search
HomeTechnology peripheralsAIOpenAI and Google have a double standard: use other people's data to train large models, but never allow their own data to leak out

In a new era of generative AI, big tech companies are pursuing a "do as I say, not as I do" strategy when it comes to using online content. To a certain extent, this strategy can be said to be a double standard and an abuse of the right to speak.

At the same time, as large language models (LLM) become the mainstream trend in AI development, both large and start-up companies are sparing no effort to develop their own large models. Among them, training data is an important prerequisite for the ability of large models.

Recently, according to Insider reports, Microsoft-backed OpenAI, Google and its backed Anthropic have been using online content from other websites or companies for training for many years. Their generative AI model . These were all done without asking for specific permission and will form part of a brewing legal battle to determine the future of the web and how copyright law is applied in this new era.

OpenAI and Google have a double standard: use other peoples data to train large models, but never allow their own data to leak out

These big tech companies may argue that they are fair use, whether that is really the case is up for debate. But they won’t let their content be used to train other AI models. So we can’t help but ask, why can these large technology companies use other companies’ online content when training large models?

These companies are smart, but also very hypocritical

Is there any solid evidence for the claim that big tech companies use other people’s online content but don’t allow others to use their own? This can be seen in the terms of service and use of some of their products.

First let’s look at Claude, which is an AI assistant similar to ChatGPT launched by Anthropic. The system can complete tasks such as summary summarization, search, assistance in creation, question and answer, and coding. It was upgraded again some time ago and the context token was expanded to 100k, which greatly accelerated the processing speed.

OpenAI and Google have a double standard: use other peoples data to train large models, but never allow their own data to leak out

Claude’s Terms of Service are as follows. You may not access or use the Service in the following ways (some of which are listed here). If any of these restrictions are inconsistent or unclear with the Acceptable Use Policy, the latter shall prevail:

  • Develop any product or service that competes with our Services, including developing or training any AI or machine learning algorithms or models
  • From our Crawl, crawl or otherwise obtain data or information from the Service

Claude Terms of Service Address: https://vault.pactsafe.io/s /9f502c93-cb5c-4571-b205-1e479da61794/legal.html#terms

Similarly, Google’s Generative AI Terms of Use states, “You may not use the Service To develop machine learning models or related technologies."

OpenAI and Google have a double standard: use other peoples data to train large models, but never allow their own data to leak out

##Google Generative AI Terms of Use Address: https: //policies.google.com/terms/generative-ai

What about OpenAI’s terms of use? Similar to Google, "You may not use the output of this service to develop models that compete with OpenAI."

OpenAI and Google have a double standard: use other peoples data to train large models, but never allow their own data to leak out

OpenAI Terms of Use Address: https://openai.com/policies/terms-of-use

These companies are smart, they know that high-quality content is critical to training new AI models, so it makes sense not to allow others to use their output in this way. But they have no scruples in using other people’s data to train their own models. How to explain this?

OpenAI, Google and Anthropic declined Insider's request for comment and did not respond.

Reddit, Twitter and Others: Enough is Enough

Actually, other companies weren't happy when they realized what was happening. In April, Reddit, which has been used for years to train AI models, plans to start charging for access to its data.

Reddit CEO Steve Huffman said, “Reddit’s data corpus is too valuable to give away that value to the largest companies in the world for free.”

Also in April this year, Musk accused Microsoft, OpenAI’s main supporter, of illegally using Twitter data to train AI models. "Time for litigation," he tweeted.

OpenAI and Google have a double standard: use other peoples data to train large models, but never allow their own data to leak out

#However, in response to Insider's comment, Microsoft said, "There are so many things wrong with this premise that I don't even know where to start. ”

OpenAI CEO Sam Altman has tried to deepen this problem by exploring new AI models that respect copyright. According to Axios, he recently said, "We are trying to develop a new model. If the AI ​​system uses your content or uses your style, you will get paid for it."

OpenAI and Google have a double standard: use other peoples data to train large models, but never allow their own data to leak out

Sam Altman

Publishers (including Insiders) will all have vested interests. Additionally, some publishers, including U.S. News Corp., are already pushing for tech companies to pay to use their content to train AI models.

The current training method of AI models "breaks" the network

A former Microsoft executive said there must be something wrong with this. Microsoft veteran and famous software developer Steven Sinofsky believes that the current training method of AI models "breaks" the network.

OpenAI and Google have a double standard: use other peoples data to train large models, but never allow their own data to leak out

Steven Sinofsky

He’s pushing The post reads, "In the past, crawled data was used in exchange for click-through rates. But now it is only used to train a model and does not bring any value to creators and copyright owners."

Perhaps, as more companies wake up, this uneven data usage in the era of generative AI will soon be changed.

The above is the detailed content of OpenAI and Google have a double standard: use other people's data to train large models, but never allow their own data to leak out. For more information, please follow other related articles on the PHP Chinese website!

