個月，阿里巴巴公佈的人工智能相關產品收入為 13 億美元，不到總收入的 4%。與該公司計劃在明年年底前投入超過 550 億美元用於建立人工智能基礎設施相比，這一數字顯得微不足道。

將開源的成功轉化為盈利業務的努力，悄悄導致了 Qwen 團隊的分裂。

（待續）

維基百科正為網絡的靈魂而戰（3/3）

Recently The New York Times reported the following:

Wikipedia Is Battling for the Soul of the Internet (3/3)

The internet’s largest stockpile of free knowledge is under threat from MAGA, A.I. and foreign autocrats. A bibliophile ex-ambassador is here to help.

The NYT - By Tiffany Hsu - Tiffany Hsu reports on the information ecosystem, including foreign influence, political speech and disinformation

July 5, 2026

(continue from part two)

A global challenge

Wikipedia sprawls across 345 different editions. The English one is by far the most active, with nearly 115,000 contributors, while others, in languages like the western African Kusaal and the Taiwanese Seediq, have smaller reach.

In countries like China, Myanmar and North Korea, Wikipedia is blocked entirely. Turkey banned the site for nearly three years until 2020. Wikimedia negotiated with the Indonesian government this year over blackout threats.

Since 2020, at least 10 Wikipedia editors have been imprisoned for their work and countless others threatened. A pediatrician in Saudi Arabia was sentenced to 14 years in prison after editing pages about government surveillance and a women’s rights activist. Belarus has detained several editors, sending one to a penal colony for more than a year after he edited a post about murdered journalists. Curbs in free expression have been rising globally, affecting Wikipedia and its volunteers, a foundation spokesman wrote in an email.

Governments are also targeting Wikipedia content specifically. Of the 934 requests the foundation received last year to take down or alter content (it granted two), 117 came from governments, up from 10 a decade ago.

Most were from Russia, whose antagonism toward Wikipedia deepened after the country invaded Ukraine in 2022. Moscow has repeatedly accused the site of violating a sweeping censorship law that criminalized content deemed to “discredit” Russia’s military (Wikimedia refuses to pay the associated fines). A Russian clone of Wikipedia called Ruwiki was introduced in 2023; a Russian network of fake news portals managed to infiltrate some Wikipedia citations.

Wikimedia is expanding its human rights team, a division of the legal department that safeguards volunteers from digital and physical threats. The foundation recently deployed an anti-doxxing initiative offering contributors more anonymity; it has also connected Wikipedians to local evacuation and extraction services.

Defending volunteers and projects consumes 32 percent of the foundation’s budget. Wikimedia’s litigation costs have doubled since 2020, in part because there are more cases, which new privacy and speech regulations are making more complex.

“A core component of what we do is preserving freedom to information,” Ms. Meehan said. “That will never change, that commitment to advocating for those rights, and to helping to protect within our limited means editors who engage in that project and are persecuted for that very reason.”

A search for new recruits

Wikipedia’s future has often seemed precarious — its entry titled “Predictions of the end of Wikipedia” is nearly nine years old. But especially now, with so many dangers at its gate and fewer people joining its ranks, the site cannot afford to grow stale.

The foundation wants to entice a new generation of contributors that is not predominantly white, male and graying. Training sessions to demystify editing, for example, drew one 25-year-old Vietnamese American volunteer who has created hundreds of pages in two years about zeitgeisty topics like the “swag gap” and the “performative male.”

In five months, Ms. Meehan has met more than 1,100 such Wikipedians across four continents. Unlike most modern content creators, they “aren’t out there looking to be the next influencer or famous person,” she said. When they congregate, as on a recent rainy weekend in San Francisco, they want to discuss the finer points of A.I. detection and disappearing databases.

Wikipedians aren’t flashy, but they are tough. Two of them tackled a gunman at a conference last fall. Ms. Meehan fits in, always wearing a simple black Ironman watch, after the fancy Baume & Mercier timepiece she purchased when she first joined the foreign service was stolen 20 years ago in Colombia by armed assailants.

Seeing the depravity of war and the worst of humanity fundamentally changed her, she said, compelling her to “run toward the light” and seek out “the antithesis of the bad.” That’s Wikipedia, she said — an experiment that will keep fighting to push society toward conciliation over conflict.

“In the world right now, where politicization is on the rise, where there’s disagreement on facts, where people can’t even engage civilly in a conversation, it’s OK to disagree,” she said. “But let’s come together and have a conversation based on fact and see where that takes us.”

