AI language models

attackers-prompted-gemini-over-100,000-times-while-trying-to-clone-it,-google-says

Attackers prompted Gemini over 100,000 times while trying to clone it, Google says

On Thursday, Google announced that “commercially motivated” actors have attempted to clone knowledge from its Gemini AI chatbot by simply prompting it. One adversarial session reportedly prompted the model more than 100,000 times across various non-English languages, collecting responses ostensibly to train a cheaper copycat.

Google published the findings in what amounts to a quarterly self-assessment of threats to its own products that frames the company as the victim and the hero, which is not unusual in these self-authored assessments. Google calls the illicit activity “model extraction” and considers it intellectual property theft, which is a somewhat loaded position, given that Google’s LLM was built from materials scraped from the Internet without permission.

Google is also no stranger to the copycat practice. In 2023, The Information reported that Google’s Bard team had been accused of using ChatGPT outputs from ShareGPT, a public site where users share chatbot conversations, to help train its own chatbot. Senior Google AI researcher Jacob Devlin, who created the influential BERT language model, warned leadership that this violated OpenAI’s terms of service, then resigned and joined OpenAI. Google denied the claim but reportedly stopped using the data.

Even so, Google’s terms of service forbid people from extracting data from its AI models this way, and the report is a window into the world of somewhat shady AI model-cloning tactics. The company believes the culprits are mostly private companies and researchers looking for a competitive edge, and said the attacks have come from around the world. Google declined to name suspects.

The deal with distillation

Typically, the industry calls this practice of training a new model on a previous model’s outputs “distillation,” and it works like this: If you want to build your own large language model (LLM) but lack the billions of dollars and years of work that Google spent training Gemini, you can use a previously trained LLM as a shortcut.

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OpenAI’s GPT Store lets ChatGPT users discover popular user-made chatbot roles

The bot of 1,000 faces —

Like an app store, people can find novel ChatGPT personalities—and some creators will get paid.

Two robots hold a gift box.

On Wednesday, OpenAI announced the launch of its GPT Store—a way for ChatGPT users to share and discover custom chatbot roles called “GPTs”—and ChatGPT Team, a collaborative ChatGPT workspace and subscription plan. OpenAI bills the new store as a way to “help you find useful and popular custom versions of ChatGPT” for members of Plus, Team, or Enterprise subscriptions.

“It’s been two months since we announced GPTs, and users have already created over 3 million custom versions of ChatGPT,” writes OpenAI in its promotional blog. “Many builders have shared their GPTs for others to use. Today, we’re starting to roll out the GPT Store to ChatGPT Plus, Team and Enterprise users so you can find useful and popular GPTs.”

OpenAI launched GPTs on November 6, 2023, as part of its DevDay event. Each GPT includes custom instructions and/or access to custom data or external APIs that can potentially make a custom GPT personality more useful than the vanilla ChatGPT-4 model. Before the GPT Store launch, paying ChatGPT users could create and share custom GPTs with others (by setting the GPT public and sharing a link to the GPT), but there was no central repository for browsing and discovering user-designed GPTs on the OpenAI website.

According to OpenAI, the ChatGPT Store will feature new GPTs every week, and the company shared a list a group of six notable early GPTs that are available now: AllTrails for finding hiking trails, Consensus for searching 200 million academic papers, Code Tutor for learning coding with Khan Academy, Canva for designing presentations, Books for discovering reading material, and CK-12 Flexi for learning math and science.

A screenshot of the OpenAI GPT Store provided by OpenAI.

Enlarge / A screenshot of the OpenAI GPT Store provided by OpenAI.

OpenAI

ChatGPT members can include their own GPTs in the GPT Store by setting them to be accessible to “Everyone” and then verifying a builder profile in ChatGPT settings. OpenAI plans to review GPTs to ensure they meet their policies and brand guidelines. GPTs that violate the rules can also be reported by users.

As promised by CEO Sam Altman during DevDay, OpenAI plans to share revenue with GPT creators. Unlike a smartphone app store, it appears that users will not sell their GPTs in the GPT Store, but instead, OpenAI will pay developers “based on user engagement with their GPTs.” The revenue program will launch in the first quarter of 2024, and OpenAI will provide more details on the criteria for receiving payments later.

“ChatGPT Team” is for teams who use ChatGPT

Also on Monday, OpenAI announced the cleverly named ChatGPT Team, a new group-based ChatGPT membership program akin to ChatGPT Enterprise, which the company launched last August. Unlike Enterprise, which is for large companies and does not have publicly listed prices, ChatGPT Team is a plan for “teams of all sizes” and costs US $25 a month per user (when billed annually) or US $30 a month per user (when billed monthly). By comparison, ChatGPT Plus costs $20 per month.

So what does ChatGPT Team offer above the usual ChatGPT Plus subscription? According to OpenAI, it “provides a secure, collaborative workspace to get the most out of ChatGPT at work.” Unlike Plus, OpenAI says it will not train AI models based on ChatGPT Team business data or conversations. It features an admin console for team management and the ability to share custom GPTs with your team. Like Plus, it also includes access to GPT-4 with the 32K context window, DALL-E 3, GPT-4 with Vision, Browsing, and Advanced Data Analysis—all with higher message caps.

Why would you want to use ChatGPT at work? OpenAI says it can help you generate better code, craft emails, analyze data, and more. Your mileage may vary, of course. As usual, our standard Ars warning about AI language models applies: “Bring your own data” for analysis, don’t rely on ChatGPT as a factual resource, and don’t rely on its outputs in ways you cannot personally confirm. OpenAI has provided more details about ChatGPT Team on its website.

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