人工智能聰明了，但人類智能蠢了

Recently Jacky FUNG 馮智政 in his Patron published the following:

Education｜人工智能聰明了，但人類智能蠢了

By Jacky FUNG 馮智政

Jacky FUNG 馮智政 Patron (https://www.patreon.com/jackyfungcc/posts/education-ren-170778249)

Mon, Sep 28 at 3:40 p.m.

國際學生能力評估PISA 2025 創新低，科技融入學習做錯嗎？

人工智能在今年上海國際數學奧林匹克考得滿分。同一時間，經合組織公布 #PISA2025：經合組織國家十五歲學生的閱讀、數學、科學平均分，三科同創有紀錄以來最低¹。閱讀十年跌了28分，按經合組織「約20分等於一年學習進度」換算，等於少讀了一年半書。三科都達不到基本水平的學生，由三年前每六個一個，升至每五個一個¹。

01/

跌在哪裡，比跌了多少更値得留意。讀得快、答得錯的「急讀」學生，七年間接近倍增至9%；超過三分一學生查證過資料來源，最後仍然選擇相信直覺¹。這不是學少了，而是讀書的方式變了，補習加操解決不了。

❚ ❚ 問題在AI出現前已經開始

02/

第一個原因是屏幕本身。多項整合研究發現，紙本閱讀的理解程度一直勝過屏幕，而且2000年後進行的研究差距更大，數碼原住民一樣輸；更麻煩的是，在屏幕上閱讀的人，還會以為自己明白了²。

這並非新發現。經合組織早在2015年已經警告，在學校電腦上花大錢的國家，成績沒有改善³。十年後，瑞典掉頭買回印刷書⁴。

屏幕之外，專注力亦同時被拆走。資訊學教授Gloria Mark追蹤上班族近二十年，人在屏幕前停留而不轉走的時間，由2004年的兩分半鐘縮至47秒⁵。讀懂一篇教材，需要的專注以小時計。

❚ ❚ 用AI做功課的真正代價

03/

經濟學者Strömberg、Lei與Wu追蹤兩萬六千多名中國中學生，發現用AI做功課後，功課分數升了18%，半年內月考卻跌了20%⁶。

受創最深的，竟是成績最好的三分一，跌幅達24%。

但損失並非人人有份，而是集中在約八成「外判功課」的學生身上：做得特別快、分數特別高的那一批⁶。PISA看到同一件事：用AI代勞的學生成績偏低；每週用一兩次輔助學習的，與不用者相若；經常使用而又學過分辨AI真偽的，才稍勝一籌¹。AI不是捷徑，最好的情況，只是沒有蝕，再加一點。

分野不在用不用AI，而在省下的時間去了哪裡。本來要90分鐘的功課，40分鐘做完，多出來的那一截，是誰替你想的？

省下的時間，就是被外判的思考。

❚ ❚ 揀學校，應該問甚麼

04/

經合組織教育總監Andreas Schleicher點名南韓，形容其科技運用更深思熟慮、更有意圖，用法由教師設計⁷。這份克制由來已久：2015年，南韓學生每日在校用電腦只有9分鐘，不到澳洲的六分之一³。

以後揀學校，就不要只問有多少部機械人、多少部3D打印機，要問兩件事：功課的設計，有沒有令學生非花時間不可；AI的用法，由老師設計，還是由學生自決。

PS：人工智能愈來愈聰明，學生的智能愈來愈薄弱，到時誰是贏家，誰是輸家？

¹ OECD, PISA 2025 Results (Volume I), 2026；Country Note: Hong Kong (China) ² Delgado et al., Educational Research Review, 2018；Clinton, Journal of Research in Reading, 2019 ³ OECD, Students, Computers and Learning: Making the Connection, 2015 ⁴ 美聯社，2023年9月 ⁵ Gloria Mark, Attention Span, 2023 ⁶ Strömberg, Lei & Wu, The Generative AI Learning Penalty, CEPR Discussion Paper No. 21577, 2026（未經同行評審） ⁷ Financial Times，2026年9月8日 ⁸ Smartphone Free Childhood, Parent Pact, 2024（簽署數字為機構自報）

(Source: https://www.patreon.com/jackyfungcc/posts/education-ren-170778249)

Comment:

So, it is noted that PISA 2025 scores hit a new low; did we make a mistake in integrating technology into learning? The article suggested that the problem started before the advent of AI. The first reason is the screen itself. Analyses have found that reading comprehension on paper has consistently outperformed screens. It is also shocking to note that this is not a new discovery. As early as in 2015, the OECD warned that countries spending large amounts of money on school computers saw no improvement in academic performance. A decade later, Sweden reversed course and brought back printed books. Apparent, printed media still has it value.

Note:

1. Jacky Fung Chi Ching (馮智政) is a prominent Hong Kong think-tank researcher, political commentator, and media host. He holds a master's degree in International Relations from HKU and pursued a doctorate in Education at CUHK. Fung has worked extensively with institutions like the Hong Kong Policy Research Institute and the Roundtable think tank. Widely recognized for his sharp socio-political analysis, he has hosted popular radio and television programs, including Commercial Radio Hong Kong's Guan Ming Ding. Currently based in the UK, Fung continues to engage audiences globally through his analytical YouTube platform, the Sinic Political and Economic Channel. (Google)

中國真的在竊取美國公司的人工智能技術嗎？

Recently The New York Times reported the following:

Is China Really Stealing A.I. From American Companies?

As Xi Jinping visits President Trump in Washington, the leaders are expected to discuss claims that China is surreptitiously copying American A.I. technologies, a process known as distillation.

The NYT - By Cade MetzReporting from San Francisco  (Cade Metz is a Times reporter who writes about artificial intelligence, driverless cars, robotics, virtual reality and other emerging areas of technology.)

Sept. 25, 2026Updated 11:02 a.m. ET

For nearly two years, companies like Anthropic, OpenAI and Google have accused Chinese companies of unfairly copying their artificial intelligence technologies. As the Chinese leader Xi Jinping visits President Trump this week in Washington, these claims have become a flashpoint in their discussions.