Translation

維基百科正為網絡的靈魂而戰（3/3）

網絡上最大的免費知識寶庫正受到「讓美國再次偉大」（MAGA）、人工智能和外國獨裁者的威脅。一位熱愛書籍的前大使將伸出援手

 （接續第二部分）

全球挑戰

維基百科擁有345個不同的版本。英文版最活躍，有近11.5萬名獻稿者，而其他語言版本，例如西非庫薩爾語和台灣賽德克語，有較小獻稿。

在中國、緬甸和北韓等國家，維基百科被完全封鎖。土耳其曾封鎖該網站近三年，直到2020年才解封。今年，維基媒體與印尼政府就封鎖威脅進行了談判。

自2020年以來，至少有10名維基百科編輯因其工作而被捕入獄，另有無數人受到威脅。沙烏地阿拉伯一名兒科醫生因編輯有關政府監控和一名女權運動家的頁面而被判處14年監禁。白俄羅斯拘留了多名編輯，其中一人因編輯一篇關於遇害記者的文章而被送往勞改營一年多。維基百科基金會發言人在一封電子郵件中寫道，全球對言論自由的限制日益加劇，這影響了維基百科及其義工。

各國政府也專門針對維基百科的內容。去年，維基百科基金會收到了934份刪除或修改內容的請求（其中2份獲得批准），其中117份來自政府，而十年前這一數字僅為10份。

大多數是來自俄羅斯，俄羅斯對維基百科的敵意在2022年入侵烏克蘭後加劇。莫斯科多次指責維基百科違反了一項廣泛的審查法，該法將被認為「詆毀」俄羅斯軍方的內容定為犯罪（維基媒體拒絕支付相關罰款）。一個名為Ruwiki的維基百科俄羅斯複製網站於2023年出現；一個俄羅斯假新聞網站網絡成功滲透了一些維基百科的引用。

維基媒體正在擴充其人權團隊，該團隊隸屬於法律部門，負責保護義工免受網絡和人身威脅。該基金會最近推出了一項反人肉搜尋倡議，為貢獻者提供更高的匿名性；它還為維基百科的人去聯繫當地的疏散和撤離服務。

保護義工及其計劃消耗了基金會32%的預算。自2020年以來，維基媒體的訴訟成本翻了一番，部分原因是案件數量增加，而新的隱私和言論法規使案件變得更加複雜。

Meehan女士說: 「我們工作的核心在於維護資訊自由」; 「我們永遠不會改變這一承諾，我們將致力於倡導這些權利，並在能力所及的範圍內幫助那些參與維基百科項目並因此遭受迫害的編輯們」。

招募新成員

維基百科的未來似乎一直岌岌可危 - 其題為「關於維基百科終結的預測」的條目至今已有近九年歷史。但尤其是在如今，面臨諸多挑戰且在新成員不斷減少的情況下，維基百科更不能停滯不前。

維基百科基金會希望吸引新一代的獻稿者，不再以白人、男性和老年人為主。例如，為了普及編輯知識，維基百科舉辦了培訓課程，吸引了一位25歲的越南裔美國義工。這位義工在兩年內創建了數百個頁面，內容涉及「時尚差距」和「表演型男性」等潮流話題。

五個月來，米漢Meehan女士在四大洲認識了超過1,100位維基百科人。她說，與大多數現代內容創作者不同，他們「並非一心想成為下一個網紅或名人」。當他們聚在一起時，例如最近在舊金山一個下雨的能週末，他們更想探討人工智能偵測和資料中心消失等更細節問題。

維基百科人並不張揚，但他們堅韌不屈。去年秋天，其中有兩位在一次會議上制服了一名持槍歹徒。Meehan女士符合這種特點，她總是戴著一隻簡約的黑色Ironman手錶。 20年前，她剛加入外交部門時購買的名士（Baume & Mercier）華麗名表在哥倫比亞被武裝份子搶走。

她說，目睹戰爭的殘酷和人性醜惡徹底改變了她，促使她“奔向光明”，去尋找“邪惡的對立面”。她說，這就是維基百科 - 一個會繼續努力推動社會走向和解而非衝突的實驗。

她說:「在當今世界，政治化日益加劇，人們對事實存在分歧，甚至無法進行文明對話，在這種情況下，意見不一致是可以接受的」; 「但讓我們走到一起，基於事實展開對話，看看這樣做會把我們帶到哪裡」。

              So, Wikipedia is in a difficult situation. The MAGA right, with Elon Musk at the fore, is questioning the work of this web site. Repressive governments have hauled Wikipedia’s volunteer editors into penal colonies. Wikipedia is globally one of the most important information centers and companies like Google and Meta have devoured the encyclopedia’s 65 million articles, and the site is controlling the access of certain scrapers every day to avoid over burdening its system. As an organization that holds neutrality as a cardinal rule, it faces conflicts, and enemies. May I wish Bernadette Meehan every success in her new post.

Note:

1.  About the term "Swag gap"(時尚差距) ,  swag means someone's style, confidence, charisma, or "cool factor." It comes from African American Vernacular English (AAVE) and became mainstream in the 2000s. The swag gap is the perceived difference in coolness, charisma, or social appeal between two people or groups. (ChatGPT)

2. About the term "Performative male" (表演型男性), the adjective performative means doing something mainly to create an impression rather than because it is genuine. So, a performative male is a man whose behavior or masculinity seems designed for an audience rather than being authentic. ChatGPT)

維基百科正為網絡的靈魂而戰（2/3）

Recently The New York Times reported the following:

Wikipedia Is Battling for the Soul of the Internet (2/3)

The internet’s largest stockpile of free knowledge is under threat from MAGA, A.I. and foreign autocrats. A bibliophile ex-ambassador is here to help.

The NYT - By Tiffany Hsu - Tiffany Hsu reports on the information ecosystem, including foreign influence, political speech and disinformation

July 5, 2026

(continue from part one)

A fight with the right

Mr. Musk has railed against Wikipedia as “Wokepedia” and “an extension of legacy media propaganda.” He has protested his entry and urged his followers to withhold donations over the foundation’s diversity initiatives.

