Coca-Cola, one of the world's leading beverage companies, has recently signed a deal with OpenAI's DALL-E and ChatGPT. The partnership aims to integrate generative AI technology into Coca-Cola's marketing and consumer experiences. OpenAI, a research organization dedicated to creating artificial intelligence that benefits humanity, has collaborated with management consulting firm Bain & Company to launch the OpenAI x Bain alliance. Coca-Cola is the first company to sign on to this new partnership. Although the details of the deal have not been disclosed, the press release suggests that the collaboration may include marketing and sales initiatives.

ChatGPT is a large AI language model trained by OpenAI, designed to converse with users in natural language. In this article, we'll explore how ChatGPT works, including its architecture, training process, and capabilities. ChatGPT is based on a deep learning architecture called Generative Pre-training Transformer (GPT) is a type of neural network architecture used for natural language processing tasks. It's based on the Transformer architecture introduced by Google in 2017. The transformer architecture consists of multiple layers of neurons that process input text in a highly parallelized manner.

Snap announced Monday it's rolling out an OpenAI-powered chatbot named My AI to its Snapchat subscribers. Snapchat was announced in June and costs $3.99 per month. According to The Verge, the chatbot is based on OpenAI ChatGPT technology, which also underpins Microsoft's Bing AI. It can recommend gift ideas, weekend plans, or recipes, Snap said in a press release. Users can customize the name and chat background of the "experimental feature."

Suffering a bit of anxiety over what recent breakthroughs in artificial intelligence might mean for humanity? So is Twitter, Tesla, and SpaceX CEO Elon Musk. "Having a bit of AI existential angst today," the billionaire tweeted over the weekend, just a few hours after starting the day on a much lighter "hope you have a good Sunday" note to followers. Honestly, in the grand scheme of Musk tweets, this one is a bit more relatable than most. AI broke into the public sphere in a major way towards the end of last year, with OpenAI's ChatGPT chatbot swiftly shaping up to be the fastest-growing app in consumer history.

Large-scale diffusion models have achieved state-of-the-art results on text-to-image synthesis (T2I) tasks. Despite their ability to generate high-quality yet creative images, we observe that attribution-binding and compositional capabilities are still considered major challenging issues, especially when involving multiple objects. Attribute-binding requires the model to associate objects with the correct attribute descriptions, and compositional skills require the model to combine and generate multiple concepts into a single image. In this work, we improve these two aspects of T2I models to achieve more accurate image compositions. To do this, we incorporate linguistic structures with the diffusion guidance process based on the controllable properties of manipulating cross-attention layers in diffusion-based T2I models. We observe that keys and values in cross-attention layers have strong semantic meanings associated with object layouts and content. Therefore, by manipulating the cross-attention representations based on linguistic insights, we can better preserve the compositional semantics in the generated image. Built upon Stable Diffusion, a SOTA T2I model, our structured cross-attention design is efficient that requires no additional training samples. We achieve better compositional skills in qualitative and quantitative results, leading to a significant 5-8% advantage in head-to-head user comparison studies. Lastly, we conduct an in-depth analysis to reveal potential causes of incorrect image compositions and justify the properties of cross-attention layers in the generation process. Text-to-Image Synthesis (T2I) is to generate natural and faithful images given a text prompt as input. Recently, there has been a significant advancement in the quality of generated images by extremely large-scale vision-language models, such as DALL-E 2 (Ramesh et al., 2022), Imagen (Saharia et al., 2022), and Parti (Yu et al., 2022).

Figure 1: Examples of the established deepart detection database (DDDB). The examples of LAION-5B Schuhmann et al. (2022) are conventional artworks (conarts), and the rest examples (i.e., StableDiff Rombach et al. (2021),DALL-E 2 Ramesh et al. (2022),Imagen Saharia et al. (2022),Midjourney Holz (2022), and Parti Yu et al. (2022)) are deepfake artworks (deeparts) produced by generative models. Our data and code will be released. Deepfake technologies have been blurring the boundaries between the real and unreal, likely resulting in malicious events. By leveraging newly emerged deepfake technologies, deepfake researchers have been making a great upending to create deepfake artworks (deeparts), which are further closing the gap between reality and fantasy. This database enables us to explore once-for-all deepart detection and continual deepart detection. For the two new problems, we suggest four benchmark evaluations and four families of solutions on the constructed DDDB. The comprehensive study demonstrates the effectiveness of the proposed solutions on the established benchmark dataset, which is capable of paving a way to more interesting directions of deepart detection. The constructed benchmark dataset and the source code will be made publicly available. There has been a propensity to view deepfake technologies as destructive to the supposed boundaries between the real and unreal, leading to potentially detrimental effects. Despite this, deepfake researchers are continuing to make breakthroughs by wielding newly emerged deepfake technologies to create artworks, which are called deeparts throughout this paper. The new deepart techniques include Stable DiffusionRombach et al. (2021), DALL-E Ramesh et al. (2021; 2022), Imagen Saharia et al. (2022), Midjourney Holz (2022), and Parti Yu et al. (2022) As shown in Figure 1, compared to conventional deepfakes, deeparts have been making the boundary between reality and fantasy much more blurry.

We've joined the AI-hype bandwagon here at the Seattle Search Network. We live and breathe search engine marketing and jump at every Google hiccup, even if we've been okay ignoring Bing all these years. Maybe that's about to change. From random thoughts to early experiments with the tools, there's no shortage of differences of opinion, but that's what keeps us on our toes as digital marketers. We'd love to hear what you think.

The connected world is preparing to take a new technological leap with the generative modality of artificial intelligence: that which is capable of generating text, images, video or music. Analysts agree that we are facing a tipping point, the massive adoption of artificial intelligence is imminent. We will use it habitually and it will change our way of creating. Microsoft's billion-dollar investment in OpenAI--the company that launched ChatGPT--should confirm this bet. The ability to automatically generate content will be present in all its products, from word processing to email.

Snap announced today that it's adding an OpenAI chatbot (similar to ChatGPT) to Snapchat. "My AI" is an experimental feature initially available for $3.99-per-month Snapchat subscribers, although the company reportedly wants to expand it to all users eventually. My AI will appear as a regular Snap user profile, suggesting the company is marketing it less as an all-purpose writing machine and more as a virtual friend. "The big idea is that in addition to talking to our friends and family every day, we're going to talk to AI every day," CEO Evan Spiegel told The Verge. "And this is something we're well positioned to do as a messaging service."

Snapchat is the latest company to get in on the AI frenzy. The company announced today that it's launching "My AI," a new chatbot running the latest version of OpenAI's GPT technology that it has customized for its users. My AI is now available as an experimental feature for Snapchat, the social network's $3.99 a month subscription service. The new chatbot will be pinned to the top of the Chat tab. My AI can do things like help answer a trivia question or write a haiku.