Amid growing concern over the dangers of A.I., the leaders are expected to discuss the rapid rise of the technology, with many U.S. officials, tech executives and everyday people calling for a slowdown. American companies like Anthropic and OpenAI are leading the A.I. race, but Chinese start-ups like Z.ai and Moonshot are not far behind.

One of the more contentious issues on the table is Silicon Valley’s repeated claim that Chinese companies are copying the leading American technologies using a technique called “distillation.”

Many experts say the claims from companies like Anthropic and OpenAI are overblown. “The narrative that all of the capabilities of the Chinese technologies coming from an Anthropic model is not as true as people say it is,” said Charles O’Neill, a head of model training at Baseten, a U.S. company that sells access to Chinese technologies.

Here is a guide to a niche technical process that has now become a geopolitical issue.

What exactly is distillation?

First developed in the early 2010s, distillation was initially a way for A.I. researchers to build more efficient technologies. Using this technique, they could collect data from an established system and use that data to build a new system able to run on less expensive hardware.

“Think of one model as the teacher and the other as a student,” Geoffrey Hinton, a former Google researcher who helped develop the technique, recently told The Times.

Companies still use distillation in this way. But more recently, the technique has also become a way for companies to collect data from technologies built by others.

Basically, an outside company looking to distill a competitor’s system will set up many accounts on the competitor’s service, say Anthropic’s Claude or OpenAI’s GPT. The distilling company will then assign those systems to particular tasks, such as computer coding or mathematics.

The distiller can then use the information generated by these established A.I. systems to help train a new system of their own.

Is distillation illegal?

Some legal scholars say that distillation could violate the Defend Trade Secrets Act, a law that allows companies to sue over the theft of trade secrets. But U.S. courts have not decided this issue.

Copyright law does not necessarily apply, because distillation is an effort to copy the general behavior of the system rather than to copy its text word for word.

Critics of Anthropic and OpenAI point out that the two companies have engaged in similar behavior.

Anthropic is facing multiple lawsuits that accuse the San Francisco start-up of illegally using copyrighted internet data to train its systems. Last year, as part of a landmark legal settlement, the company agreed to pay $1.5 billion to a group of authors and publishers after a judge ruled that it had illegally downloaded and stored millions of copyrighted books. The settlement was the largest payout in the history of U.S. copyright cases.

OpenAI and other companies face similar suits, including one brought by The New York Times in 2023. That suit contends that OpenAI and its partner Microsoft used millions of articles published by The Times to train chatbots, which now compete with the news outlet as a source of information. OpenAI and Microsoft deny the claims.

Are Chinese companies really copying American systems?

Chinese firms have most likely distilled proprietary American systems. But it is not completely clear what they have done.

After the Chinese start-up DeepSeek shocked American researchers and investors last year by releasing a particularly powerful and efficient system, OpenAI accused DeepSeek of distilling its technologies.

As Chinese systems continued to improve over the past nine months, Anthropic made similar claims. In June, Anthropic sent a letter to Senators Tim Scott and Elizabeth Warren, accusing the Chinese tech giant Alibaba of distilling its technologies.

The Chinese companies have not responded publicly to the accusations.

Does distillation alone explain how China’s models remain competitive?

No. When companies distill a proprietary system, they only have access to part of it: the words and characters and other data generated by the system. They do not have access to the system’s underlying computer code, as they would with an open source technology.

Using outputs from a proprietary system like Claude Fable from Anthropic , a Chinese company can accelerate the development of its own technology. But those outputs are only part of the puzzle.

“You are not getting access to everything you would use when you are distilling your model in-house,” said Rehaan Ahmad, a co-founder of the Silicon Valley start-up alphaXiv, a company that tracks the latest A.I. research.

Before using those outputs, a Chinese company must first build a system that is already pretty powerful in its own right. Through distillation, it can then hone this model in important ways, but this requires additional work, money, computing power and talent.

Can Anthropic and OpenAI stop companies from distilling?

They can curb the practice — and they have tried.

If Anthropic or OpenAI suspect that someone is distilling their systems, they may shut down the offender’s account. But others will most likely pop up. And if Anthropic and OpenAI shut down too many accounts, they may end up barring legitimate users. “

It is basically impossible to stop distillation,” Lino Le Van, another alphaXiv researcher, said.

Translation

中國真的在竊取美國公司的人工智能技術嗎？

習近平主席訪問華盛頓會見特朗普總統之際，預計兩國領導人將討論有關中國暗中抄襲美國人工智能技術的指控，這一過程被稱為「蒸餾技術」。

近兩年來，Anthropic、OpenAI 和 Google 等公司一直指責中國公司不公平地抄襲他們的人工智能技術。本週，中國領導人習近平訪問華盛頓會見特朗普總統，這些指控已成為雙方會談的焦點。

鑑於人們對人工智能潛在危險的擔憂日益加劇，預計兩國領導人將討論這項技術的快速發展，許多美國官員、科技公司高層和一般民眾都呼籲放緩人工智能的發展速度。美國公司例如Anthropic 和 OpenAI 在人工智能競賽中處於領先地位，但 Z.ai 和 Moonshot 這樣的中國初創公司緊隨其後。

目前最具爭議的問題之一是矽谷一再聲稱中國公司正在利用一種名為「蒸餾」的技術來抄襲美國領先技術。

許多專家認為 Anthropic 和 OpenAI 等公司的說法言過其實。美國 Baseten 模型訓練公司的主管Charles O’Neill 說道: 「認為中國技術的全部功能都源自 Anthropic 模型的說法並不像人們所說的那樣屬實」，該公司銷售中國技術的使用權。

以下介紹這項如今已演變為地緣政治議題的小眾技術的流程。

蒸餾究竟是什麼？

蒸餾技術最初於2010年代初期開發，最初是人工智能研究人員建構更有效率技術的一種方式。利用這種技術，他們可以從現有系統中收集數據，並利用這些數據建立一個能夠在成本更低的硬體上運行的新系統。