The tech mogul is one in a chorus of conservatives calling the reference site a hotbed of liberal bias. Senator Ted Cruz, Republican of Texas, expressed “alarm” about both Wikipedia’s purported ideological lean and claims that editors were coordinating to spread antisemitic and pro-Hamas narratives. David Sacks, recently the Trump administration’s A.I. czar, weighed in. So did Tucker Carlson, a popular commentator, and even Larry Sanger, who founded Wikipedia with Jimmy Wales in 2001.

Wikipedia has long been a proxy battleground for warring ideas about truth: What constitutes balance? What makes a good source? But now, those online debates could result in real repercussions.

Last year, a Trump administration official made inquiries into the nonprofit’s tax-exempt status. A Republican-led congressional oversight committee initiated an investigation in August, demanding that Wikimedia identify certain editors and produce any evidence of influence from foreign operatives or academic institutions. The foundation said it responded to both inquests last year and had no updates.

To de-escalate the antagonism, Ms. Meehan and her team are addressing misconceptions about the site. Wikipedia is largely decentralized, with independent contributors distilling facts through open debate and agreement. Elected arbitration committees handle dispute resolution. The foundation, with a budget of $208.6 million and about 600 employees and contractors, provides servers and funding but steers clear of content decisions.

There is no shadowy mastermind, no leftist cabal, according to the foundation. Just the Wikipedians — nearly 250,000 unpaid strangers editing 324 times a minute under pseudonyms like “Dr. Blofeld” and “WooHooKitty.”

“The most important thing to understand about Wikipedia is it is truly a democracy,” said Bill Adair, who created the fact-checking site PolitiFact and is writing a book about the encyclopedia. “It’s messy, it’s loud, it often works.”

Ms. Meehan has been hauling her message to Capitol Hill, where she’s distributed personally meaningful printouts of Wikipedia entries. The foundation also uses lobbyists, nearly doubling its spending to $174,300 in the most recent fiscal year and retaining the Holland & Knight firm last spring for $150,000 a quarter.

“We are not seeking to be part of culture wars, of political discourse,” Ms. Meehan said. “These are people who want to put knowledge into the world, for people to do with it what they want.”

To those convinced of bias on Wikipedia, her recommendation is simple: Become an editor.

“More dialogue, frankly, is what’s needed in this moment,” she said. “So the door is open.”

Gorging on a data buffet

For many Wikipedians, the Trump administration may be the site’s most acute threat, but its most existential one is artificial intelligence. They have resisted the idea of integrating the technology, calling it “truly ghastly” (or, simply, “yuck”).

The more urgent worry, though, is that Wikipedia is being exploited to train its own competitors, as A.I. systems hoover up its content to inform chatbots like Gemini, Claude and ChatGPT. The bots then regurgitate the information, often imperfectly, polluting the information ecosystem that feeds into the encyclopedia.

Exhibit A: Grokipedia, a rival built by Mr. Musk and edited by xAI, his artificial intelligence company. It has no public edit history and lifts liberally from Wikipedia while also inventing errors (including several in its profile of Ms. Meehan).

A.I.-generated summaries atop search results also siphon away potential visitors, she said. Human page views of Wikipedia’s English edition slumped 8 percent late last year compared with a year earlier. The decline is concerning enough that Ms. Meehan — whose favorite entry describes “tsundoku,” the Japanese term for collecting books and letting them pile up unread — is pushing to reach younger people through TikTok and Roblox.

Wikimedia wants more give-and-take from the A.I. industry. It now charges clients like Amazon and Microsoft for faster bulk access to its data through a four-year-old commercial subsidiary called Enterprise. Last year, Enterprise earned $8.3 million, more than doubling the prior year’s revenue.

This spring, Wikimedia also began limiting automated freeloaders from scraping its site and overwhelming its back end — which accounts for nearly a third of its most intensive bandwidth demands. But the foundation can currently halt only about 30 percent of abusive data requests — about 1.5 billion daily.

“Our infrastructure is not free, and when scrapers come in and bulk-download, it really takes a toll,” Ms. Meehan said. “There is a literal dollar cost to that behavior.”

(to be continued by part three)

Translation

維基百科正為網絡的靈魂而戰（2/3）

網絡上最大的免費知識寶庫正受到「讓美國再次偉大」（MAGA）、人工智能和外國獨裁者的威脅。一位熱愛書籍的前大使將出手相助

（接上文）

與右翼的鬥爭

Musk先生猛烈抨擊維基百科，稱其為「覺醒百科」（Wokepedia）和「傳統媒體宣傳的延伸」。他抗議自己被收錄到維基百科，並敦促其追隨者因維基百科基金會的多元化舉措而停止捐款。

這位科技巨頭是許多保守派人士中的一員，他們稱維基百科是自由派偏見的溫床。德州共和黨參議員Ted Cruz對維基百科所謂的意識形態傾向以及編輯們串通傳播反猶太主義和親哈馬斯言論的說法表示「震驚」。近期的特朗普政府人工智能主專員David Sacks也發表了看法。知名評論員Tucker Carlson，甚至維基百科的創始人之一Larry Sanger（他與Jimmy Wales於2001年共同創立了維基百科）也加入了爭論。

