Results for: Generative AI

Adobe has unveiled groundbreaking generative AI innovations at MAX London, expanding creativity for all. The new Photoshop (beta) introduces advanced Generative Fill with Reference Image and Generate Image, shortening the distance between the blank page and stunning results. The Firefly Image 3 Foundation Model advances state of the art for AI image generation, bringing new levels of creative expression and control. Adobe Express mobile apps now bring the magic of Firefly generative AI to mobile, empowering millions to create standout content on-the-go.

Adobe Photoshop has unveiled a major update with breakthrough advancements in Generative Fill. Powered by the new Firefly Image 3 Foundation Model, users now have even greater control over their creations, including the ability to use Reference Image for inspiration and Generate Image directly within their workflows. These features empower creators of all skill levels to bring their vision to life with unmatched speed and precision.

Adobe’s flagship image editing software, Photoshop, is receiving a significant upgrade that harnesses the power of artificial intelligence (AI). This update empowers users to generate images directly within the app using simple text prompts, making image creation more accessible and efficient.

Adobe has announced an update to its Photoshop Firefly generative AI tool, which deepens the integration and vastly expands capabilities through the adoption of a new model: Firefly Image 3 Model. This new model brings several key enhancements, including the ability to use reference images, set a content type, and add effects before generation begins. It also has a better understanding of longer prompts and takes advantage of an improved style engine, resulting in more natural-looking images. Firefly Image 3 model will arrive first in Adobe Photoshop desktop beta and the Firefly web app in beta today, with general availability expected in Photoshop and Firefly later this year.

Generative Artificial Intelligence (AI) is a subsection of AI that uses vast amounts of training data to generate brand-new outputs, which can include text, images, videos, code, data, or 3D renderings. Generative AI models are used to create content that serves different purposes, including entertainment, information, and even problem-solving. They are trained using machine learning techniques and are often powered by large language models (LLMs), such as OpenAI’s GPT-3.5 and GPT-4. Generative AI models are becoming increasingly sophisticated and are finding applications in various fields, such as art, entertainment, education, and research.

Microsoft has introduced VASA-1, a groundbreaking AI model that generates hyper-realistic talking faces from a single photo and audio track. The model has a wide range of applications, including gaming, film making, and education. However, concerns have been raised about its potential for misuse in creating deepfakes.

BlueFocus, a leading Chinese marketing firm, has achieved remarkable financial performance with revenue exceeding CN¥50 billion. The company’s Q1 2024 results show continued growth, with revenue surging by 61.74% year-over-year. BlueFocus is strategically embracing generative AI to address industry challenges and drive innovation. The company aims to become an industrial leader in generative AI by leveraging its scale and fostering imagination space.

Apple is expected to make significant advancements in generative AI, integrating it into its devices without relying on cloud processing. This aligns with the company’s privacy-centric approach and follows industry trends. Apple’s acquisition of Datakalab and upcoming hardware updates suggest a focus on local AI processing and multimodal language models. The iPhone 16 and Macs featuring the M4 processor are likely to debut these AI capabilities, potentially matching industry standards for NPU performance.

As the demand for generative AI (Gen AI) solutions surges, Info-Tech Research Group’s new research provides essential strategies for negotiating Gen AI vendor contracts. With organizations facing challenges in implementing AI tools, the research emphasizes the importance of IT leaders defining responsible AI principles and carefully understanding AI capabilities and risks before negotiating with providers.

Generative AI’s environmental impact has gained attention, particularly its energy and water consumption. Factors such as model size, training intensity, and data center location influence energy usage. Excessive energy use can contribute to climate change and animal habitat loss. Some tech giants are addressing these issues through renewable energy initiatives, power purchase agreements, and improvements in data center efficiency. Water use is also a concern, with data centers requiring large amounts for cooling. IBM and Microsoft are researching innovative water-saving technologies. Despite sustainability goals, concerns remain about carbon offsets and greenwashing practices. Organizations should carefully consider the environmental impact of generative AI and implement strategies to mitigate it.