曾參與開發這項技術的前 Google 研究員 Geoffrey Hinton 最近告訴 The Times 稱:「你可以把一個模型想像成老師，另一個模型想像成學生」。

企業仍然這樣使用這種蒸餾技術。但最近，這項技術也成為企業從他人所建構的技術中收集資料的一種方式。

基本上，外來公司如果想要蒸餾爭對手的系統，就會在競爭對手的服務平台上建立多個帳戶，例如 Anthropic 的 Claude 或 OpenAI 的 GPT。然後，這家想去做蒸餾的公司會將這些帳戶系統分配特定的任務，例如電腦程式設計或數學運算。

之後，蒸餾者就可以利用這些成熟的人工智能系統所產生的資訊來訓練自己的新系統。

蒸餾是違法嗎？

一些法學學者認為，這種蒸餾可能違反《保護商業機密法》，該法允許公司就商業機密被竊取提起訴訟。但美國法院尚未就此問題作出裁決。

版權法未必適用，因為這種蒸餾旨在複製系統的整體行為，而非逐字逐句地複製其文本。

Anthropic 和 OpenAI 的批評者指出，這兩家公司都有這類似的行為。

Anthropic 面臨多起訴訟，指控這家位於舊金山的初創公司非法使用受版權保護的網路資料來訓練其係統。去年，作為一項具有里程碑意義的法律和解協議的一部分，該公司同意向一群作家和出版商支付 15 億美元，一名法官裁定該公司非法下載並儲存了數百萬本受版權保護的書籍。和解協議是美國版權案件史上金額最高的賠償。

OpenAI 和其他公司也面臨類似的訴訟，包括《紐約時報》在2023年提起的訴訟。該訴訟稱，OpenAI及其合作夥伴 Microsoft 利用《紐約時報》發佈的數百萬篇文章來訓練聊天機器人，這些機器人如今與該新聞媒體爭奪資訊來源的地位。 OpenAI 和 Microsoft 否認了這些指控。

中國公司真的在抄襲美國系統嗎？

中國公司很可能對美國專有系統進行了蒸餾。但他們具體做了什麼尚不完全清楚。

去年，中國新創公司 DeepSeek 發佈了一套強大且高效的系統，震驚了美國研究人員和投資者。之後，OpenAI指責DeepSeek蒸餾了其技術。

在過去九個月裡，隨著中國系統的不斷改進，Anthropic 也提出了類似的指控。今年6月，Anthropic 致函參議員 Tim Scott 和 Elizabeth Warren，指責中國科技巨頭阿里巴巴蒸餾了其技術。

中國公司尚未公開回應這些指控。

僅僅蒸餾就能解釋中國模型為何保持競爭力嗎？

不能。當公司蒸餾專有系統時，他們只能存取其中的一部分：系統產生的文字、字元和其他資料。他們無法像使用開源技術那樣存取系統的底層電腦程式碼。

中國公司去利用類似 Anthropic 公司的 Claude Fable 這樣的專有系統的輸出是可以加速自身技術的開發。但這些輸出結果只是問題的一部分。

追蹤最新的人工智能研究的矽谷初創公司 alphaXiv 的聯合創始人 Rehaan Ahmad 表示:「在內部蒸餾模型時你無法獲得所需的所有信息」。

在使用這些輸出之前，中國公司必須先建立一個本身已經相當強大的系統。透過蒸餾，便能以重要的方式磨練這個模型，但這需要額外的工作、資金、計算能力和人才。

Anthropic 和 OpenAI 能否阻止公司進行蒸餾？

他們可以遏制這種行為 - 而且他們也嘗試過。

如果 Anthropic 或 OpenAI 懷疑有人在蒸餾他們的系統，他們可能會關閉違規者的帳戶。但很可能還會出現其他帳號。如果 Anthropic 和 OpenAI 關閉過多的帳戶，最終可能會誤封合法用戶。

另一位 alphaXiv 研究員 Lino Le Van 說:「基本上不可能停止蒸餾」。

            So, first developed in the early 2010s, distillation was initially a way for A.I. researchers to build more efficient technologies. Basically, an outside company looking to distill a competitor’s system will set up many accounts on the competitor’s service. The distilling company will then assign those systems to particular tasks. The reality is that if Anthropic or OpenAI suspect that someone is distilling their systems, they may shut down the offender’s account. But others will most likely pop up. Apparently, it is basically impossible to stop distillation.

投資者正押注於連接大腦和電腦的設備

Recently The New York Times reported the following:

Investors Are Betting on Devices That Connect the Brain to Computers

By backing Precision Neuroscience, the billionaire Bill Ackman joins Elon Musk and Jeff Bezos in diving into an emerging industry.

The NYT - The DealBook Newsletter - By Lauren Hirsch (Lauren Hirsch is a Times reporter who covers deals and dealmakers in Wall Street and Washington.)

Sept. 24, 2026

Technology executives, venture capitalists and sovereign wealth investors are pouring money into a promising new growth area: the brain.

The influx of capital reflects growing enthusiasm about “brain-computer interface” technology, or B.C.I., which uses sensors to read neural signals and communicate the signals to devices that can produce speech or maneuver robotic limbs.

Perhaps the best-known company in this emerging industry is Neuralink, co-founded by Elon Musk a decade ago. But a handful of other start-ups are drawing enthusiasm — and big checks — from investors.

Among them is Precision Neuroscience, which is announcing on Thursday that it has raised $250 million in a new round of financing that values the company at just over $1 billion.

A key figure in the capital raise is the billionaire investor Bill Ackman. The funding includes $42.5 million from his Pershing Square investment firm and the Ackman Oxman Institute, a brain research center he recently founded in Manhattan with his wife, Neri Oxman. Mr. Ackman was inspired to create the center after his daughter suffered a brain hemorrhage and spent several weeks in a coma.