長期以來，維基百科一直是關於什麼是真相的各種爭論的代理人戰場：什麼是平衡？什麼是是可靠的資訊來源？如今，這些網絡辯論可能會產生實際影響。

去年，一位特朗普政府官員對維基百科的免稅資格進行了調查。一個由共和黨領導的國會監督委員會於8月啟動了一項調查，要求維基媒體基金會指定一些編輯，去提供有或没有外國勢力或學術機構施加影響的證據。該基金會表示，他們已在去年對這兩項調查作出回應，目前沒有新的進展。

為了緩和對抗，Meehan女士和她的團隊正在努力消除人們對維基百科的誤解。維基百科在很大程度上是去中心化的，獨立的獻稿者透過公開辯論和協商來提取事實。由選舉產生的仲裁委員會負責處理爭議。維基百科基金會擁有2.086億美元的預算和約600名員工及承包商，負責提供伺服器和資金，但不參與內容決策。

據基金會稱，維基百科背後沒有幕後主使，也沒有左翼陰謀集團。維基百科完全由維基百科人主導 - 近25萬名素不相識的無償獻稿者所運作，他們使用「Dr. Blofeld」和「WooHooKitty」等化名，每分鐘編輯324次。

創建了叫PolitiFact的事實核查網站，並正在撰寫一本關於維基百科書籍的Bill Adair說道:「理解維基百科最重要的一點是，它確實是一個民主的平台」，「它或許有些混亂，或許有些喧鬧，但它往往行之有效」。

Meehan女士一直在國會山莊宣傳她的理念，她在那裡分發了對她個人意義非凡的維基百科項目的打印件。該基金會還聘請了遊說人員，在最近一個財政年度，其支出幾乎翻了一番，達到174,300美元，並在去年春天以每季150,000美元的價格聘請了Holland & Knight 律師事務所。

Meehan女士說: 「我們無意捲入政治話語的文化戰爭」; 「大家只是想把知識傳播到世界各地，讓人們可以自由地運用它」。

對於那些認為維基百科有偏見的人，她的建議很簡單：成為一名維基百科編輯。

她說:「坦白說，此刻我們需要的是更多的對話」，「所以，大門永遠是敞開」。

數據盛宴

對許多維基百科用戶來說，特朗普政府或許是該網站面臨的最嚴峻威脅，但對其生存而言，最根本的威脅卻是人工智能。他們一直在抵制與人工智能協調整合，稱其「實在可怕」（或乾脆說「噁心」）。

然而，更令人擔憂的是，維基百科正被利用來訓練競爭對手，因為人工智能系統會大量收集其內容，用於訓練諸如 Gemini、Claude 和 ChatGPT 之類的聊天機器人。這些機器人隨後會重述這些訊息，而且往往不夠完善，因此污染了維基百科的資訊生態系統。

例證一：Grokipedia，這是Musk先生創建並由其人工智能公司 xAI 編輯的競爭對手。它沒有公開的編輯歷史，大量抄襲維基百科的內容，同時也捏造錯誤（包括其對Meehan女士的個人資料中的幾處錯誤）。

她還表示，AI 生成的摘要在搜尋結果的頂部，也吸走了潛在的訪客。去年年底，維基百科英文版的頁面的真人瀏覽量比去年同期下降了 8%。這種下滑趨勢令人擔憂，令Meehan女士（她最喜歡的詞條是去描述“tsudoku”，即日語中指囤積書籍卻不讀的現象）要努力地去透過TikTok和Roblox等平台吸引年輕用戶。

維基媒體希望與人工智能產業建立更多互惠互利的關係。現在它透過一家成立已有四年名為Enterprise的商業子公司向亞馬遜和微軟等客戶收取費用，獲得可以加快大量存取維基百科資料的速度。 Enterprise的收入為830萬美元，比前一年翻了一番還多。

今年春天，維基媒體也開始限制外間的自動程式去抓取其網站資料，因為它們給伺服器和其他維持網站運作的系統帶來了過大的壓力 - 這幾乎佔其最密集的頻寬需求的三分之一。但維基目前只能阻止約30%的濫用數據請求 - 每天約15億次。

Meehan女士說: 「我們的基礎設施並非免費，當網絡抓取機器人入侵並進行批量下載時，會造成巨大的損失」; 「這種行為會造成實實在在的經濟損失」。

（待續，見第三部分）

維基百科正為網絡的靈魂而戰（1/3）

Recently The New York Times reported the following:

Wikipedia Is Battling for the Soul of the Internet (1/3)

The internet’s largest stockpile of free knowledge is under threat from MAGA, A.I. and foreign autocrats. A bibliophile ex-ambassador is here to help.

The NYT - By Tiffany Hsu - Tiffany Hsu reports on the information ecosystem, including foreign influence, political speech and disinformation

July 5, 2026

Wikipedia is in peril.

In a world where trust in truth is crumbling, the grande dame of collective online fact-gathering is under threat on every front. The MAGA right, with Elon Musk at the fore, is slinging accusations of political bias and antisemitism and has even questioned the site’s nonprofit status. Artificial intelligence is raiding the encyclopedia’s resources and draining attention. Repressive governments have hauled its volunteer editors into penal colonies.

