9/25/2023 0 Comments Microsoft photo aiThe Drop tool is a significant addition, allowing users to send files and other content to themselves, creating a personal notebook that syncs between devices. In addition to the Image Wizard, Microsoft has added several other features to Edge that improve its functionality. While it may not be ideal for users looking for high-quality images, it is an excellent tool for those looking to create custom visuals quickly and easily. The images generated by the tool are relatively simple and straightforward, with a minimalist design. Once the tool is added, users can generate images by typing in prompts that describe what they want to see. The Image Wizard feature is a seamless addition to Edge, and users can access it by adding it to the sidebar. The feature's main selling point is its ability to create custom visuals tailored to a user's specific needs. However, Microsoft's Image Wizard stands out for its ease of use, which is a critical factor in making AI-powered tools accessible to users who may not be tech-savvy. Microsoft's AI image generator is not the first of its kind, with competitors such as OpenAI's DALL-E and Google's DeepDream, among others. Photo by Pawel Czerwinski / Unsplash Creating "very specific" visualizations The goal is to make the tool accessible to a broader audience, allowing users to create custom images without the need for advanced image editing skills. The Image Wizard uses OpenAI's DALL-E, which is capable of generating images based on text inputs. The Image Wizard feature is a part of Microsoft's larger initiative to integrate AI into its products, and its partnership with OpenAI has been instrumental in achieving that goal. This announcement is a significant step forward in making AI-powered image generation accessible to a broader audience. Microsoft believes that this feature will be useful for creating "very specific" visualizations for social media posts, slideshows, and documents. This tool, called the "Image Wizard," generates images based on prompts typed into the Edge sidebar. Microsoft says it plans to make Kosmos-1 available to developers, though the GitHub page the paper cites has no obvious Kosmos-specific code upon this story's publication.Microsoft has announced that its AI image generator, powered by DALL-E, is now available to Edge users worldwide. In the future, the researchers say they'd like to scale up Kosmos-1 in model size and integrate speech capability as well. Still, while Kosmos-1 represents early steps in the multimodal domain (an approach also being pursued by others), it's easy to imagine that future optimizations could bring even more significant results, allowing AI models to perceive any form of media and act on it, which will greatly enhance the abilities of artificial assistants. This is by no means a slam dunk, and errors in the methodology could have affected the results, but Kosmos-1 beat random chance (17 percent) on the Raven IQ test. Kosmos-1 could only correctly answer a question on the Raven test 22 percent of the time (26 percent with fine-tuning). To test Kosmos-1, the researchers fed it a filled-out test, one at a time, with each option completed, and asked if the answer was correct. Of particular interest is Kosmos-1's performance on Raven's Progressive Reasoning, which measures visual IQ by presenting a sequence of shapes and asking the test taker to complete the sequence. In many of these tests, Kosmos-1 outperformed current state-of-the-art models, according to Microsoft. After training, they evaluated Kosmos-1's abilities on several tests, including language understanding, language generation, optical character recognition-free text classification, image captioning, visual question answering, web page question answering, and zero-shot image classification. Microsoft trained Kosmos-1 using data from the web, including excerpts from The Pile (an 800GB English text resource) and Common Crawl. For the modalities of continuous signals (e.g., image, and audio), it is also feasible to represent inputs as discrete code and then regard them as “foreign languages”. For input tokens, we use a lookup table to map them into embeddings. Then the embeddings are fed into the decoder. An embedding module is used to encode both text tokens and other input modalities into vectors. For example, “ document ” is a text input, and " paragraph Image Embedding paragraph ” is an interleaved image-text input. The special tokens and indicate the beginning and end of encoded image embeddings. Specifically, we use and to denote start- and end-of-sequence. For input format, we flatten input as a sequence decorated with special tokens.
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