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OpenAI ChatGPT-5 introduction displayed on smartphone screen
(Cheng Xin/Getty Images)

Here’s how people are actually using ChatGPT

The new report released in collaboration with the National Bureau of Economic Research offers one of the largest surveys of real-world AI chatbot use.

Jon Keegan

OpenAI has released its largest report yet on how real people are actually using ChatGPT. The fascinating working research paper, published by the National Bureau of Economic Research, describes a wide-ranging study that used AI to analyze 1 million chat transcripts (no humans read any of the chats). The study has not been peer reviewed.

Some of the big takeaways from the paper:

  • 💃 70% (!!!) of all queries were not related to work. That number may send a chill down the spine of Big Tech, as its betting on enterprise AI to generate enough revenue to justify the hundreds of billions its spending to build out AI infrastructure.

  • 📝 Among work-related messages, the most common use for ChatGPT is writing, and mostly just to modify or improve a user’s text. Writing queries made up 42% of work-related messages and 52% of all messages from users who work in business and management.

  • 🙋🏻 About half (49%) of all queries were classified as “asking” — for guidance, advice, or information. 40% of messages were requests classified as “doing,” or asking the chatbot to complete a task.

  • 👩‍💻 Female users contributed more than half of all queries, as of July 2025. This is a massive shift from early on, when the vast majority of users were male. But it’s worth noting that the study determined this by classifying first names as masculine or feminine.

  • 🛹 The youth loves AI. Half of all messages were from adults under 26.

The OpenAI researchers took a random sample of about 1 million messages between May 2024 and June 2025 from logged-in, adult ChatGPT users (who did not opt out of sharing their messages for training).

ChatGPT usage - Breakdown of tasks by topic.
Breakdown of tasks by topic (Chart: OpenAI/NBER)

This study is one of the largest surveys of real-world AI use, so this data will be of great interest to all the companies trying to figure out how theyre going to make money selling AI services.

One thing that stood out was how utilitarian the usage of AI was. Rather than falling in love with an AI chatbot or having deep conversations with your new AI buddy, it looks like people are just using it to make their work better and figure things out.

It remains to be seen how AI will end up being part of our everyday lives, but it might look a lot more boring than Silicon Valley is making it out to be.

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Report: China’s “Manhattan Project” built an advanced EUV chip fab prototype

The most advanced chipmaking process in the world is currently owned by one company: Dutch chipmaker ASML.

The process, known as extreme ultraviolet lithography (EUV), allows for the smallest, most complex semiconductors to be etched onto silicon chips.

These advanced chips are used in a huge number of crucial industries such as AI, mobile phones, and weapons manufacturing.

A new report from Reuters says that China has completed a factory-sized prototype of an EUV chip fab, a first that could have huge ramifications for the balance of power in the global technology race.

The prototype was built in a high-security facility in Shenzhen by former ASML employees and made use of secondary markets to acquire older, used ASML parts, according to the report. Despite a goal of delivering working chips by 2028, sources say China is likely a couple years behind that schedule.

ASML’s $250 million EUV machines are used to manufacture advanced chips for Nvidia, Advanced Micro Devices, and for chips made by TSMC.

ASML shares were down about 4.8% as of 12 p.m. ET.

These advanced chips are used in a huge number of crucial industries such as AI, mobile phones, and weapons manufacturing.

A new report from Reuters says that China has completed a factory-sized prototype of an EUV chip fab, a first that could have huge ramifications for the balance of power in the global technology race.

The prototype was built in a high-security facility in Shenzhen by former ASML employees and made use of secondary markets to acquire older, used ASML parts, according to the report. Despite a goal of delivering working chips by 2028, sources say China is likely a couple years behind that schedule.

ASML’s $250 million EUV machines are used to manufacture advanced chips for Nvidia, Advanced Micro Devices, and for chips made by TSMC.

ASML shares were down about 4.8% as of 12 p.m. ET.

tech

Google is reportedly working with Meta to expand software support for its AI chips

Nvidia dominates the market for AI chips. But its advantage is not limited to hardware.

The company has a growing suite of software tools that are usually paired with its chips, optimized to get the most out of the GPUs crunching the data.

Any challengers to Nvidia’s dominance will need to make it easy for developers to walk away from the Nvidia software-hardware lock-in. That’s what Google and Meta are teaming up to do.

A new report from Reuters says Google is working on an initiative code-named “TorchTPU,” which aims to make it easier for AI developers who use the ubiquitous, open-source PyTorch software framework to switch the hardware layer to Google’s tensor processing units (TPUs).

Meta is a huge backer of the PyTorch project, so the company is teaming up with Google to help develop its TorchTPU software, per the report.

Last month, it was reported that Google is planning on selling TPUs worth “billions of dollars” to Meta, which follows other Big Tech players who are hedging their bets against Nvidia’s dominance.

Any challengers to Nvidia’s dominance will need to make it easy for developers to walk away from the Nvidia software-hardware lock-in. That’s what Google and Meta are teaming up to do.

A new report from Reuters says Google is working on an initiative code-named “TorchTPU,” which aims to make it easier for AI developers who use the ubiquitous, open-source PyTorch software framework to switch the hardware layer to Google’s tensor processing units (TPUs).

Meta is a huge backer of the PyTorch project, so the company is teaming up with Google to help develop its TorchTPU software, per the report.

Last month, it was reported that Google is planning on selling TPUs worth “billions of dollars” to Meta, which follows other Big Tech players who are hedging their bets against Nvidia’s dominance.

$100B

Waymo, Alphabet’s autonomous driving subsidiary, is in talks to raise more than $15 billion in a funding round that would value the company near $100 billion, Bloomberg reports. That’s more than double the valuation from its last round in October 2024, reflecting its lead in driverless ride-hailing.

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