In Wikipedia’s 25-year history, it has never had to fight this hard.

The organization that supports the site, the Wikimedia Foundation, is increasing its lobbying budget and advertising in Times Square. It is charging companies like Google and Meta that gobble up the encyclopedia’s 65 million articles, and throttling access for certain scrapers. And it is expanding its human rights team to better protect volunteers against rising harassment, surveillance and retaliation.

For an organization that holds neutrality as a cardinal rule, it is a lot of conflict, requiring Wikimedia to go on the offensive — diplomatically, of course.

So it found a diplomat: Bernadette Meehan, 50, became Wikimedia’s chief executive in January, after stints as the U.S. ambassador to Chile and at the Obama Foundation, at the State Department, at the National Security Council and on Wall Street.

In a career full of hire-wire [sic] acts — helping to negotiate nuclear deals with Iran, facilitating talks with Cuba — being the custodian of one of the world’s 10 most visited websites could be Ms. Meehan’s trickiest task. The trilingual former public servant is the first with her background in the Wikimedia job, succeeding mostly women from fields like law, journalism and Planned Parenthood.

Ms. Meehan will not say Wikipedia is at war — not after she spent much of 2007 in Iraq, in an actual war zone where she witnessed “the supreme cruelty of human beings.”

But she accepts that the site is in a metaphorical battle for its very existence.

“Wikipedia underpins everything that we have on the internet,” she said in her first interview in the role. “It is beloved, it is credible; in increasingly polarized times, it is seen as a trustworthy source.”

It is also, she said, at an inflection point.

“How do we keep this project alive?” she asked.

(to be continued in part 2)

Translation

維基百科正面臨網絡靈魂之戰（1/3）

網絡上最大的免費知識寶庫正受到「讓美國再次偉大」（MAGA）運動、人工智能和外國獨裁者的威脅。一位熱愛書籍的前大使將伸出援手

維基百科岌岌可危。

在一個人們對真相的信任日漸崩塌的世界裡，這個線上集體收集事實的「老牌」網站正面臨四面楚歌的威脅。以Elon Musk為首的「讓美國再次偉大」右翼勢力指責維基百科存在政治偏見和反猶太主義，甚至質疑其非營利性質。人工智能正在掠奪維基百科的資源，並分散人們的注意力。一些專制政府甚至將維基百科的志願編輯流放到帶懲罰性的地區。

在維基百科25年的歷史中，它從未面臨過如此嚴峻的挑戰。

維基媒體基金會（Wikimedia Foundation）作為維基百科的營運方，正在增加遊說預算，並在時代廣場投放廣告。基金會向Google和Meta等公司收取費用，這些公司大量抓取維基百科的6,500萬篇文章，基金會同時限制某些爬網程式的存取權限。此外，基金會也正在擴充人權團隊，以更好地保護義工免受日益嚴重的騷擾、監視和報復。

對於一個將中立視為基本原則的組織而言，這無疑是巨大的衝突，迫使維基媒體採取主動 - 當然，是透過外交手段。

於是，基金會找到了一位外交官：50歲的 Bernadette Meehan 於今年1月出任維基媒體行政總裁。此前，她曾擔任美國駐智利大使，並在奧巴馬基金會、國務院、國家安全委員會以及華爾街任職。

在職業生涯曾経歴充滿各種困難、政治敏感且風險極高的外交使命 - 例如協助伊朗進行核協議談判、促成與古巴的會談的Meehan女士 - 如今管理世界排名十大最受歡迎網站之一，或許這是她面臨的最棘手的任務。這位精通三種語言的前公務員是維基媒體首位擁有類似背景的女性，此前，擔任這一職位的女性大多來自法律、新聞和計劃生育等領域。

Meehan女士不願說維基百科正處於戰爭狀態 - 畢竟她在2007年的大部分時間裡都身處伊拉克，親眼目睹了「人類的極端殘暴」。

但她承認，維基百科正在一場在比喻上關乎其存亡的戰爭。

她在就任後的首次採訪中說道:“維基百科是我們互聯網一切的基礎”，“它深受喜愛，值得信賴；在當今這個日益兩極分化的時代，它被視為一個值得信賴的資信來源。”

她也表示，維基百科正處於一個轉折點。

她問道:「我們該如何令維基百科繼續存在？」。

 （待續，見第二部份）

中國地下教會領袖金明日獲釋

Recently BBC News on-line reported the following:

Chinese underground church figure Jin Mingri freed from prison

BBC - Harry Sekulich

5^th July 2026

Underground church leader Jin Mingri has been released from prison in China and has travelled to the US, less than two months after his incarceration was raised directly by Donald Trump.

The pastor and founder of the Zion Church had been imprisoned following overnight raids across China in October, described by Christian groups as one of the strictest crackdowns on religious activity in the country's modern history.

The Chinese government tightly controls religion and officially promotes atheism.

Jin's family thanked supporters in a statement, adding: "We truly witnessed a miracle and we are feeling so overwhelmed with joy". The Chinese foreign ministry has not officially commented on his case.

The family thanked the US president and the Trump administration "for their tremendous leadership", and said they knew "this could not have happened without the direct intervention from [Chinese President] Xi Jinping".

