Google's virtual try-on tool now includes dresses, allowing shoppers to see how they'll look on various models. Using generative AI, the tool displays detailed images, showing features like shadows and draping. This has increased engagement by 60%, with users trying clothes on multiple models per product. The tool is available for dresses from brands like SIMKHAI and Boden. It provides a more accurate view of both the dress and the person wearing it.

Google has expanded its generative AI-powered virtual try-on tool to include dresses, allowing users to try on thousands of dresses from brands like Boden and Staud virtually. Dresses, a highly searched category, pose a challenge for traditional diffusion techniques due to their intricate details and varied lengths. To overcome this, Google developed a new training strategy and built the VTO-UNet Diffusion Transformer (VTO-UDiT), which maintains body details while accurately displaying dresses. This advanced tool aims to improve the virtual shopping experience.

Google is aiming to provide tailored shopping experiences catering to the unique needs and tastes of its users. Personalized shopping tools now include style recommendations, brand preferences, AI image generation, and virtual try-on features. These tools allow individuals to refine their searches based on personal preferences, rate styles, and visual products in real-life scenarios before making a purchase.

71% of customers are confident in using AI to virtually try on products before buying. This indicates the potential for AI to streamline decision-making processes in online retail. The top generative AI use cases consumers look forward to are automating product filters based on customer needs, creating customized items, and summarizing product reviews.

Google has introduced a new feature that allows users to personalize shopping experiences by rating products with Tinder-style swipe gestures to compete with Amazon and Walmart's AI shopping tools. The tool, available on mobile browsers and the Google app, will show style recommendations based on user ratings, with options to adjust preferences for further personalized results.

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Pinterest’s new body type ranges empower users to tailor their search results for women’s fashion and wedding ideas. It aims to foster inclusivity and representation online. Users can personalize their browsing experience to reflect their unique preferences and identities, with the option to select from 4 body type ranges. This AI-powered innovation offers Pinterest users greater control over their visual discovery and shopping journey.

Pinterest has launched a body type filtering feature in the U.S. that allows users to search fashion and wedding ideas based on different body types and showcase size-inclusive brands. The tool, powered by Pinterest's computer vision technology, has led to a 66% increase in user engagement. Pinterest plans to expand the feature to men's fashion.

Google's new tools in Google Merchant Center include product trend insights that highlight popular search and purchase trends. Enhanced AI features now offer summaries of product performance, and conversational queries allow for easier access to tailored data reports. Additionally, Google has improved product availability notes with an automated onboarding process and introduced new customer acquisition goals in Performance Max and Search campaigns.

This dataset, generated using large language models, tailors outfits to different occasions, styles, and body types, offering high-quality and relevant suggestions.

Squarespace has recently introduced AI image and text generation features, marking a significant update to its platform. This move aligns with a broader trend in web design, where various website builders are incorporating AI tools to streamline the design process. Squarespace's new Blueprint AI platform automatically populates websites with AI-generated content, raising questions about the authenticity and originality of such creations. The integration of AI-generated imagery and text aims to enhance user experience by providing a quick way to visualize how a website might look. Squarespace claims that the images produced are aesthetically pleasing and inspirational, with users able to customize the tone and style of the content based on their brand personality. This feature is particularly appealing to small business owners and creatives who may not have access to high-quality stock images or the resources to create original content. However, there are concerns among users, especially creatives, about the implications of using AI-generated content. Many worry that the generic nature of AI imagery could detract from the uniqueness of their portfolios or brands. Additionally, there are legal and ethical considerations regarding the training of AI models, as some of the technology used by Squarespace relies on publicly available models from companies like Google and OpenAI. This has led to questions about the safety and legality of using such images commercially, especially given ongoing lawsuits against these companies related to the use of artists' works in training datasets. Despite these concerns, Squarespace's AI features could be beneficial for users looking to quickly prototype their websites or for those who prefer to use AI-generated content rather than traditional stock images. The platform's approach allows users to see a more tailored representation of their site, which could be particularly useful for specific niches, such as wedding photography or service-based businesses. As the landscape of web design continues to evolve with AI technology, Squarespace's latest offerings reflect a growing demand for tools that simplify the design process while also sparking debate about the future of creativity in the digital space.

eBay has introduced an AI-powered background enhancement tool for product photos on its mobile apps for iOS users in the U.S., U.K., and Germany that allows sellers to remove and replace backgrounds with AI-generated backdrops. Developed with eBay's Responsible AI team to ensure fairness and safety, the tool aims to simplify the process of creating listings, save time, and improve listing quality. An Android rollout is expected in the coming months.

Instagram's new "AI Studio" lets creators develop AI chatbot versions of themselves. It is currently rolling out as an early test in the US.

