All Content from Business Insider 10月24日 13:47
功能性AGI已足够改变经济和社会
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Replit首席执行官Amjad Masad认为,虽然真正的通用人工智能(AGI)可能改变文明,但“功能性AGI”已足以对经济产生颠覆性影响并重塑社会。他指出,能够从真实世界数据中学习的AI系统能够自动化大量当前工作。Masad对实现真正AGI的突破持谨慎态度,认为行业可能陷入“局部最优陷阱”,即过度优化现有技术而非寻求根本性创新。他定义功能性AGI为无需具备人类意识或推理能力,只需能从数据中学习并独立完成可验证任务的AI系统,这种AI足以大规模自动化经济领域的工作。

🚀 **功能性AGI的定义与影响**: Replit CEO Amjad Masad将“功能性AGI”定义为无需具备人类意识或推理能力,但能从真实世界数据中学习并独立完成可验证任务的AI系统。他强调,这种功能性AGI已经足够强大,能够自动化经济中的大量工作,从而对经济和社会产生深远且颠覆性的改变,而无需等待实现真正意义上的通用人工智能。

📉 **对真正AGI突破的谨慎态度**: Masad对实现能够跨领域学习和适应的“真正AGI”持谨慎甚至悲观态度。他认为,当前的AI发展可能陷入“局部最优陷阱”,即AI公司过度专注于对现有模型进行微小、有利可图的改进,而不是探索可能带来根本性突破的新路径。他推测,实现真正的通用智能可能超出当前技术迭代和行业发展所能企及的范围,甚至可能不在我们有生之年。

💡 **AI发展的现实路径**: 尽管对真正的AGI突破表示怀疑,Masad肯定了当前AI技术的巨大价值和经济效益。他认为,AI行业应该关注并利用好当前已有的“功能性AGI”能力,通过自动化各行各业的工作来实现经济转型和社会重塑。这种务实的视角,将AI的焦点从遥不可及的超智能转向了当下可实现且影响巨大的应用价值。

True AGI may be civilization-changing, but "functional AGI" is already economically transformative and enough to reshape society, said Replit CEO Amjad Masad.

Forget building a god-tier superintelligence. Replit CEO Amjad Masad said we don't need that to change the economy and society — we just need "functional AGI."

The CEO of the vibe coding startup said on an episode of the "a16z" podcast published Thursday that while Silicon Valley obsesses over true AGI, the practical version is already within reach, and it's good enough to automate massive chunks of the economy.

"We can get to like functional AGI," Masad said. He defines functional AGI as AI that doesn't need human-like consciousness or reasoning, just systems capable of learning from real-world data and completing verifiable tasks on their own.

"We'll target every sector economy and you can automate a big part of labour that way," he said. "We're on that track for sure."

Masad said he's not convinced that we'll ever reach true AGI, the kind of artificial intelligence that can learn and adapt across knowledge fields like a human mind.

While true AGI could "propel us to the next level of human civilization," Masad said he's "bearish on true AGI breakthrough because what we built is so useful and economically valuable."

Masad also said the industry might be stuck in a "local maximum trap," which means AI companies are optimizing what already works instead of reinventing the field. By chasing small, profitable improvements to today's large models, they could be missing the path to a true breakthrough.

"Maybe the general problem is actually not within our lifetimes," Masad said, referring to solving the problem of general intelligence itself. "Who knows?"

Masad did not respond to a request for comment from Business Insider.

The AGI dream is losing its shine

Masad's comments come amid renewed debate over whether AGI is even a meaningful goal.

Major AI labs still consider AGI the ultimate prize. OpenAI, Google, Meta, and Microsoft have devoted their top researchers to the same goal.

However, some experts have questioned whether LLMs can ever evolve into true general intelligence.

"Nobody with intellectual integrity should still believe that pure scaling will get us to AGI," Gary Marcus, an AI leader and best-selling author, wrote in a blog post in August. "Even some of the tech bros are waking up to the reality that 'AGI in 2027' was marketing, not reality."

The release of OpenAI's GPT-5 didn't live up to the AGI hype, either.

"This is clearly a model that is generally intelligent, although I think in the way that most of us define AGI, we're still missing something quite important, or many things quite important," OpenAI CEO Sam Altman told reporters during a press call in August before the release of GPT-5.

Other industry veterans have echoed that caution. Meta's chief AI scientist, Yann LeCun, said we may still be "decades" away from achieving AGI.

"Most interesting problems scale extremely badly," LeCun said at the National University of Singapore in April. "You cannot just assume that more data and more compute means smarter AI."

Read the original article on Business Insider

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