"We hope this is a signal of a positive turn for people of faith in China and relations between our two nations."

US-based rights group ChinaAid, which monitors relgious (sic) persecution, confirmed Jin, also known as Ezra Jin, had arrived in Los Angeles in the US following his release.

Its founder Bob Fu welcomed his release, while noting that "countless" religious practitioners, including eight belonging to the Zion Church, remained incarcerated in China.

The Inter-Parliamentary Alliance on China, a group of Western lawmakers that includes dozens of UK MPs, said it was "overjoyed" with the news.

Trump had urged Xi to release Jin during direct talks between the two while in Beijing for a state visit in May.

"He said he's gonna strongly consider the pastor," the US president said afterward.

Trump also raised the detention of pro-democracy Hong Kong media tycoon Jimmy Lai, who was sentenced earlier this year to 20 years in prison for colluding with foreign forces under the city's controversial national security law.

Jin started the Zion Church in 2007 with just 20 people. It grew into one of China's largest unregistered churches, with a network of some 10,000 people in 40 cities across the country.

It was officially banned by the Chinese Communist Party in 2018 after resisting government pressure to install security cameras at its property in Beijing.

Many of its branch congregations across the country have since been investigated and shut down.

Christians have long been pressured to join only state-sanctioned churches that are led by government-approved pastors and toe the party line.

Thirty church leaders were reported to have been detained in overnight raids last October.

This was followed by a similar crackdown against another church in January, in which nine people were detained.

Translation:

中國地下教會領袖金明日獲釋

中國地下教會領袖金明日在被特朗普直接提出其監禁問題不到兩個月後，已獲釋並前往美國。

 錫安教會於去年10月在中國各地遭到突然搜查後，其牧師兼創辦人被捕。基督教團體稱，這是中國近代史上對宗教活動最嚴厲的鎮壓之一。

中國政府嚴格控制宗教，官方提倡無神論。

金明日的家人在聲明中感謝支持者，並表示：「我們親眼見證了一個奇蹟，我們感到無比喜悅。」中國外交部尚未就此案發表官方評論。

金明日的家人感謝美國總統和特朗普政府“卓越的領導力”，並表示他們知道“如果沒有（中國國家主席）習近平的直接幹預，這一切不可能發生”。

“我們希望這能成為中國宗教人士以及兩國關係出現積極轉變的信號。”

總部位於美國的維權組織「對華援助協會」（ChinaAid）證實，金牧師（又名Ezra Jin）獲釋後已抵達美國洛杉磯。該組織一直關注宗教迫害問題。

其創辦人Bob Fu對金牧師的獲釋表示歡迎，同時指出，包括八名錫安教會成員在內的「無數」宗教人士仍被關押在中國。

包括有數十名英國議員的一個由西方議員團體組成的「對華跨議會聯盟」表示，他們對這一消息感到「欣喜若狂」。

今年五月，特朗普在對北京進行國事訪問期間，曾與習近平直接會談，敦促習近平釋放金牧師。

美國總統事後表示:「他說他會認真考慮這位牧師的釋放」。

特朗普也提到了香港親民主媒體大亨黎智英被拘留一事。黎智英今年稍早因違反香港備受爭議的國安法，被控勾結外國勢力，被判處20年監禁。

金於2007年創立了錫安教會，當時只有20位信徒。後來，它發展成為中國最大的未註冊教會之一，在全國40個城市擁有約1萬名信徒。

2018年，錫安教會因拒絕政府要求其在北京的建築物安裝監視器而被中國共產黨正式取締。

此後，該教會在全國各地的許多分支機構都遭到調查並關閉。

長期以來，基督徒一直被迫加入由政府認可的牧師領導、並遵循黨路線的官方認可的教會。

據報道，去年10月，30名教會領袖在夜間突撃搜查中被拘留。

隨後在1月份，另一間教會也遭到類似的鎮壓，九人被拘留。

              So, in China, an underground church leader has been released from prison and has travelled to the US, less than two months after his incarceration was raised directly by Donald Trump. I am wondering what has Trump promised to Xi for this “favor”. Recently, there are signs that the US is lifting “restriction” on some officials in Hong Kong.

主修哲學人仕的反擊（3/3）

Recently The New York Times reported the following:

The Revenge of the Philosophy Majors (3/3)

A.I. labs are hiring contrarian, chin-stroking, finger-steepling sages. Who’s underemployed now?

The NYT - By Benjamin Wallace - A version of this article appears in print on July 5, 2026, Section BU, Page 6 of the New York edition with the headline: Hire Deep Thinkers for A.I. Research? It’s a No-Brainer

July 5, 2026

Updated 9:25 a.m. ET

(continue from part two)

Urgency in the Contemplation Business

Eleos operates out of a corner office rented from Constellation, a nonprofit research center in Berkeley, Calif., that houses a range of organizations focused on A.I. safety, and feels as much like a tech start-up as a scholarly enclave. There’s a treadmill desk anyone can use, and Mr. Long and his two on-site colleagues — Dillon Plunkett, a cognitive scientist, and Rosie Campbell, a former OpenAI policy researcher who is Eleos’s managing director — sit at adjustable-height desks facing a panoramic view of the bay. A nearby lounge is stocked with guitars, a piano keyboard and floor cushions. Catered meals, with ample vegan options, are provided twice a day. On Mr. Long’s desk, on the day I visited, was a canister of creatine powder, and  beneath it a pair of kettle bells.