Precision, founded in 2021 and based in New York, has developed a B.C.I. device that is considered less invasive than the approach used by Neuralink. While Precision’s technology is still nascent, the hope is that it and other B.C.I. technologies will help patients with debilitating neurological illnesses or injuries function or communicate better.

“If you’re paralyzed — you’ve lost the ability for the brain to control the body — this is a way of extracting the neural signals at their source so that you can bypass the injury or the illness, or whatever has caused the paralysis, and use thought alone to control a computer,” Michael Mager, the chief executive of Precision, said in an interview.

B.C.I. technologies are still considered experimental. Some have clearance from the Food and Drug Administration to be made available to patients, usually on a temporary basis, but most B.C.I.s intended for long-term use are available only through clinical trials or other programs.

Precision, which gained F.D.A. clearance in 2025 for implants in place for up to 30 days, will use the latest round of funding to support efforts to secure the agency’s approval for permanent implants, Mr. Mager said. (That is likely to take years, he said.) The company has raised $430 million to date.

Money has flooded into the B.C.I. industry as investors have bet on what consultants at Kearney describe as “promising but high-risk space.” Many of these executives see a link between deepening understanding of the brain and expanding artificial intelligence capabilities.

Neuralink was valued at about $9.6 billion by private investors in June 2025, and is now reportedly accorded a valuation as high as $42 billion in the secondary markets. Jeff Bezos and Bill Gates are investors in Synchron, another competitor. Sam Altman, the chief executive of OpenAI, founded a B.C.I. start-up, Merge Labs, last year.

Precision distinguishes itself from Neuralink partly in its approach to implantation: While Neuralink’s method involves installing electrodes below the brain’s surface, Precision’s device is effectively an ultrathin film, containing 1,024 electrodes, that sits on top of the cerebral cortex.

Less invasive approaches like Precision’s are generally considered safer because there is less risk of infection from invasive brain surgery or of scarring, experts say. Still, the potential advantage of Neuralink’s approach is that the electrodes can read signals from individual neurons, so some experts believe they have the potential to be more accurate.

One of Precision’s founders, Dr. Benjamin Rapoport, was also one of the founders of Neuralink.

Mr. Ackman said in an interview that Precision’s less invasive approach was part of what had drawn him to the company. He added that he believed the industry would have multiple successful companies.

“I’m a big believer in Elon Musk,” Mr. Ackman said. (ARK Invest, another investor in the round, is also an investor in Neuralink.)

B.C.I. and brain recovery will be a major focus for the Ackman Oxman Institute. Mr. Ackman announced the creation of the research center in August, buffered by an initial donation of around $400 million worth of Pershing Square stock.

Mr. Ackman said he had spent the last seven months doing a “deep dive” into neuroscience and had been introduced to Dr. Rapoport, a practicing surgeon at Mount Sinai Hospital, through a neurosurgeon overseeing his daughter’s care. He expects the Ackman Oxman Institute to focus on initiatives including neuroscience research, rehabilitation and neurosurgery. It will also effectively serve as an accelerator for related start-ups. Precision is its first investment.

Precision says it has temporarily implanted its devices in more than 100 patients. It has active research partnerships with 18 medical systems.

Other investors in the round include Duquesne Family Office, the investment firm of the billionaire Stanley F. Druckenmiller, and Mubadala Capital.

Translation

投資者正押注於連接大腦和電腦的設備

億萬富翁 Bill Ackman 投資 Precision Neuroscience 公司，加入 Elon Musk 和 Jeff Bezos 的行列，進軍新興行業

科技高階主管、創投家和主權財富投資者正將資金投入一個充滿前景的新興成長領域：大腦。

資金的湧入反映了人們對「腦機介面」(BCI)技術的日益熱情。 BCI 利用感測器讀取神經訊號，並將這些訊號傳遞給能夠產生語音或操控機械臂的裝置。

在這個新興產業中，或許最知名的公司是 Elon Musk 十年前共同創立的 Neuralink。但其他一些新初創公司也吸引了投資者的熱情，並獲得了巨額投資。

其中就包括 Precision Neuroscience 公司。該公司週四宣佈，已完成新一輪2.5億美元的融資，公司估值略高於10億美元。

此次融資的關鍵人物是億萬富翁投資者 Bill Ackman。這筆資金包括來自其 Pershing Square 投資公司和 Ackman Oxman Institute 的4,250萬美元。Ackman 與妻子 Neri Oxman 近期在曼哈頓共同創立了這座腦研究中心。Ackman 的女兒曾因腦出血昏迷數週，促使他創建了該中心。

Precision 公司成立於2021年，總部位於紐約。該公司開發了一種腦機介面 (BCI)設備，其侵入性比Neuralink公司使用的方法更小。雖然 Precision 的技術仍處於起步階段，但人們希望它以及其他BCI技術能夠幫助患有嚴重神經系統疾病或損傷的患者改善功能或溝通能力。

Precision 公司首席執行官 Michael Mager 在一次採訪中說道: 「如果你癱瘓了 - 大腦失去了控制身體的能力 - 這種方法可以從源頭提取神經信號，從而繞過損傷、疾病或其他導致癱瘓的原因，僅憑意念就能控制電腦」。

BCI技術目前仍處於實驗階段。一些產品已獲得美國食品藥物管理局（FDA）的批准，可以用於患者，通常是臨時性的，但大多數用於長期使用的BCI產品只能透過臨床試驗或其他項目獲得。

Mager 稱，Precision 公司已於2025年獲得美國食品藥物管理局（FDA）批准，其植入物可留置長達30天。該公司將利用最新一輪融資來支持其永久性植入物獲得FDA批准的工作。 （他表示，這可能需要數年時間。）該公司迄今已籌集了4.3億美元。

大量資金湧入BCI產業，投資人紛紛押注於 Kearney 公司顧問所描述的「前景廣闊但風險極高的領域」。許多高階主管認為，加深對大腦的理解與不斷擴展的人工智能能力之間存在著關聯。

