The Download: AI’s extinction risk and bioweapons threat

《下载》：人工智能的灭绝风险与生物武器威胁

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. 这是我们工作日时事通讯《下载》的今日版，为您提供每日科技界动态。

Could AI really kill us all? Your questions, answered

人工智能真的会毁灭人类吗？为您解答疑问

On Wednesday, MIT Technology Review hosted a live Roundtables event that asked the question many seem to be asking right now: could AI really kill us all? But attendees had more questions than we had time to answer, so we asked senior AI editor Will Douglas Heaven and AI reporter Grace Huckins to tackle some of the best ones. The questions they tried to answer include: am I going to die? Why should AI kill us, if at all? Is AI really dangerous, or is it just tech companies drumming up PR? And what steps can be taken to make sure AI is controlled, monitored and regulated effectively? Here are their responses. —Will Douglas Heaven and Grace Huckins 周三，《麻省理工科技评论》举办了一场圆桌直播活动，探讨了当下许多人都在问的问题：人工智能真的会毁灭人类吗？由于参与者提出的问题超出了我们的解答时间，我们邀请了资深人工智能编辑 Will Douglas Heaven 和人工智能记者 Grace Huckins 来回答其中一些最精彩的问题。他们试图解答的问题包括：我会死吗？如果人工智能会毁灭人类，原因是什么？人工智能真的危险吗，还是科技公司在炒作公关？以及可以采取哪些措施来确保人工智能得到有效的控制、监测和监管？以下是他们的回应。——Will Douglas Heaven 和 Grace Huckins

The specter of AI-enabled bioweapons is a wake-up call for biotech

人工智能驱动的生物武器阴影为生物技术敲响了警钟

One of the ways AI could potentially cause catastrophic harm is by aiding the design and creation of bioweapons. In 2022, researchers found that it was remarkably easy to do this with an AI “molecule generator” built to develop drugs. In less than six hours, the model generated 40,000 molecules that could serve as chemical warfare agents. Today, AI tools can answer questions on almost every area of science, while advances in gene editing and synthetic biology have made biotech tools more accessible. There are safeguards, but none are ironclad. However, scientists disagree about how serious the risk is anyway. Find out why it’s easier than ever to design killer pathogens. —Jessica Hamzelou 人工智能可能造成灾难性伤害的途径之一，是辅助设计和制造生物武器。2022 年，研究人员发现，利用为药物研发而构建的人工智能“分子生成器”来做这件事非常容易。在不到六个小时内，该模型生成了 40,000 种可用作化学战剂的分子。如今，人工智能工具可以回答几乎所有科学领域的问题，而基因编辑和合成生物学的进步使得生物技术工具变得更加普及。虽然存在保障措施，但没有一个是万无一失的。然而，科学家们对于风险的严重程度仍存在分歧。了解为什么设计致命病原体变得比以往任何时候都更容易。——Jessica Hamzelou

The role of the astronaut is in flux

宇航员的角色正在发生变化

We go to space for geopolitical prestige, manifest destiny, spiritual fulfillment, scientific curiosity, and, increasingly, business opportunities. In the wake of Artemis II, a slew of new books suggest that these justifications are subsumed by one unifying fact: humans have itchy feet, and we are simply wired to roam. In The Ultraview Effect, space anthropologist Deana L. Weibel frames human space exploration as part of our need to embark on pilgrimages. In A Heart for Space, civilian astronaut Eiman Jahangir recounts one such voyage with Blue Origin. And in Dinner with an Astronaut, former NASA astronaut Leroy Chiao argues that people simply “need to know what’s on the other side.” See what these three new books have to say about why we go to space. —Becky Ferreira 我们进入太空是为了地缘政治声望、天命论、精神满足、科学好奇心，以及日益增长的商业机会。在“阿尔忒弥斯 2 号”任务之后，一系列新书表明，这些理由都被一个统一的事实所涵盖：人类天生好动，我们注定要四处漫游。在《超视效应》（The Ultraview Effect）一书中，太空人类学家 Deana L. Weibel 将人类太空探索视为我们踏上朝圣之旅需求的一部分。在《太空之心》（A Heart for Space）中，平民宇航员 Eiman Jahangir 讲述了他与蓝色起源公司的一次太空之旅。而在《与宇航员共进晚餐》（Dinner with an Astronaut）中，前 NASA 宇航员 Leroy Chiao 认为，人们只是“需要知道另一边有什么”。看看这三本新书对我们为何进入太空有何见解。——Becky Ferreira

The must-reads

必读内容

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 我已梳理了互联网，为您找出今天关于科技最有趣、最重要、最可怕和最引人入胜的故事。

1. Microsoft and OpenAI workers say AI is destroying the web 微软和 OpenAI 的员工称人工智能正在摧毁网络

   • Cannibalizing clicks from websites obliterates the business models that keep fresh content coming. (404 Media)
   • 蚕食网站点击量摧毁了维持新鲜内容产出的商业模式。（404 Media）
   • The employees showed concern that publishers couldn’t survive AI scraping. (NYT)
   • 员工们担心出版商无法在人工智能抓取中生存。（《纽约时报》）
   • The comments emerged during the NYT’s copyright case. (WP)
   • 这些评论出现在《纽约时报》的版权诉讼期间。（《华盛顿邮报》）
   • They could weaken OpenAI and Microsoft’s defense. (Reuters)
   • 这可能会削弱 OpenAI 和微软的辩护。（路透社）
   • AI means the end of internet search as we’ve known it. (MIT Technology Review)
   • 人工智能意味着我们所熟知的互联网搜索时代的终结。（《麻省理工科技评论》）

