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经济学人:山姆·奥尔特曼的戏剧表明科技界的更深层次分裂
There is littledoubting the dedication of Sam Altman to Openai, the firm at the forefront of an artificial-intelligence (ai) revolution. As co-founder and boss he appeared to work as tirelessly for its success as at a previous startup where his singlemindedness led to a bout of scurvy, a disease more commonly associated with mariners of a bygone era who remained too long at sea without access to fresh food. So hissudden sackingon November 17th was a shock. The reasons why the firm’s board lost confidence in Mr Altman are unclear. Rumours point to disquiet about his side-projects, and fears that he was moving too quickly to expand Openai’s commercial offerings without considering the safety implications, in a firm that has also pledged to develop the tech for the “maximal benefit of humanity”.
The company’s investors and some of its employees are now seeking Mr Altman’s reinstatement. Whether they succeed or not, it is clear that the events at Openaiare the most dramatic manifestation yet of a wider divide in Silicon Valley. On one side are the “doomers”, who believe that, left unchecked,ai poses an existential risk to humanity and hence advocate stricter regulations. Opposing them are “boomers”, who play down fears of anaiapocalypse and stress its potential to turbocharge progress. The camp that proves more influential could either encourage or stymie tighter regulations, which could in turn determine who will profit most fromaiin the future.
Openai’s corporate structure straddles the divide. Founded as a non-profit in 2015, the firm carved out a for-profit subsidiary three years later to finance its need for expensive computing capacity and brainpower in order to propel the technology forward. Satisfying the competing aims of doomers and boomers was always going to be difficult.
The split in part reflects philosophical differences. Many in the doomer camp are influenced by “effective altruism”, a movement that is concerned by the possibility ofai wiping out all of humanity. The worriers include Dario Amodei, who left OpenAI to start up Anthropic, another model-maker. Other big tech firms, including Microsoft and Amazon, are also among those worried aboutai safety.
Boomers espouse a worldview called “effective accelerationism” which counters that not only should the development ofaibe allowed to proceed unhindered, it should be speeded up. Leading the charge is Marc Andreessen, co-founder of Andreessen Horowitz, a venture-capital firm. Otheraiboffins appear to sympathise with the cause. Meta’s Yann LeCun and Andrew Ng and a slew of startups including Hugging Face and Mistralaihave argued for less restrictive regulation.
婴儿潮一代拥护一种名为“有效加速主义”的世界观,这种世界观反驳说,人工智能的发展不仅应该不受阻碍地进行,而且应该加速。领先者是风险投资公司 Andreessen Horowitz 的联合创始人马克·安德森 (Marc Andreessen)。其他人工智能专家似乎也同情这一事业。 Meta 的 Yann LeCun 和 Andrew Ng 以及包括 Hugging Face 和 Mistral ai 在内的众多初创公司都主张减少限制性监管。
Mr Altman seemed to have sympathy with both groups, publicly calling for “guardrails” to makeaisafe while simultaneously pushing Openaito develop more powerful models and launching new tools, such as an app store for users to build their own chatbots. Its largest investor, Microsoft, which has pumped over $10bn into Openai for a 49% stake without receiving any board seats in the parent company, is said to be unhappy, having found out about the sacking only minutes before Mr Altman did. If he does not return, it seems likely that Openaiwill side more firmly with the doomers.
Yet there appears to be more going on than abstract philosophy. As it happens, the two groups are also split along more commercial lines. Doomers are early movers in theairace, have deeper pockets and espouse proprietary models. Boomers, on the other hand, are more likely to be firms that are catching up, are smaller and prefer open-source software.
Start with the early winners. Openai’s Chatgptadded 100m users in just two months after its launch, closely trailed by Anthropic, founded by defectors from Openaiand now valued at $25bn. Researchers at Google wrote the original paper on large language models, software that is trained on vast quantities of data, and which underpin chatbots including Chatgpt. The firm has been churning out bigger and smarter models, as well as a chatbot called Bard.
Microsoft’s lead, meanwhile, is largely built on its big bet on Openai. Amazon plans to invest up to $4bn in Anthropic. But in tech, moving first doesn’t always guarantee success. In a market where both technology and demand are advancing rapidly, new entrants have ample opportunities to disrupt incumbents.
