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Choose How Your Websites Can Add to The Training Data for Bard and Vertex AI

Artificial intelligence is transforming how we access information, communicate, and get things done. Powerful AI services from tech giants like Google are now integrated into our daily lives. The natural language model behind Google’s new Bard chatbot and their Vertex AI platform leverage massive datasets to return amazingly accurate results.

But where does all this training data come from? While some is carefully curated from books and other sources, much of it comes from public websites people use every day. As a website owner, you actually have the ability to contribute your data to help train and advance AI systems like Bard and Vertex.


Opting into Page Indexing
Integrating Structured Data
Submitting Custom Training Data
Setting Up Site Search
In Short
Frequently Asked Questions

There are a few key ways you can opt into providing Google with access to the information on your site. This allows your unique content to improve AI comprehension of your niche and vertical. The data from your site helps the models grasp real-world information so they can better serve your needs and those of your visitors.

Providing training data is voluntary, but offers benefits for both the AI systems and internet users. This guide will explore methods websites can use to add their content to the pool if they choose to participate.

Opting into Page Indexing

The primary way Google trains its natural language processing AI is by crawling the internet and analyzing the text, images and data found on websites. Billions of webpages are crawled regularly to build Google’s index for powering search results.

This allows their algorithms to digest vast amounts of real-world information across every topic imaginable from a diverse range of sources. As a website owner, you can indicate which of your pages you are comfortable having indexed for search and having the content used to advance AI training.

Google only wants to access publicly available pages that you authorize for indexing. This allows them to respect website owners’ preferences, while still gathering open web data. You can use a robots.txt file to provide instructions about what pages Googlebot can and cannot crawl.

The Crawl-delay setting also allows you to adjust how frequently pages are accessed. Proper use of metadata like Noindex and nofollow provides further control over what is included. Opting into crawling and indexing of your website through these methods will allow Google to safely analyze your content in order to train AI models.

This helps the systems better comprehend your specific niche or industry to provide more intelligent and relevant information when people search related topics. Your website likely contains extremely valuable real-world data that could improve AI comprehension. Participating in indexing makes that data available to enhance natural language systems like Bard.

Integrating Structured Data

In addition to text content on your webpages, Google can also learn a lot from structured data that provides more context about the information on your site. Structured data refers to code marked up using schema to label entities, relationships, and attributes within webpage content. For example, schema can indicate ratings, author information, event locations, product details, and more.

This metadata enables Google, and therefore its AI, to understand more complex concepts and interconnectivity. Integrating schema markup is as easy as adding code like JSON-LD or microdata to your site code. There are schemas tailored for many industries and use cases like recipes, courses, products, reviews, articles, FAQs, and more.

Adding appropriate schema gives Google’s AI clarity into the purpose and meaning behind elements on your pages beyond just reading text. This leads to more intelligent extraction of information and comprehension of nuanced details.

Some great opportunities to leverage structured data to improve AI training include:

  • Product schema for online stores – teach product names, prices, SKUs, images, etc.
  • Recipe schema for food blogs – classify ingredients, cook times, instructions, etc.
  • Course schema for educational sites – explain subjects, credits, prerequisites, etc.
  • Event schema for calendars – provide dates, locations, registration details, etc.

The time spent properly tagging up structured data pays off by advancing AI capabilities in your field while improving your own SEO. It’s a win-win for participating websites and the AI models ingesting the training data.

Submitting Custom Training Data

If your website operates in a particularly obscure, unique or advanced niche, the information may be so specialized that broader AI systems have little exposure to it. In these cases, Google provides services through its Vertex AI platform that allow you to directly submit custom datasets for training. This proprietary or sensitive data can be uploaded privately so that you maintain complete control rather than making it public on the open web.

Google currently accepts submissions of text, image, audio and video datasets to help improve its AI capabilities specific to your vertical. Here are some examples of custom training data that could strengthen comprehension:

  • Text data – Provide industry terminology, common queries, speech patterns, named entities, etc. that AI lacks context for based on broader training data. Uploading niche dictionaries or corpuses advances language intelligence.
  • Image data – Supply collections of images covering visual concepts key to your field but not well represented online yet. Anything from products to workflows.
  • Audio data – Share audio clips with important auditory elements like equipment sounds for machine learning. Or clips with accents and wording unique to a region or language.
  • Video data – Videos can combine visuals, audio and text associated with your specialization for multimodal understanding. Training on actual expert footage provides in-depth insight.

While leveraging public web data has advantages for diversity, custom datasets help fill critical gaps. Submitting niche data directly allows you to shape training based on real private insights only your content can provide. The end result is AI better equipped to serve the needs of your audience.


Enabling full-featured search functionality on your website provides another valuable avenue for training data. As visitors use site search to find information in your content, Google can leverage those query logs to better understand user intent for your niche. The language people use when searching your site teaches AI a tremendous amount about the goals, needs and terminology of your industry.

  • Site search data improves models in a few key ways:
  • Reveals the types of questions users have that they can’t find answers for elsewhere online yet related to your vertical. This helps AI serve these intents.
  • Uncovers long-tail keyword patterns and phrasing unique to your niche that broader training data likely misses.
  • Shows which pages users actually find useful for common queries, improving result relevancy.
  • Provides behavioral signals and real user preferences tailored to your site vs generic datasets.

In order to ensure privacy, Google anonymizes and aggregates analytics from site search implementations. Visitors are untraceable from the training data. As an added protection, you can opt to not share query report insights with Google. However, allowing access improves AI matching. Site search unlocks training data already available on your site that can make AI models more intelligent.

In Short

To improve artificial intelligence, it is crucial to provide diverse, high-quality training data. Your website can contribute valuable information to AI comprehension by participating in indexing, integrating structured data, submitting custom datasets, or leveraging on-site search.

Participation can strengthen SEO, increase discoverability, drive traffic, and amplify your brand as an industry leader. It also supports the development of improved AI technologies that provide more value to users. Advances in AI will allow society to uncover new insights and innovations.

Google handles data with care under strict controls, maintaining transparency and consent. As AI services expand into more aspects of life, the need for diverse, high-quality training data from subject matter experts grows. Proper training is essential for AI to elevate information discovery and sharing.

Frequently Asked Questions

Should I allow Google to index all pages of my website?

Not necessarily all pages. Focus on allowing indexing of main pages with your core content. Use robots.txt and metadata as needed to exclude non-public pages or thin pages like contact and tos.

What if my website contains sensitive information?

If your site includes protected personal data, health information, or other regulated content, do not allow indexing and instead rely on submitting selective custom datasets.

Can I remove my page from being indexed later on?

Yes, you can update robots.txt or page metadata at any time in the future to prevent continued indexing if you change your mind. Previously indexed content still aids training.

Who controls what data Google uses from my site?

You maintain complete control. Any data shared from indexing, structured markup or site search is at your discretion and can be limited or revoked anytime.

What are the risks of sharing my website data?

Google handles crawled data securely under policies forbidding misuse. The only risk is public visibility but private or sensitive info should not be indexed/shared anyway.

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