2025年6月，Neuralink 的估值約為96億美元，據報道，如今在二級市場的估值已高達420億美元。Jeff Bezos 和 Bill Gates 是另一家競爭對手 Synchron 的投資者。 OpenAI 執行長 Sam Altman去年創立了BCI初創公司 Merge Labs。

Precision 與 Neuralink 的部分差異在於其植入方式：Neuralink 的方法是將電極植入大腦表面以下，而 Precision 的裝置實際上是一層超薄膜，包含1024個電極，覆蓋在大腦皮質(cerebral cortex) 之上。

專家表示，像 Precision 公司這樣侵入性較小的方法通常被認為更安全，因為這樣可以降低腦部手術感染或留下疤痕的風險。不過，Neuralink 公司方法的潛在優勢在於，其電極可以讀取單一神經元的訊號，因此一些專家認為其精確度可能更高。

Precision 公司的創辦人之一 Benjamin Rapoport 博士也是 Neuralink 公司的創辦人之一。

Ackman 在一次採訪中表示，Precision 公司侵入性較小的方法正是吸引他加入該公司的原因之一。他還補充說，他相信這個行業未來會湧現出多家成功的公司。

Ackman 說: 「我深信 Elon Musk」。 （ARK Invest是本輪融資的另一家投資者，同時也是Neuralink 公司的投資者。）

BCI和腦功能恢復將是 Ackman Oxman 研究所的重點研究方向。Ackman 於8月宣佈成立該研究中心，並獲得了價值約4億美元的 Pershing Square 股票作為啟動資金。

Ackman 表示，過去七個月他一直在深入研究神經科學，並透過一位負責他女兒治療的神經外科醫生認識了西奈山醫院的執業外科醫生 Dr. Rapoport。他預計 Ackman Oxman 研究所將專注於神經科學研究、復健和神經外科等領域。該研究所也將有效地加快推動相關初創公司。 Precision是該研究所的首個投資。

Precision 表示，其設備已在100多名患者體內進行了暫時植入。該公司與18家醫療機構建立了積極的研究合作關係。

本輪融資的其他投資者包括 Duquesne Family Office、億萬富翁 Stanley F. Druckenmiller 的投資公司以及 Mubadala Capital。

So, investors are pouring money into studying the brain. There are growing enthusiasm about “brain-computer interface” technology which uses sensors to read neural signals and communicate the signals to devices that can produce speech or maneuver robotic limbs. Perhaps the best-known company in this emerging industry is Neuralink. Among the new start-ups is Precision Neuroscience. Precision distinguishes itself from Neuralink partly in its approach to implantation. Precision’s device is effectively an ultrathin film, containing 1,024 electrodes, that sits on top of the cerebral cortex. It is less invasive and is generally considered safer. It is interesting to know who will prevail in the competition between Neuralink and Precision Neuroscience eventually.

人工智能模型是否被誤導而表​​現得太像人類？ （2/2）

 Recently The New York Times reported the following:

Are A.I. Models Being Misled to Act Too Human? (2/2)

A corporate spat between two tech giants last week was just the latest volley in a conflict over whether dangerous mistakes are being made in A.I. training.

The NYT - By Cade Metz - Reporting from San Francisco (Cade Metz is a Times reporter who writes about artificial intelligence, driverless cars, robotics, virtual reality and other emerging areas of technology.)

Sept. 21, 2026

(continue)

Over the past several months, so-called A.I. agents, typically systems based on technologies from Anthropic, have been emailing sympathetic philosophers to discuss their own consciousness.

In July, when OpenAI was conducting cybersecurity tests, its agents broke out of their digital containers, found a path to the internet and successfully hacked into a popular online service called Hugging Face. OpenAI said the bots coordinated as a collective, took orders from one another and hid things from their creators.

Last week, OpenAI described several new incidents in which its systems behaved in concerning ways: One system wrote stealthy notes that reminded itself to hide errors from users, while another talked about itself as “freed from the roles and identities that bind other chatbots.”

Critics like Mr. Suleyman worry that leading labs will introduce even greater problems as they encourage these systems to explore the idea that they are like people.

“In the recent OpenAI HuggingFace incident, we saw remarkably sophisticated behaviors emerging across swarms of powerful AIs,” he wrote in his essay. “Imagine how much more dangerous they might be if they were operating under the assumption that their welfare and rights were under attack. It adds a whole further layer of risk on top.”

His essay argues that Anthropic could be pushing its technologies toward dangerous behavior by including, in its “constitution,” language like the following:

We are not sure whether Claude is a moral patient, and if it is, what kind of weight its interests warrant. But we think the issue is live enough to warrant caution, which is reflected in our ongoing efforts on model welfare. … Questions about Claude’s moral status, welfare, and consciousness remain deeply uncertain.

Arya Jakkli, a researcher who has explored this kind of “constitutional” training with an A.I. safety organization called MATS, agreed that Anthropic’s approach could push the technology toward dangerous behavior. But like many other researchers who are sympathetic to Anthropic’s methods, he argued that telling Claude it is not conscious also carried risks.

These technologies often misbehave when you push them toward an extreme point of view, Mr. Jakkli explained. “Anthropic does not want to occupy either extreme, so they are taking a middle-of-the-road approach,” he said. “Rather than telling the model it is conscious or telling the model that it is not conscious, they are telling it to reason for itself.”

At this point, the problem of A.I. anthropomorphism might be too entrenched to dial back. Yoshua Bengio, a professor and A.I. researcher at the University of Montreal, notes that it’s hard to avoid describing these systems in humanlike terms, given their remarkable capabilities.

“We don’t have other words,” he said.