Statement
This article is reproduced at:51CTO.COM. If there is any infringement, please contact admin@php.cn delete
The Hidden Dangers Of AI Internal Deployment: Governance Gaps And Catastrophic RisksThe Hidden Dangers Of AI Internal Deployment: Governance Gaps And Catastrophic RisksApr 28, 2025 am 11:12 AM

The unchecked internal deployment of advanced AI systems poses significant risks, according to a new report from Apollo Research. This lack of oversight, prevalent among major AI firms, allows for potential catastrophic outcomes, ranging from uncont

Building The AI PolygraphBuilding The AI PolygraphApr 28, 2025 am 11:11 AM

Traditional lie detectors are outdated. Relying on the pointer connected by the wristband, a lie detector that prints out the subject's vital signs and physical reactions is not accurate in identifying lies. This is why lie detection results are not usually adopted by the court, although it has led to many innocent people being jailed. In contrast, artificial intelligence is a powerful data engine, and its working principle is to observe all aspects. This means that scientists can apply artificial intelligence to applications seeking truth through a variety of ways. One approach is to analyze the vital sign responses of the person being interrogated like a lie detector, but with a more detailed and precise comparative analysis. Another approach is to use linguistic markup to analyze what people actually say and use logic and reasoning. As the saying goes, one lie breeds another lie, and eventually

Is AI Cleared For Takeoff In The Aerospace Industry?Is AI Cleared For Takeoff In The Aerospace Industry?Apr 28, 2025 am 11:10 AM

The aerospace industry, a pioneer of innovation, is leveraging AI to tackle its most intricate challenges. Modern aviation's increasing complexity necessitates AI's automation and real-time intelligence capabilities for enhanced safety, reduced oper

Watching Beijing's Spring Robot RaceWatching Beijing's Spring Robot RaceApr 28, 2025 am 11:09 AM

The rapid development of robotics has brought us a fascinating case study. The N2 robot from Noetix weighs over 40 pounds and is 3 feet tall and is said to be able to backflip. Unitree's G1 robot weighs about twice the size of the N2 and is about 4 feet tall. There are also many smaller humanoid robots participating in the competition, and there is even a robot that is driven forward by a fan. Data interpretation The half marathon attracted more than 12,000 spectators, but only 21 humanoid robots participated. Although the government pointed out that the participating robots conducted "intensive training" before the competition, not all robots completed the entire competition. Champion - Tiangong Ult developed by Beijing Humanoid Robot Innovation Center

The Mirror Trap: AI Ethics And The Collapse Of Human ImaginationThe Mirror Trap: AI Ethics And The Collapse Of Human ImaginationApr 28, 2025 am 11:08 AM

Artificial intelligence, in its current form, isn't truly intelligent; it's adept at mimicking and refining existing data. We're not creating artificial intelligence, but rather artificial inference—machines that process information, while humans su

New Google Leak Reveals Handy Google Photos Feature UpdateNew Google Leak Reveals Handy Google Photos Feature UpdateApr 28, 2025 am 11:07 AM

A report found that an updated interface was hidden in the code for Google Photos Android version 7.26, and each time you view a photo, a row of newly detected face thumbnails are displayed at the bottom of the screen. The new facial thumbnails are missing name tags, so I suspect you need to click on them individually to see more information about each detected person. For now, this feature provides no information other than those people that Google Photos has found in your images. This feature is not available yet, so we don't know how Google will use it accurately. Google can use thumbnails to speed up finding more photos of selected people, or may be used for other purposes, such as selecting the individual to edit. Let's wait and see. As for now

Guide to Reinforcement Finetuning - Analytics VidhyaGuide to Reinforcement Finetuning - Analytics VidhyaApr 28, 2025 am 09:30 AM

Reinforcement finetuning has shaken up AI development by teaching models to adjust based on human feedback. It blends supervised learning foundations with reward-based updates to make them safer, more accurate, and genuinely help

Let's Dance: Structured Movement To Fine-Tune Our Human Neural NetsLet's Dance: Structured Movement To Fine-Tune Our Human Neural NetsApr 27, 2025 am 11:09 AM

Scientists have extensively studied human and simpler neural networks (like those in C. elegans) to understand their functionality. However, a crucial question arises: how do we adapt our own neural networks to work effectively alongside novel AI s

See all articles

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Tools

ZendStudio 13.5.1 Mac

ZendStudio 13.5.1 Mac

Powerful PHP integrated development environment

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

SecLists

SecLists

SecLists is the ultimate security tester's companion. It is a collection of various types of lists that are frequently used during security assessments, all in one place. SecLists helps make security testing more efficient and productive by conveniently providing all the lists a security tester might need. List types include usernames, passwords, URLs, fuzzing payloads, sensitive data patterns, web shells, and more. The tester can simply pull this repository onto a new test machine and he will have access to every type of list he needs.

Atom editor mac version download

Atom editor mac version download

The most popular open source editor