Google will soon start testing search and shopping ads within AI Overviews for users in the US. The company says it will display ads in AI Overviews when they're relevant to both the query and the information in the AI Overview. Advertisers already running certain campaigns through Google will automatically become eligible to appear in AI Overviews. It is unclear when exactly the change will roll out.

Google is expanding its AI Overviews in Search by providing more detailed information directly in search results. This potentially reduces the need for users to visit websites. To address this, Google is testing new link displays within these overviews. This update could encourage users who do click through to spend more time on the sites they visit.

Snapchat unveiled a suite of new AR and ML tools aimed at empowering brands and advertisers to create more engaging experiences on the platform. These tools include enhanced AR try-on assets, branded AR ads with generative AI technology, and AR Extensions for seamless integration into various ad formats.

Google announced plans to test search and shopping ads in the AI summaries. Ads will appear within the AI Overview in a section labeled as ‘sponsored' when they're relevant to both the query and the information in the AI Overview. AI Overview will draw on ads from advertisers' existing campaigns. This means they can neither completely opt out of the experiment nor have to adapt the settings and designs of their ads to appear in the feature.

AI design tools, like Midjourney, DALL-E, and Adobe Sensei, enhance the design process by handling repetitive tasks, analyzing data, and generating ideas. While they offer speed and efficiency, they lack the human touch needed for emotional and cultural nuances. The future of design lies in blending AI's capabilities with human creativity, allowing designers to focus on strategic and creative aspects and creating more impactful and emotionally resonant work.

Google has integrated AI into its internal software development tools, with developers now using AI-based code completion for 50% of code characters. It has improved both model accuracy and user experience, and the company plans to further leverage AI in areas like testing, code understanding, and code maintenance. The industry as a whole is moving towards adding natural language as a common interface for software engineering tasks, like fixing bugs and writing new code.

There's been a shift in attention from the metaverse to the Apple Vision Pro. Brands have been testing immersive experiences and integrating them into users' real-world environments. Companies like e.l.f. Beauty have been seeing 50% higher conversion rates on their Vision Pro apps compared to their mobile apps. Wayfair, Lowe's, and J.Crew have released apps for Vision Pro that let users experience products through the headset. Any kind of experience designed for the headset is helping brands stand out at this point.

Google is incorporating AI into its search engine with features like "AI Overviews" and a new planning tool. It aims to deliver summarized answers, automatic categorization, and personalized results using its Gemini AI to understand queries, generate summaries, and design result pages. For users, this could mean a completely new way to interact with the internet: less typing, fewer tabs, and more chatting with a search engine.

Pinterest Ad Labs, a new innovation program, allows select brands to test creative and ad tools, including personalized background generation and interactive shopping through collages. These tools aim to enhance engagement and make ads more visually appealing and shoppable. Pinterest is also launching Pinterest Performance+, an AI-powered suite to improve campaign performance and reduce campaign creation time.

AI-driven filmmaking is rapidly reshaping the landscape of visual storytelling, with companies like Runway AI Inc. at the forefront of this transformation. As artificial intelligence becomes more integrated into creative processes, it enhances audience engagement and fosters innovation. Runway's co-founder and chief technology officer, Anastasis Germanidis, highlights the company's commitment to generative storytelling, which allows for the creation of compelling visuals and personalized content. One notable application of Runway's technology was during Madonna's live concert tour, where the visuals displayed were generated using Runway's tools. Recently, the company introduced a video-to-video tool that enables users to transform the style of an input video while preserving its structure. This tool offers filmmakers the ability to control motion and achieve stunning stylistic results, showcasing the versatility of AI in filmmaking. At the Anyscale Ray Summit 2024, Germanidis discussed the significance of Runway's Gen-3 Alpha technology, which serves as a foundation for AI-driven filmmaking. This technology generates expressive human characters and supports various tools, including text-to-video and image-to-video capabilities. Runway has also launched initiatives like the Hundred Film Fund to directly support AI-driven filmmaking projects and organized a 48-hour film festival that allowed participants to utilize Gen-3 Alpha, resulting in diverse and innovative storytelling. Runway's mission extends to empowering filmmakers with tools that facilitate experimentation and reduce production costs. The company emphasizes collaboration within the generative media community, exemplified by its partnership with Lionsgate. This collaboration aims to integrate generative tools into the workflows of established film studios, enhancing the creative process. To effectively scale multimodal data processing and training, Runway employs Anyscale Ray, which provides a robust platform for developing video models. Germanidis notes the importance of versatility in video model training, as standards are still being established in this area. The use of Ray enhances the developer experience and accelerates the creation of new components and models, allowing Runway to push the boundaries of AI-driven filmmaking. Overall, Runway is positioned as a key player in the evolution of filmmaking, bridging the gap between technology and artistic expression. The company's innovative tools and collaborative efforts are paving the way for a new era of storytelling that leverages the power of artificial intelligence.

