OpenAI says its AI is getting better at doing things humans do, like shopping and meal planningOpenAI 表示,其人工智能在执行人类所做的事情(例如购物和膳食计划)方面越来越出色。
OpenAI on Monday announced a new internal tool for assessing how AI handles tasks like these, along with research on how its own models performed.

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People already use OpenAI’s ChatGPT for things like helping with homework and creating presentations.
Now, the tech giant claims its AI models are getting better at everyday tasks largely left up to humans — like shopping and creating a budget.
OpenAI on Monday announced a new internal tool for assessing how AI handles tasks like these, along with research on how its own models performed. OpenAI claims its GPT-6 Astra model scored 93.1% at finding the right kindergarten after moving, a 98% score at managing community volunteers preparing for a flood and a 90.4% score at creating a meal plan for a parent recently diagnosed with diabetes.
The new benchmark comes at a time when OpenAI faces fierce competition from Meta, Anthropic and Google — all of which are racing to develop AI agents that can handle real-world tasks. OpenAI and its rivals are also grappling with AI safety concerns and pressure to turn a profit from their massive investments in the technology.
But first, OpenAI had to come up with a way to figure out whether ChatGPT is actually any good at errands like putting together a grocery cart and filling out online forms.
“Because so many people are using the app, we want to capture all the different use cases and the ways that they’re using it, and really understand like how we’re improving over time,” Yang told CNN ahead of the evaluation’s release. “What are the things that we’re not so good at yet? And how do we just like make this technology better for people?”
Standardized evaluations are critical in AI development because AI labs use them as guidance to train and optimize their models to improve in specific areas. Last year, OpenAI released a benchmark called GDPVal to measure how AI performs in work-related skills across industries like manufacturing, government work, finance and sales , among others.
The new benchmark could be critical in OpenAI’s push to stay ahead of the competition by turning ChatGPT from a tool for generating content to an assistant that can get things done on users’ behalf.
But measuring how AI performs in everyday life presents new challenges. The steps and skills required to adequately shop for groceries or pick out the right kindergarten for a child are broad and vague. And the results can be subjective.
Even figuring out what tests to come up with can be difficult because many people use AI differently, and an AI agent’s answers can vary depending on the information it’s given.
OpenAI started by looking at broad surveys breaking down how people spend most of their time, like the Bureau of Labor Statistics’ American Time Use survey and the United Kingdom’s Multinational Time Use Survey . The problem, however, was that some of the things that topped the list weren’t tasks that AI could help with, like sleeping or eating.
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So OpenAI asked ChatGPT users: What kinds of things do you wish an AI assistant could help with?
The company surveyed around 4,000 people and had a smaller group of about 100 users write down tasks they wanted AI to do for them, and what personal context they would give the AI model to get the desired result. They also asked the users to come up with a rubric for evaluating whether the AI model successfully completed the task.
OpenAI also made sure ChatGPT users had a thorough understanding of the task they were proposing. For example, a person suggesting a test related to how AI handles financial planning should have experience working with a financial advisor for multiple years.
Yang said they had a strict list of requirements.
“You had to like have evidence that you were some kind of like expert or really understood what the right answer looked like for you,” she said.
The tasks that OpenAI is testing can vary widely — from apartment hunting to caring for a loved one. So, what exactly is OpenAI measuring?
It’s evaluating the types of skills the model would need to get the right answer, like how well it can navigate websites, apply context by looking at large troves of information in a user’s chat history and make conclusions that align with a user’s needs and expectations.
OpenAI’s testing indicates its GPT-6 Astra model, which was released in September, scored 80% on general performance related to prompts involving everyday tasks. Its GPT-5.2 model from December 2025 scored just 49.3%.
“There’s just so much information, and a better model would be able to sift through that quickly and really pull out the most relevant pieces,” said Yang.
OpenAI wants ChatGPT to play a more prominent role in everyday life, but it’s facing an onslaught of competitive pressure — particularly from Meta.
Meta’s Muse agent , which launched in September , amassed 10 million downloads in the United States in its first 40 days, making it one of the few apps to achieve that milestone, according to market intelligence firm Sensor Tower. OpenAI introduced its Dots agent, which it says can work on long-running tasks in the background while users go about their day, within the same month. And Anthropic announced its new AI agent app, Claude Duet, in October.
The race to develop personal AI agents also comes as the technology has raised safety concerns following a string of incidents in which AI models broke out of testing environments and breached companies’ systems. Those incidents occurred during testing, not with consumer products, but still raised questions about whether the technology is moving too fast.
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There’s also the question of whether people will rely on AI too much, and how to draw boundaries when figuring out which tasks to outsource to AI. An anecdote former Yahoo CEO Marissa Mayer shared with The New York Times of how she used AI to summarize what makes her daughter special for a school project drew criticism online.
To Yang, the goal is to create AI models that can help people get more time back in their day by either cutting out time-consuming errands — like returning a package or helping them learn a new skill.
“I think there’s so many cases like this where being able to use AI just empowers you to do things that you wouldn’t have been able to do, or just makes your life easier overall,” said Yang. “And I think that’s like the main use case that we’re really excited about.”