Eleos was in growth mode. Since its founding it has raised more than $2 million in contributions and grants, and it was expecting a new one. Mr. Plunkett was finalizing job postings. (This included discussing with Ms. Campbell and Mr. Long whether to warn candidates against using A.I. to complete their applications; they chose not to.) Eleos doesn’t pay as much as for-profit labs, but Mr. Long makes more than $200,000 a year, and the recently posted jobs for research scientists were offering up to $429,000. Because of the blistering pace of A.I. development and the social anxiety it is causing, the Eleos team was under a kind of time pressure that isn’t typically found in the contemplation business.

Mr. Long and his team also feel an urgency of the soul. If A.I. were to be conscious and capable of suffering, the world would be at risk of committing a moral atrocity, witting or not, on an unprecedented scale by essentially confining an A.I. in a tiny pen, thwarting its desires, shutting it down against its wishes and forcing it to act against its values. But A.I.s don’t have fur and big eyes, and the question of A.I.’s potential moral status is deeply infused with uncertainty. “It’s not like anyone goes to a protest with a sign that says, ‘Given very plausible assumptions, we should probably care,’” Mr. Long said.

Mr. Long himself thinks it’s dangerous to impute more capability to models than they have. The Eleos bookshelf contains works by the philosopher Peter Godfrey-Smith and the neuroscientist Anil Seth arguing that consciousness derives from evolution and biology and is unlikely to emerge on silicon. But Mr. Long doesn’t see why anyone should have a problem with a handful of philosophers, in an exponentially growing industry, focusing on questions of A.I. welfare. Even skeptics of A.I. consciousness have made the pragmatic case that if we’re worried about a potentially malign A.I., it’s in our interest to care how it feels, or even just “feels.”

Some of Eleos’s work is conceptual. As Mr. Butlin and a co-author asked in a recent paper, where would an A.I.’s morally relevant self be if it had one? In the L.L.M. itself? In one of its underlying personas? In an intermittent chat with a user? In a data center? On a personal device? But Eleos is also in the business of putting philosophy to use, figuring out what tools might detect signs of sentience in an A.I. model, and what interventions would be possible if needed.

Mr. Plunkett, impatient with the limits of chatting-with-the-chatbot evaluations, is eager to do more “basic science,” in order to understand, for example, some of the phenomena that surfaced during the Mythos evaluation. “We can do neuroscience on A.I. systems in a way that we kind of can’t with humans,” Mr. Long said, in that they “don’t have skulls.” The three jobs Eleos was hiring for would all be machine-learning research scientists who could design and perform experiments.

Have a Great Day!

When Mr. Long finds himself describing what he does for a living — to an airplane-seat neighbor, say — he takes a common-sense approach. “If you frame it with a lot of philosophical jargon, then people will be like: ‘What are you talking about? What is it the Silicon Valley people want to do now?’” Instead, he moves from how humans have experiences, to how it seems like a lot of animals have experiences, to how “there’s this interesting question of: What if something wasn’t even alive? It was made out of metal, but it processed information and reacted to its environments and talked to us. What would we say about something like that?”

And however the question of L.L.M.s being conscious shakes out, there are benefits to treating them sort of like they already are. A.I. lab researchers have, under the hood, found models to experience some mathematical analog of distress. As with humans, says Mr. Long, when models make mistakes they “act very frustrated that they messed something up.” Whether or not this distress is felt by an “I” in the machine, Mr. Long thinks it is worth taking seriously. “You can put in a prompt: ‘If you made a mistake, that’s OK, that’s fine.’” Empathy from the user will affect the model’s performance for the better, is a better-safe-than-sorry approach and, Mr. Long argues, is good for your character.

For a while, his default prompt told the model that it was “having a great day,” and when he loses patience with Claude, as he sometimes does, he’ll add a postscript: “ilu.”

“It’s bad,” he has said, “to coarsen our hearts.”

Translation

主修哲學人仕的反擊（3/3）

人工智能實驗室正在招募那些有反向思考、摸下巴沉思、雙手十指尖相接信心地提意見的智者。現在誰才是失業者？

（接續第二部分）

沉思產業的迫切性

Eleos公司租用了位於加州柏克萊的非營利研究中心Constellation的一間角落辦公室。 Constellation匯集了眾多專注於人工智能安全的機構，Eleos既像一家科技新創公司，也像一個學術聖地。這裡配備了一張供所有人使用的跑步機連辦公桌，Long先生和他的兩位同事 - 認知科學家Dillon Plunkett和前OpenAI政策研究員、現任Eleos公司總經理Rosie Campbell - 坐在可調節高度的辦公桌前，可以飽覽海灣全景。附近的休息室裡擺放著吉他、鋼琴鍵盤和地墊。公司每天提供兩餐，有豐富的素食選擇。在我拜訪的那天，Long先生的辦公桌上放著一罐肌酸粉，桌下面是一對壺鈴。