Retailers are facing a significant shift in the ecommerce landscape as Google evolves its search results to resemble Amazon-style category pages. This transformation necessitates that retailers adapt their SEO strategies, placing greater emphasis on optimizing product pages rather than traditional category pages. Over the past year, Google has implemented several updates to its ecommerce search results. These changes include the introduction of product grids that display products directly, the addition of search filters, and the integration of local search elements. Most recently, Google has begun to showcase product results within AI Overviews, further enhancing the visibility of products in search results. Collectively, these updates have created a new ecommerce search experience that prioritizes product visibility. When users search for items like "espresso machines," they are now greeted with product grids at the top of the search results, often before any organic listings. This new layout allows users to refine their searches directly within the results, selecting specific features to narrow down their options. The right-side sidebar provides detailed product information, including images, pricing, and descriptions, all without needing to click through to a retailer's website. This shift indicates that Google is attempting to replicate the traditional category page experience within its search results. By prioritizing product pages, Google is effectively positioning itself as a competitor to Amazon, which has historically dominated product searches. The implications for retailers are profound; as Google continues to enhance its product-focused search results, category pages are losing their prominence. The competition between Google and Amazon for ecommerce market share has intensified, with a notable decline in Google's product search market share over the years. As a result, retailers must now focus on optimizing their product pages to align with Google's evolving search algorithms. This includes updating title tags, H1s, and product data to ensure that key features are highlighted effectively. Moreover, the importance of product data cannot be overstated. Google emphasizes the need for accurate and comprehensive product feeds, which play a crucial role in how products are displayed in search results. Retailers must ensure that their product data is optimized for search engines, reflecting relevant keywords and providing complete information. As Google continues to act as a de facto category page, there is a growing opportunity for brands that focus on long-tail queries. Smaller brands that optimize for specific, less competitive queries can gain visibility in search results that were previously dominated by larger retailers. This shift allows them to compete more effectively in a landscape that is increasingly driven by product-focused search results. However, these changes also pose challenges for affiliate sites, which are finding it harder to compete in a search environment that prioritizes direct product listings. As Google enhances its product features, affiliate sites may struggle to maintain their visibility and traffic. In conclusion, the evolution of Google's search results is reshaping the ecommerce landscape. Retailers must adapt their strategies to prioritize product pages and optimize their product data to remain competitive. As Google continues to refine its search experience to mirror that of a category page, understanding these changes will be crucial for retailers looking to thrive in the digital marketplace.

Based on UserZoom capabilities, UserTesting has created a new Feedback Engine, which combines AI with generative capabilities to help better understand feedback from user surveys. The company is also expanding its AI-powered insights capability to provide a deeper analysis of trends from user testing operations by enabling AI-powered surveys. AI-powered theme generation will allow researchers to understand test results better.

Billions of Google users will soon see AI-generated summaries at the top of many of their search results. The AI Overviews are designed to take out the hard work of searching so users can focus on the important things. Google announced several other AI-powered features at its I/O developer conference, such as a feature in Lens that lets users search by capturing a video, a planning tool that can generate trip itineraries and meal plans with a single query, and suggestions within search results. While similar products have come under scrutiny for summarizing content and not directing users to the actual sources of information, Google says that early data shows that the new way of searching will actually lead to more clicks to the open web.

While AI-powered chatbots can improve e-commerce experiences, their use also risks driving away customers. 1 in 5 shoppers are likely to abandon purchases after interacting with them due to clunky user experiences. On the other hand, consumers who engage with chatbots don’t mind seeking AI assistance for automated pricing, real-time promotions, and product discovery. The key to the successful integration of AI lies in hyper-personalized recommendations and creating a frictionless shopping experience.

Introduced at its 'It's Glowtime' event, Apple's new 'Visual Intelligence' feature enhances visual search via the iPhone 16's Camera Control button. It enables access to Google's search engine and other third-party tools, like OpenAI's ChatGPT, directly from the camera interface for varied tasks.

Google introduced AI Overviews to enhance search results, providing users with more accurate and relevant information, especially for complex queries. While some issues arose, such as erroneous results and misinterpreted content, Google has implemented over a dozen technical improvements to address these challenges, including better detection of nonsensical queries and limiting user-generated content in AI Overviews.

Snap unveiled a real-time, on-device image diffusion model for creating vivid AR experiences and introduced new generative AI tools for AR creators at the Augmented World Expo. These enhancements, which include a new Lens Studio 5.0 with an AI assistant, aim to make AR content creation faster and more efficient with features like realistic ML face effects, 3D asset generation, and character creation using text prompts.