2. Robot boats have fought each other for the first time 机器人船只首次在战斗中交火

   • A Ukrainian vessel sank a Russian one in combat. (New Scientist)
   • 一艘乌克兰船只在战斗中击沉了一艘俄罗斯船只。（《新科学家》）
   • US firms are building combat-ready humanoids. (WSJ)
   • 美国公司正在制造具备战斗能力的人形机器人。（《华尔街日报》）

3. Security researchers breached OpenAI using Anthropic’s tools 安全研究人员利用 Anthropic 的工具入侵了 OpenAI

   • They reached an employee’s ChatGPT account and internal code. (FT)
   • 他们访问了一名员工的 ChatGPT 账户和内部代码。（《金融时报》）
   • They exploited a third-party forum to reach internal systems. (WSJ)
   • 他们利用第三方论坛进入了内部系统。（《华尔街日报》）

4. OpenAI reportedly expects to soon crack another famous math problem 据报道，OpenAI 预计很快将攻克另一个著名的数学难题

   • But can it avoid another backlash when announcing it? (Information)
   • 但在宣布时，它能避免再次引发强烈抵制吗？（Information）
   • The problem it expects to solve is the Hodge Conjecture. (Gizmodo)
   • 它预计解决的问题是霍奇猜想。（Gizmodo）
   • OpenAI’s math controversies contain concerning clues about the field’s future. (MIT Technology Review)
   • OpenAI 的数学争议中包含着关于该领域未来的令人担忧的线索。（《麻省理工科技评论》）

5. Elon Musk’s SpaceXAI wants to buy data from failed startups 埃隆·马斯克的 xAI 想要购买倒闭初创公司的数据

   • It’s seeking new sources of training data for Grok. (Bloomberg)
   • 它正在为 Grok 寻找新的训练数据来源。（彭博社）
   • And it’s targeting customer and operational data. (Gizmodo)
   • 并且它的目标是客户和运营数据。（Gizmodo）
   • OpenAI is paying to create new biology data. (MIT Technology Review)
   • OpenAI 正在付费创建新的生物学数据。（《麻省理工科技评论》）

6. Schools are pushing back against Big Tech’s classroom takeover 学校正在抵制大型科技公司对课堂的接管

   • AI is accelerating concerns about corporate influence. (New Yorker)
   • 人工智能加剧了人们对企业影响力的担忧。（《纽约客》）
   • We need smarter AI use in schools. (MIT Technology Review)
   • 我们需要在学校中更明智地使用人工智能。（《麻省理工科技评论》）

7. Hackers have revealed how Flock cameras track cars—and people 黑客揭露了 Flock 摄像头如何追踪汽车和行人

   • One camera captured 1.6 million images of 50,000 vehicles. (Wired)
   • 一台摄像头拍摄了 50,000 辆车的 160 万张图像。（《连线》）
   • The cameras also detect people and misidentify objects. (404 Media)
   • 这些摄像头还会检测行人并误识别物体。（404 Media）

8. Chinese firms doubled down on science after US tech restrictions 在美国技术限制后，中国公司加倍投入科学研究

   • They produced 72% more patents citing scientific papers. (Nature)
   • 引用科学论文的专利数量增加了 72%。（《自然》）

9. A three-year-old’s cancer disappeared after an experimental cell therapy 一名三岁儿童的癌症在接受实验性细胞疗法后消失了

   • CAR T therapy may finally be able to treat solid tumors. (Gizmodo)
   • CAR-T 疗法可能终于能够治疗实体瘤了。（Gizmodo）

10. NYC’s new robotoilets will kick you out after 10 minutes 纽约市的新型机器人厕所会在 10 分钟后把你赶出来

    • The doors automatically open when the timer runs out. (Fast Company)
    • 定时器到期时门会自动打开。（Fast Company）

Quote of the day

今日名言

“The largest theft of labor in human history.” “人类历史上最大规模的劳动窃取。” —Microsoft’s director of Applied Science, Brent Hecht, raises his concerns over training data used for AI systems in comments revealed in court filings from the New York Times vs OpenAI copyright lawsuit. ——微软应用科学总监 Brent Hecht 在《纽约时报》诉 OpenAI 版权诉讼的法庭文件中披露的评论中，表达了他对人工智能系统所用训练数据的担忧。

One more thing

最后一件事

The Vera C. Rubin Observatory is ready to transform our understanding of the cosmos. High atop Chile’s 2,700-meter Cerro Pachón, the air is clear and dry, leaving few clouds to block the beautiful view of the stars. It’s here that the Vera C. Rubin Observatory is using a car-size 3,200-megapixel digital camera—the largest ever built—to produce a new map of the entire night sky every three days. Generating 20 terabytes of data per night, Rubin will capture fine details about the solar system, the Milky Way and the large-scale structure of the cosmos. Over 10 years, it will catalogue billions of new objects, offering an unprecedented look at what’s changing in the universe. 薇拉·鲁宾天文台（Vera C. Rubin Observatory）已准备好改变我们对宇宙的理解。在智利海拔 2,700 米的帕琼山（Cerro Pachón）顶峰，空气清澈干燥，几乎没有云层遮挡美丽的星空。正是在这里，薇拉·鲁宾天文台正在使用一台汽车大小、32 亿像素的数码相机——这是有史以来建造的最大的相机——每三天绘制一张全新的全夜空地图。鲁宾天文台每晚产生 20 TB 的数据，将捕捉太阳系、银河系和宇宙大尺度结构的精细细节。在 10 年的时间里，它将编目数十亿个新天体，为我们提供前所未有的视角，观察宇宙中正在发生的变化。