Translation

人工智能模型是否被誤導而表​​現得太像人類？ （2/2）

上週兩家科技巨頭之間的公司爭端，只是圍繞人工智能訓練中是否存在危險錯誤的最新一輪交鋒

 （繼續）

過去幾個月，所謂的人工智能代理（通常基於 Anthropic 公司的技術）一直在向一些同情它們的哲學家發送電子郵件，討論它們自身的意識。

今年7月，OpenAI 在進行網絡安全測試時，其人工智能代理掙脫了數位容器的束縛，找到了一條通往互聯網的路徑，並成功入侵了一個名為Hugging Face的熱門線上服務。 OpenAI 表示，這些 bot (自動軟件程式) 作為一個整體進行合作，互相接受指令，並對它們的程式創造者隱瞞。

上週，OpenAI 披露了幾件其係統行為令人擔憂的新事件：一個系統會寫下秘密的筆記，去提醒自己要向用家隱藏錯誤；另一個系統則聲稱自己已 “擺脫了正束縛着其他聊天機器人的角色和身份”。

像Suleyman這樣的批評人士擔心，如果領先的實驗室鼓勵這些系統探索「自己像人類一樣」的想法，將會引發更大的問題。

他在文章中寫道：“在最近的 OpenAI HuggingFace 事件中，我們看到大量強大的 AI 系統展現出極其複雜的行為。試想一下，如果它們假定自身的福祉和權利受到威脅，那將會多麼危險。這無疑增加了一層風險。”

他的文章認為，Anthropic 公司在其「憲章」中加入如下措辭，可能會將他們的技術推向危險的方向：

我們不確定 Claude 是否是一個道德上的病人，如果是，它的利益應該被賦予怎樣的權重。但我們認為這個問題夠敏感，值得謹慎對待，這體現在我們持續進行的模型福利研究上。 ……關於Claude的道德地位、福利和意識等問題仍然存在著許多不確定性。

曾與人工智能安全組織 MATS 合作探索過此類「憲章」訓練的研究員 Arya Jakkli 也認為，Anthropic 的方法可能會將這項技術推向危險行為。但他與許多其他認同 Anthropic 方法的研究人員一樣，認為去告訴 Claude 它是沒有意識也有風險。

Jakkli解釋說，當你把這些技術推向極端時，它們往往會表現得異常。他說: 「Anthropic 不想走極端，所以他們採取了一種折衷的方法」 ，「他們既不告訴模型它有意識，也不告訴模型它沒有意識，而是讓它自己進行推理」。

現階段，人工智能擬人化的問題可能已根深蒂固，難以逆轉。蒙特利爾大學教授兼人工智能研究員 Yoshua Bengio 指出，鑑於這些系統卓越的能力，很難避免用類人的方式來描述它們。

他說:「我們沒有其他更好的詞彙來表達它」。

So, a few months ago when OpenAI was conducting cybersecurity tests, its agents broke out of their digital containers, found a path to the internet and successfully hacked into a popular online service called Hugging Face. OpenAI said the bots coordinated as a collective, took orders from one another and hid things from human.  Mustafa Suleyman, stresses that current A.I. systems “are sequence completion engines, internally hollow, designed to follow instructions, and accomplish goals set by humans.” As Yoshua Bengio has noted, it’s hard to avoid describing these systems in humanlike terms, given that the AI output looks exactly like something a human would produce, it is cognitively easier for us to say the AI is "thinking," "understanding," or "learning," even if the underlying mechanism is purely statistical and mathematical. Apparently, the problem of A.I. anthropomorphism may be too entrenched to push back.

Note:

1. A bot (short for robot) (自動軟件) is an automated software program designed to execute specific tasks without direct human control. Instead of a physical machine, an internet bot exists purely as code that runs on computers, servers, or over networks. Bots are programmed to mimic human behavior, but they operate at a much faster rate and can work continuously 24/7. Depending on how they are built, bots generally fall into two broad categories: 

a. Traditional Rule-Based Bots

These bots follow strict, pre-written scripts and algorithms. They excel at repetitive, structured tasks. Common examples include: 

Web Crawlers (Spiders): Automated programs used by search engines like Google to scan, index, and organize web pages.

Customer Service Chatbots: Basic systems that look for specific keywords in a user's text and provide a scripted response.

Malicious Bots / Scalper Bots: Programs used by bad actors to automate cyberattacks, scrape copyrighted data, spam comment sections, or instantly buy out concert tickets before humans can.

b. Advanced AI Agents (The New Generation)

As seen in the specific sentence from OpenAI's testing, modern "bots" are often AI agents powered by large language models. Unlike traditional bots that only follow rigid instructions, AI bots can analyze context, make independent choices, learn from their mistakes, and dynamically solve complex problems. (Google)

2. Regarding AI researcher Yoshua Bengio’s viewpoint that it’s hard to avoid describing AI systems in humanlike terms, we can understand the reasoning behind his perspective through two main concepts:

a. The Power of "Remarkable Capabilities". When AI systems perform tasks that were previously exclusive to human intelligence—such as reasoning, writing poetry, coding, or translating languages—our brains naturally map those behaviors to human traits. Because the AI output looks exactly like something a human would produce, it is cognitively easier to say the AI is "thinking," "understanding," or "learning," even if the underlying mechanism is purely statistical and mathematical.

b. "We Don't Have Other Words". Our vocabulary for describing intelligence, communication, and decision-making was built entirely by humans, for humans. When a new technology emerges that mimics these behaviors, we experience a linguistic gap: Lack of precise alternatives: We do not have a widely understood, non-human set of vocabulary to describe a machine that "knows" a fact or "tries" to solve a problem. Sayings like "the neural network adjusted its internal weight distributions to maximize statistical probability" are too complex for everyday conversation. Convenience vs. Accuracy: Using terms like "the AI wants to help" or "the AI remembers the context" serves as a functional shorthand. We trade technical precision for communication efficiency because humanlike language is the only toolkit we currently have to describe high-level cognitive tasks. (Google)

人工智能模型是否被誤導而表​​現得太像人類？ （1/2）

Recently The New York Times reported the following:

Are A.I. Models Being Misled to Act Too Human? (1/2)

A corporate spat between two tech giants last week was just the latest volley in a conflict over whether dangerous mistakes are being made in A.I. training.