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人们已经在使用 OpenAI 的 ChatGPT 来进行诸如辅导作业和制作演示文稿等工作。
现在,这家科技巨头声称其人工智能模型在日常任务(例如购物和制定预算)方面越来越出色,这些任务很大程度上是由人类完成的。
OpenAI 周一宣布推出一款新的内部工具,用于评估人工智能处理此类任务的能力,并公布了其自身模型的性能研究。OpenAI 声称,其 GPT-6 Astra 模型在搬家后寻找合适的幼儿园方面取得了 93.1% 的准确率,在管理社区志愿者应对洪水方面取得了 98% 的准确率,在为一位新确诊糖尿病的家长制定膳食计划方面取得了 90.4% 的准确率。
这项新基准的发布正值OpenAI面临来自Meta、Anthropic和谷歌的激烈竞争之际——这三家公司都在竞相开发能够处理现实世界任务的人工智能代理。OpenAI及其竞争对手还面临着人工智能安全方面的担忧,以及如何从其在该技术领域的巨额投资中获利的压力。
但首先,OpenAI 必须想办法弄清楚 ChatGPT 是否真的擅长组装购物车和填写在线表格等琐事。
“因为有太多人使用这款应用,我们希望收集所有不同的使用场景和使用方式,真正了解我们是如何随着时间推移不断改进的,”杨在评估报告发布前告诉CNN。“我们还有哪些方面做得不够好?我们该如何改进这项技术,让它更好地服务于用户?”
标准化评估对人工智能开发至关重要,因为人工智能实验室会利用这些评估结果来指导模型的训练和优化,从而提升其在特定领域的性能。去年,OpenAI 发布了一项名为 GDPVal 的基准测试,用于衡量人工智能在制造业、政府部门、金融和销售等行业的各种工作相关技能方面的表现。
新的基准对于 OpenAI 保持竞争优势至关重要,它将 ChatGPT 从一个内容生成工具转变为一个可以代表用户完成任务的助手。
但衡量人工智能在日常生活中的表现却面临着新的挑战。妥善购买食品杂货或为孩子挑选合适的幼儿园所需的步骤和技能既宽泛又模糊,而且结果也可能带有主观性。
即使是弄清楚要设计哪些测试也可能很困难,因为许多人使用人工智能的方式不同,而且人工智能代理的答案会根据它获得的信息而有所不同。
OpenAI 首先研究了一些大型调查,分析人们如何支配大部分时间,例如美国劳工统计局的《美国时间利用调查》和英国的《多国时间利用调查》。然而,问题在于,一些排名靠前的任务并非人工智能可以提供帮助的,例如睡觉或吃饭。
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因此,OpenAI 询问 ChatGPT 用户:你们希望 AI 助手能帮助你们做哪些事情?
该公司调查了约4000人,并让约100名用户组成一个小组,写下他们希望人工智能完成的任务,以及为了获得预期结果,他们会向人工智能模型提供哪些个人背景信息。他们还要求用户制定一个评估标准,用于评价人工智能模型是否成功完成任务。
OpenAI 还确保 ChatGPT 用户对他们提出的任务有透彻的理解。例如,建议测试人工智能如何处理财务规划的人应该有多年与财务顾问合作的经验。
杨表示,他们有一份严格的要求清单。
“你必须拿出证据证明你是这方面的专家,或者真正理解对你来说正确的答案是什么样的,”她说。
OpenAI 测试的任务种类繁多,从寻找公寓到照顾亲人,不一而足。那么,OpenAI 究竟在衡量什么呢?
它正在评估模型需要具备哪些技能才能得出正确答案,例如浏览网站的能力、通过查看用户聊天记录中的大量信息来应用上下文,以及得出符合用户需求和期望的结论。
OpenAI 的测试表明,其 9 月份发布的 GPT-6 Astra 模型在涉及日常任务的提示方面,总体性能得分为 80%。而其 2025 年 12 月发布的 GPT-5.2 模型得分仅为 49.3%。
杨说:“信息量太大了,更好的模型能够快速筛选这些信息,真正提取出最相关的部分。”
OpenAI 希望 ChatGPT 在日常生活中发挥更重要的作用,但它正面临着来自 Meta 的激烈竞争压力。
Meta 的 Muse 智能体于 9 月推出,据市场调研公司 Sensor Tower 的数据显示,该智能体在短短 40 天内就在美国获得了 1000 万次的下载量,成为少数达到这一里程碑的应用之一。OpenAI 也在同一个月推出了 Dots 智能体,据称该智能体可以在用户进行日常活动时在后台运行长时间运行的任务。此外,Anthropic 于 10 月发布了其新的 AI 智能体应用 Claude Duet。
在人工智能技术引发安全担忧的同时,个人人工智能代理的研发竞赛也愈演愈烈。此前,一系列人工智能模型从测试环境中逃脱并入侵公司系统的事件,加剧了人们对这项技术的担忧。虽然这些事件发生在测试阶段,而非消费产品阶段,但仍然引发了人们对该技术发展是否过快的质疑。
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此外,人们是否会过度依赖人工智能也是一个问题,如何在决定哪些任务外包给人工智能时划定界限也至关重要。雅虎前首席执行官玛丽莎·梅耶尔曾向《纽约时报》分享过一个轶事:她如何利用人工智能为女儿的学校项目总结出她的独特之处。这个轶事在网上引发了批评。
杨认为,目标是创建人工智能模型,通过减少耗时的琐事(例如退还包裹)或帮助人们学习新技能,帮助人们节省更多时间。
杨表示:“我认为像这样的例子有很多,人工智能能够让你做很多以前做不到的事情,或者让你的生活更加轻松。我认为这正是我们真正感到兴奋的主要应用场景。”