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Developers who use Google Gemini for free should be aware that their data can be used to train its generative artificial intelligence models, including those that power Google AI Studio and Gemini Pro.
Last week, Google made Gemini Pro available to developers and businesses looking to build their own apps using its generative AI model. Developers can access the model through the Gemini API in Google AI Studio, while businesses will need to do so through Google Cloud’s development and machine learning platform, Vertex AI.
A free and limited test version
Developers currently have free access to Gemini Pro and Gemini Pro Vision capped at 60 requests per minute. Which Google says is suitable for most app development needs. With the Gemini Pro Vision model, queries can contain text or images, but the AI response will be in text form.
Developers using Vertex AI have the opportunity to test these two AI models for free, on a limited basis, until their general availability date – planned for early 2024. After this date, fees will apply to Google AI Studio and Vertex AI, per 1,000 characters or per image. Google announced that it had cut prices by four for input data and by two for output data.
Currently, Gemini Pro supports 38 languages and is available in over 180 markets, including the Asia Pacific region.
Developers can move their AI Studio code to Vertex AI if they want a fully managed AI platform that offers more customization and Google Cloud features, including data governance and compliance, and security. However, Google touts AI Studio as the fastest way to build with Gemini.
Data may be accessible to qualified Google employees
Developers should be aware that when using the free 60 requests per minute quota, their requests and the responses they receive “may be reviewed by qualified reviewers.”
Indeed, as Google confirmed to ZDNET, the data is used to improve the quality of its products. “Human review is a necessary step in the model improvement process,” says a company spokesperson. “With their analysis and feedback, qualified reviewers help improve the quality of generative machine learning models like those that power Google AI Studio and Gemini Pro through the Gemini API. »
To nevertheless protect the privacy of developers, Google specifies that this data is depersonalized and dissociated from their API key and their Google account – a Google account being necessary to connect to AI Studio. This protection occurs before reviewers can view or annotate the data.
Data is retained to train models
Google’s terms of service (TOU) for its generative AI APIs further specify that the data is used to “adjust models” and that it may be retained in relation to user-tuned models ” for further adjustment when supported models change”.
“When you delete an adjusted model, the data relating to it is also deleted,” we can read in the T&Cs. The latter also recommend not transmitting sensitive, confidential or personal data to its AI models.
In the event that a developer decides to move to Vertex AI, the data they have generated using Gemini Pro via AI Studio will still be able to be consulted by Google reviewers, this data being used to improve the brand’s products, explains a Google spokesperson told ZDNet. The improvements concern in particular “the development and evaluation of additional models”, he specifies. “From the anonymized data, we may also gain insights about our products to help us determine what features we would like to add to Google AI Studio. »
Google Cloud customer data is not reused
Developers and organizations concerned about the security of their data, but still want to build with Gemini, should use the model through Vertex AI, as Google Cloud customers.
Google in fact assures that this route allows you to “personalize Gemini with total control of the data”. Access to Gemini models through Vertex AI also allows enterprise customers to tune the models with their own data.
Additionally, Google says it doesn’t train its generative AI models with data from its cloud customers’ queries.
Source: ZDNet.com