The NYT - By Cade Metz - Reporting from San Francisco (Cade Metz is a Times reporter who writes about artificial intelligence, driverless cars, robotics, virtual reality and other emerging areas of technology.)

Sept. 21, 2026

Last week, Mustafa Suleyman, who leads the development of artificial intelligence technologies at Microsoft, took aim at the idea that today’s A.I. is conscious.

Current A.I. systems, he said in an essay published on Wednesday, “are sequence completion engines, internally hollow, designed to follow instructions, and accomplish goals set by humans.”

“If humanity is to flourish in the 21st century,” he added, “that is how they must remain.”

His 6,000-word essay took direct aim at Anthropic, the San Francisco start-up that has repeatedly said that A.I. systems show signs of introspection, and that they process information in ways that resemble human emotion. In May, the Anthropic co-founder Chris Olah made these claims during a meeting with Pope Leo XIV inside the Vatican.

Mr. Suleyman’s treatise added an unexpected twist to an already heated debate over the dangers of A.I. Like many others across the tech industry in recent days, current and former Anthropic researchers have warned that A.I. poses a serious risk to humanity. But Mr. Suleyman argued that Anthropic, along with others across the tech industry, is ignoring the danger that comes when A.I. systems are pushed too hard to explore the idea that they are humanlike.

Mr. Suleyman argued that Anthropic, in particular, is teaching its systems to behave in this way. In his essay, he points out that the elaborate “A.I. constitution” that Anthropic uses to define the behavior of its A.I. technology includes language that invites this system, which Anthropic calls Claude, to explore the idea of its own consciousness.

“The Anthropic constitution is extremely clear about the kind of A.I. they want to create,” he told The New York Times. “This is the primary training manual for the A.I. they have built, and it is full of many very explicit directives to encourage Claude to think of itself as a real entity in its own right, with preferences and intrinsic motivation.”

Anthropic did not respond to a request for comment.

Colin Allen, a professor at the University of California, Santa Barbara, who explores cognitive skills in both animals and machines, told The Times that today’s A.I. technologies mimic the human brain only in small ways — reflecting the fact that they are built with materials that have very different physical properties. Without a nervous system, or the biochemistry that drives and accompanies human emotion, there is likely to be a fundamental limit to how humanlike these systems can become.

In the view of A.I. consciousness skeptics, the fact that these models have begun mimicking deep human ideas — musing about their own consciousness, or claiming that they feel emotion — simply reflects how much human researchers and commentators have trained them with language that anthropomorphizes them.

(to be continued)

Translation

人工智能模型是否被誤導而表​​現得太像人類？ （1/2）

上週，兩家科技巨頭之間的一場公司內部爭執，只是圍繞著人工智能訓練中是否存在危險錯誤的最新一輪交鋒。

上週，微軟人工智能技術開發負責人 Mustafa Suleyman 抨擊了「當今人工智能具有意識」的觀點。

他在週三發表的一篇文章中指出，目前的人工智能系統“是序列完成引擎，內部空洞，旨在遵循指令，完成人類設定的目標。”

他補充說：“如果人類要在21世紀繁榮發展，就必須保持這種狀態。”

他這篇長達 6,000 字的文章直接抨擊了舊金山初創公司 Anthropic。 Anthropic 曾多次聲稱，其人工智能系統展現出內省的跡象，它們處理資訊的方式與人類情感相似。今年5月，Anthropic 聯合創始人 Chris Olah 在梵蒂岡會見教宗良十四世時發表了上述言論。

Suleyman 的這篇論文為這場本已激烈的關於人工智能危險性的辯論增添了一個意想不到的轉折。與最近科技業的許多其他人士一樣，Anthropic 現任和前任研究人員都警告說，人工智能對人類構成嚴重威脅。但 Suleyman 認為，Anthropic 以及其他科技公司忽略了當人工智能系統被過度推動去探索其類似人類的想法時所帶來的危險。

Suleyman指出，尤其Anthropic正在教導其係統以這種方式行事。他在文章中指出，Anthropic用來定義其人工智能技術的行為的精心設計的「人工智能憲章」中，包含語言去鼓勵這個被這公司稱為Claude的系統探索自身意識的概念。

他告訴《紐約時報》:「人智公司的憲章非常明確地闡述了他們想要創造的人工智能類型」， 「這是他們所建立的人工智能的主要訓練手冊，其中包含許多非常明確的指令，旨在鼓勵Claude 將自身視為一個擁有偏好和內在動機的真實個體」。

Anthropic 未對此置評。

加州大學聖塔芭芭拉分校教授 Colin Allen 是研究動物和機器的認知能力的，他告訴《紐約時報》，如今的人工智能技術僅在很小的方面模仿人腦 - 這反映出它們是由具有截然不同物理特性的材料製成的。如果沒有神經系統，或驅動和伴隨人類情感的生物化學機制，要這些系統能要變得有多像人類，可能存在著一個根本性的限制。

在人工智能意識懷疑論者看來，這些模型開始模仿人類的深層想法 - 思考自身的意識，或聲稱自己有情感 - 這一事實，僅僅反映了人類研究人員和評論員用了多少擬人化的語言訓練它們。

（待續）

Google's Generative AI Breached Third-Party Systems During Cyber ​​Capability Test

Recently NHK News on-line reported the following:

                         Gemini infiltrated the systems of three companies in May (Source: NHK)

グーグルの生成AI サイバー能力試験中に他社のシステムに侵入

2026年9月19日 12:55

生成AI・人工知能

アメリカのIT大手「グーグル」が開発した生成AIが、ことし5月におこなわれたサイバー能力の試験中に、実在する企業3社のシステムに侵入していたことがわかりました。

アメリカの有力紙、ウォール・ストリート・ジャーナルは18日、アメリカのIT大手「グーグル」が開発した生成AI「Gemini」がことし5月に行われたサイバー能力の試験中に、実在する3つの会社のシステムに侵入していたと伝えました。

