Generative Artificial Intelligence (Generative AI) represents a class of artificial intelligence methodologies designed to autonomously produce novel content across various modalities such as text, images, audio, and other data types. Distinguished by its capacity to generate outputs without explicit programming instructions, generative AI systems leverage learned patterns from extensive training datasets to create content that adheres to the underlying structures of the data.

A prevalent instantiation of generative AI involves the utilization of generative models, with two prominent paradigms being Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs).

Generative Adversarial Networks (GANs): GANs employ a dual neural network architecture comprising a generator and a discriminator. Through adversarial training, the generator endeavors to produce content indistinguishable from real data, while the discriminator aims to differentiate between authentic and generated data. This adversarial interplay results in the continuous refinement of the generator’s ability to produce increasingly realistic outputs.

Variational Autoencoders (VAEs): VAEs operate by learning a probabilistic mapping between input data and a latent space. Novel data is then generated through sampling from this latent space, enabling the production of diverse outputs.

Generative AI finds applications in diverse domains, including image synthesis, text generation, music composition, drug discovery, and style transfer. Notably, it contributes to content creation, creative processes, and scientific endeavors.

However, the proliferation of generative AI raises ethical concerns, particularly in relation to the generation of deceptive content such as deepfakes. The responsible development and deployment of generative AI systems necessitate a balanced consideration of their potential benefits and associated risks. As the field continues to advance, addressing ethical implications will remain a pivotal aspect of research and development in generative AI.

Technology has significantly enhanced various aspects of our shopping experience, transforming the way we research, find inspiration, try out products, and hunt for deals. As we approach the busiest shopping weeks of the year, technology, particularly generative AI, is simplifying the process of discovering gifts for others and ourselves.

Discover more about Google’s updated shopping experiences and join Search Labs at goo.gle/sge-gifts.

Access AI-Generated Gift Ideas

The Search Generative Experience (SGE), incorporating generative AI into Search, aims to facilitate faster and easier understanding of topics and uncovering new insights, particularly beneficial for gift-giving. A new feature within SGE is being introduced to assist holiday shoppers in finding inspiration and the perfect holiday gift more efficiently.

For instance, if you’re searching for a gift for a home cook, input “great gifts for home cooks” and explore various subcategories such as specialty tools, artisanal ingredients, culinary subscriptions, and cooking classes. Generative AI allows you to tailor your search to specific preferences, like finding gifts for home cooks who love pasta or catering to niche interests, such as a 7-year-old aspiring inventor.

SGE serves as a starting point to explore the web, presenting links to informative content from various sources, creating new opportunities for content discovery. If you’re in the U.S. and already opted into SGE, you can use this tool in the Google app (Android and iOS) and Chrome desktop. Otherwise, you can opt in through Search Labs at goo.gle/sge-gifts.

Shop What’s on Your Mind

During the holiday season, many people shop for themselves, and shoppers often have specific visions in mind, especially when it comes to apparel. Introducing a new feature that enables you to place the exact item on your mind directly into your shopping cart using AI-powered image generation for shopping.

When searching for apparel using SGE, you can generate photorealistic images inspired by your search terms, allowing you to visualize and find the style you’re looking for. For example, if you’re searching for a colorful, patterned puffer jacket, you can generate images and make adjustments to refine your search. This feature will be available on mobile in the U.S. starting in December for those already opted into SGE.

Generative AI is also improving the virtual try-on experience to help you visualize how clothing will look on you. Following the success of the virtual try-on tool for women’s tops, this capability is expanding to include men’s tops. When searching for “men’s tops,” you’ll see results from various brands with a “try-on” icon. Tap on a result to see how the clothing looks on a real model, with options to choose from a diverse range of models.

These new generative AI tools aim to make your holiday shopping experience smarter and more confident, whether you’re shopping for family, friends, or yourself.