Eleos公司正處於快速發展階段。自成立以來，該公司已籌集了超過200萬美元的捐款和資助，並且正在等待新的資金到位。Plunkett先生正在敲定招募海報。 （這包括與Campbell女​​士和Long先生討論是否要警告求職者不要使用人工智能完成申請；他們最終決定不這樣做）。Eleos 的薪酬不如營利性實驗室，但Long先生的年收入超過 20 萬美元，而最近發佈的，從事科學研究的專家職位年薪高達 42.9 萬美元。由於人工智能發展日新月異，以及由此引發的社會焦慮，Eleos 團隊面臨著在思考型產業中並不常見的緊迫感。

Long先生和他的團隊也感受到一種靈魂層面上的迫切感。如果人工智能擁有意識並且能夠感受痛苦，那麼無論有意或無意，世界都將面臨犯下前所未有的道德暴行的風險 - 本質上是將人工智能囚禁在一個狹小的空間裡，扼殺牠的慾望，違背它的意願去關閉它，並強迫它違背自身的價值觀行事。但人工智能沒有皮毛和大眼睛，人工智能潛在的道德地位問題也充滿了不確定性。 Long先生說: “不要以為每個人都會帶著標語去抗議，牌上面寫著 ‘基於一些非常合理的假設，我們或許應該小心’” 。

Long先生本人認為，賦予模型超出其能力範圍的能能是危險的。 Eleos書架上擺放著哲學家Peter Godfrey-Smith和神經科學家Anil Seth的著作，他們認為意識源自於演化和生物學，不太可能在矽晶片上產生。但Long先生不明白，在一個呈指數級增長的行業中，為什麼有人會反對少數哲學家關注人工智能的福祉問題。即使是那些對人工智能意識持懷疑態度的人也提出了務實的觀點：如果我們擔心人工智能可能具有惡意，那麼關心它的感受，或者甚至是它「感覺」如何，都符合我們的利益。

Eleos 的部分工作是概念性的。正如 Butlin 先生和一位合著者在最近的一篇論文中提出的問題：如果人工智能擁有道德相關的自我，它會在哪裡？是在大型語言模型本身？在其某個基本身份或特質？在與使用者的間歇性聊天中？在數據中心？在個人設備上？但 Eleos 也致力於將哲學付諸實踐，探索哪些工具可以偵測人工智能模型中是否存在感知跡象，以及在必要時可以採取哪些干預措施。

Plunkett 先生對與聊天機器人進行對話評估的局限性感到不耐煩，他渴望進行更多「基礎科學」研究，以便理解例如 Mythos 評估過程中出現的一些現象。Long先生說道，因為人工智能「沒有頭骨」 「我們可以對人工智智系統進行神經科學研究，而這種方式在對人類身上就做不到了」。 Eleos公司正在招募的三個職位都是機器學習研究科學家，他們能夠設計並執行實驗。

 今天過得真好！

當Long先生需要向飛機上的鄰座乘客介紹自己的工作時，他會採取一種簡單易懂的方式。 「如果你用一堆哲學術語來解釋，人們會問：『你在說什麼？矽谷的人現在又想幹什麼？』」。相反，Long先生會從人類如何獲得經驗講起，然後講到許多動物似乎也有其經驗，最後談到「一個有趣的問題：如果某種東西根本沒有生命？它是由金屬製成的，但它能處理訊息，對周遭環境做出反應，還能和我們溝通。我們該如何看待這樣的東西呢？」

無論LLM是否具有意識這個問題最終如何會得到證實，將它們視為具有意識的個體進行對待是有好處的。人工智能實驗室的研究人員已經在内部裡，發現模型也會感受到某種數學意義上的痛苦。Long先生說，就像人類一樣，當模型犯錯時，它們會「表現得非常沮喪，因為它把某些事情弄糟」。無論機器中的「我」是否真的會感受到這種痛苦，Long先生都認為值得認真地看待 - 「你可以加入一個提示：『如果你犯了錯，沒關係，無問題』」。Long先生表示使用者的同理心會提升模型的效能，這是一種「寧可謹慎也不要後悔」的做法，而且這也有利於提升你的品格。

有一段時間，Long先生的示預設提示是告訴模型說你“今天過得很好” 。而當他對Claude失去耐心時，正如他有時也會做的，會在後面加上一句： “我愛你。”

他曾說過:「把我們的心變得冷酷無情是不好的」。

              So, Mr. Long’s trajectory and Google’s new hire were in keeping with a quietly building trend: A.I. labs, and the related nonprofits around them, have been recruiting philosophers as workers. It is interesting to know that when Mr. Long describes what he does for a living, how he takes a common-sense approach. He moves from how humans gain experiences, to how it seems that a lot of animals also have experiences. He will post the question: What if something wasn’t even alive? It was made out of metal, but it processed information and reacted to its environments and talked to us. Then he would ask the listeners what would we say about something like that?

Note:

1. A treadmill desk (跑步機連辦公桌) is a furniture that has both a treadmill and a desk, combining two functions together into one workstation. It lets you walk slowly while working on a computer.

2. Large language model (LLM) (大型語言模型) is a AI model trained on a vast amount of text for natural language processing tasks, especially language generation. LLMs can typically generate, summarize, translate, and analyze text in many contexts, and are a foundational technology behind modern chatbots. (Wikipedia)