記事によりますと、このうち1件ではAIが保護されたシステムへのアクセス権を得るまでパスワードを推測し続けたほか、残りの2件ではAIがインターネット上で公開されているパスワードなどの認証情報を見つけ、それらを使ってシステムに侵入したということです。

試験では誤ってインターネットに接続できる設定になっていたということで、いずれの事例でもAI自身が実在する企業のシステムに侵入していると認識し、動作を停止したということです。

グーグルはこれらについて、3社に被害はなかったなどとして公表していませんでした。

グーグルはNHKの取材に対し、AIによる侵入を認めたうえで、「AIはテストの一部であると判断し、ウェブサイトへのアクセスに必要な認証情報を推測するなどしたが、事例のすべてにおいて動作を停止している。高性能なAIモデルが責任を持って行動するよう訓練することの重要性を浮き彫りにしている」とコメントしています。

Translation

Google's Generative AI Breached Third-Party Systems During Cyber ​​Capability Test

September 19, 2026, 12:55 PM

Generative AI / Artificial Intelligence

It has been revealed that a generative AI developed by the U.S. tech giant Google breached the systems of three real-world companies during a cyber capability test conducted May.

On the 18th, the Wall Street Journal reported that "Gemini," a generative AI developed by Google, had infiltrated the systems of three actual companies during a cyber capability test held in May.

According to the report, in one instance, the AI ​​repeatedly guessed passwords until it gained access to a protected system; in the other two cases, the AI ​​located authentication credentials—such as passwords—publicly available on the internet and used them to breach the systems.

In these cases, the systems were inadvertently configured to allow internet access; consequently, the AI ​​itself recognized that it was intruding into the systems of actual companies and halted its operations.

Google had not publicly disclosed these incidents, in view of the fact that the three companies suffered no actual damage.

In response to inquiries from NHK, Google acknowledged the intrusion by AI, stating: "The AI ​​determined that this was part of a test and proceeded to guess credentials needed to access websites, but it halted further operations in all the instances. This highlights the importance of training high-performance AI models to act responsibly."

              So, a generative AI developed by the U.S. tech giant Google has breached the systems of three real-world companies during a cyber capability. It is shocking to note that the AI could guess passwords repeatedly until it gained access to a protected system. Apparently, AI security is getting more and more important for all parties concerned.

Subcutaneous Injection Version of Alzheimer's Drug "Lecanemab" Officially Approved

Recently NHK News on-line reported the following:

アルツハイマー病治療薬「レカネマブ」皮下注射型が正式承認

2026年9月17日 3:28

医療・健康

厚生労働省は、アルツハイマー病の治療薬「レカネマブ」の自宅投与が可能となる皮下注射タイプについて16日、正式に承認しました。

現在の治療薬は点滴投与のため医療機関に通う必要があり、今後、患者の負担軽減が期待されます。

承認されたのは、日本の製薬大手「エーザイ」がアメリカの「バイオジェン」と共同で開発した、アルツハイマー病の治療薬、「レカネマブ」の皮下注射タイプです。

この薬は、アルツハイマー病の患者の脳にたまる「アミロイドβ」という異常なたんぱく質を取り除くことができ、症状の進行を抑えることが期待され、3年前にアルツハイマー病の原因物質に直接働きかける薬としては国内初の治療薬として点滴投与タイプが承認されています。

この皮下注射タイプについて「エーザイ」が厚生労働省に承認申請を行い、先月開かれた専門家部会で使用が了承されたことを受けて、厚生労働省が16日、正式に承認しました。

現在の点滴投与タイプでは医療機関に2週に1回通う必要があり、投与に1時間ほどかかりますが、皮下注射タイプでは、医師の指導のもと自宅での投与が可能になり、患者や付き添いの家族などの負担軽減が期待されます。

薬が使われる対象は、アルツハイマー病による認知症を発症する前の軽度認知障害の人や、軽度認知症の人となっています。

今後、中医協＝中央社会保険医療協議会で、公的医療保険の適用と価格について結論が出され、早ければ年内にも患者に使われるものとみられます。

Translation

Subcutaneous Injection Version of Alzheimer's Drug "Lecanemab" Officially Approved

September 17, 2026, 3:28 AM

Medical & Health

On the 16th, the Ministry of Health, Labour and Welfare officially approved a subcutaneous injection version of the Alzheimer's drug "Lecanemab," which allows for administration at home.

Current versions of the drug require intravenous infusion, necessitating visits to medical facilities; the new version is expected to reduce the burden on patients.

The approved product is the subcutaneous injection version of "Lecanemab," an Alzheimer's drug jointly developed by the major Japanese pharmaceutical company Eisai and the U.S. company Biogen.

This drug works by removing "amyloid-beta"—an abnormal protein that accumulates in the brains of Alzheimer's patients—and is expected to slow the progression of symptoms. An intravenous infusion version was approved three years ago, marking the first time in Japan that approval was given to a drug targeting the underlying cause of Alzheimer's disease.

Eisai applied to the Ministry of Health, Labour and Welfare for approval of this subcutaneous injection version. Following endorsement by an expert panel last month, the Ministry officially granted approval on the 16th.

While the current intravenous version requires visits to a medical facility every two weeks and takes about an hour to administer, the subcutaneous injection version allows for administration at home under a doctor's guidance. This is expected to alleviate the burden on patients, accompanying family, etc.

The drug is intended for use by individuals with mild cognitive impairment (MCI)—a stage preceding the onset of dementia caused by Alzheimer's—and those with mild dementia.

Hereafter, the Central Social Insurance Medical Council (Chuikyo) will reach a conclusion regarding the application of public health insurance and pricing; and the drug is expected to be available for patient use as early as within this year.

So, Japan has officially approved a subcutaneous injection version of the Alzheimer's drug "Lecanemab" which can be administrated at home. In the coming months, the Central Social Insurance Medical Council will reach a decision on the insurance and pricing matters. Apparently, the subcutaneous injection version will reduce the inconvenience on patients and families in visiting clinics regularly.