This may give added force to the doomers’ push for stricter rules. In testimony to America’s Congress in May Mr Altman expressed fears that the industry could “cause significant harm to the world” and urged policymakers to enact specific regulations forai. In the same month a group of 350aiscientists and tech executives, including from Openai, Anthropic and Google signed a one-line statement warning of a “risk of extinction” posed byaion a par with nuclear war and pandemics. Despite the terrifying prospects, none of the companies that backed the statement paused their own work on building more potentaimodels.
Politicians are scrambling to show that they take the risks seriously. In July President Joe Biden’s administration nudged seven leading model-makers, including Microsoft, Openai, Meta and Google, to make “voluntary commitments’‘, to have theiraiproducts inspected by experts before releasing them to the public. On November 1st the British government got a similar group to sign another non-binding agreement that allowed regulators to test theirai products for trustworthiness and harmful capabilities, such as endangering national security. Days beforehand Mr Biden issued an executive order with far more bite. It compels anyaicompany that is building models above a certain size—defined by the computing power needed by the software—to notify the government and share its safety-testing results.
Another fault line between the two groups is the future of open-sourceai.llms have been either proprietary, like the ones from Openai, Anthropic and Google, or open-source. The release in February ofllama, a model created by Meta, spurred activity in open-sourceai(see chart). Supporters argue that open-source models are safer because they are open to scrutiny. Detractors worry that making these powerfulaimodels public will allow bad actors to use them for malicious purposes.
两个群体之间的另一个分歧是开源人工智能的未来。 llms 要么是专有的(例如 Openai、Anthropic 和 Google 的),要么是开源的。 Meta 创建的模型 llama 在 2 月份发布,刺激了开源人工智能领域的活动(见图表)。支持者认为,开源模型更安全,因为它们可以接受审查。反对者担心,公开这些强大的人工智能模型会让不良行为者将它们用于恶意目的。
But the row over open source may also reflect commercial motives. Venture capitalists, for instance, are big fans of it, perhaps because they spy a way for the startups they back to catch up to the frontier, or gain free access to models. Incumbents may fear the competitive threat. A memo written by insiders at Google that was leaked in May admits that open-source models are achieving results on some tasks comparable to their proprietary cousins and cost far less to build. The memo concludes that neither Google nor Openaihas any defensive “moat” against open-source competitors.
So far regulators seem to have been receptive to the doomers’ argument. Mr Biden’s executive order could put the brakes on open-sourceai. The order’s broad definition of “dual-use” models, which can have both military or civilian purposes, imposes complex reporting requirements on the makers of such models, which may in time capture open-source models too. The extent to which these rules can be enforced today is unclear. But they could gain teeth over time, say if new laws are passed.
Not every big tech firm falls neatly on either side of the divide. The decision by Meta to open-source itsaimodels has made it an unexpected champion of startups by giving them access to a powerful model on which to build innovative products. Meta is betting that the surge in innovation prompted by open-source tools will eventually help it by generating newer forms of content that keep its users hooked and its advertisers happy. Apple is another outlier. The world’s largest tech firm is notably silent aboutai. At the launch of a new iPhone in September the company paraded numerousai-driven features without mentioning the term. When prodded, its executives lean towards extolling “machine learning”, another term forai.
并非所有大型科技公司都完全站在分歧的两边。 Meta 开源其人工智能模型的决定使其成为初创公司意想不到的冠军,因为它让初创公司能够使用强大的模型来构建创新产品。 Meta 认为,开源工具带来的创新浪潮最终将通过生成更新形式的内容来帮助它,从而让用户着迷,让广告商满意。苹果是另一个异类。这家全球最大的科技公司对人工智能尤其保持沉默。在 9 月份推出新款 iPhone 时,该公司展示了众多人工智能驱动的功能,但没有提及这个术语。当受到敦促时,其高管倾向于赞扬“机器学习”,这是人工智能的另一个术语。
That looks smart. The meltdown at Openaishows just how damaging the culture wars overaican be. But it is these wars that will shape how the technology progresses, how it is regulated—and who comes away with the spoils.■
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