Which among the following is not a Google Generative AI Offering?
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Google Generative AI offerings are not explicitly mentioned in the provided abstracts.
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| Papers (5) | Insight |
|---|---|
| The provided paper does not mention any Google Generative AI offerings. | |
| The paper does not mention any specific Google Generative AI offerings. | |
| The provided paper does not mention any specific Google Generative AI offerings. | |
| The provided paper does not mention any specific Google Generative AI offerings. | |
| The provided paper does not mention any specific Google Generative AI offerings. |
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What can generative AI do?5 answersGenerative AI has diverse capabilities. It can accelerate research in various fields but faces backlash due to copyright concerns, potentially impacting its future legality. In genetics, generative models like GANs and RBMs can create high-quality artificial genomes, aiding in data augmentation, imputation, and encoding for supervised tasks. In drug design, generative models are used to generate novel structures within defined applicability domains, enhancing drug-likeness and fostering industrial adoption. Specifically in de novo drug design, generative models like GANs, autoencoders, and transformers are applied to expand compound libraries, design specific properties, and develop molecular design tools. Overall, generative AI's potential spans from accelerating research and genetic studies to aiding in drug design, albeit with challenges and legal implications.
What is GENERATIVE AI?5 answersGenerative Artificial Intelligence (AI) refers to technology that autonomously creates new content, such as text, images, and code. It leverages Machine Learning and Large Language Models to predict sequential information and generate contextually feasible solutions for users to consider. However, challenges arise regarding traceability of ideas and potential copyright issues when using original creations as training data. Despite these challenges, the generative AI market is rapidly growing, with a projected increase from 1.5 billion dollars in 2021 to 6.5 billion dollars by 2026. Workshops are being conducted to explore the use of Generative AI in design research and practice, aiming to showcase its potential, address ethical considerations, and guide future research directions.
Whats generative AI?4 answersGenerative AI refers to the technology that can autonomously generate new content, such as text, images, audio, and video. It has the potential to enhance the search experience, reshape information generation and presentation methods, and become new entry points for online traffic. Generative AI can produce high-quality artistic media for various fields, including visual arts, music, fiction, literature, video, and animation. It has the capability to fundamentally alter the creative processes and has its own distinct affordances as a new medium. However, there are concerns regarding the use of generative AI, including issues of attribution, compensation, and copyright infringement. Ongoing lawsuits in the United States may have substantial implications for the future of generative AI systems, affecting their legality and use. The integration of generative AI in the IT industry is also transforming the role of IT professionals, impacting their responsibilities, skills, and career prospects.
Is there a lack of an definition of generative ai?5 answersThere is a lack of a common structure for defining generative AI in the context of user interface patterns. While there are dedicated GUI specification languages, they fail to capture the reusability and variability demands of generative user interface patterns. As a result, model-based processes are required to store and define these patterns. On the other hand, in the context of AI in education, there is a focus on chat-based tools and less attention on AI image generation. AI-based image generators have the potential to enhance healthcare education by facilitating self-reflection, emotional intelligence, critical analysis, and dialogue on complex topics. They can also support visual learning and reflection in various educational settings. However, there is a need for nurse educators to find ethical ways to integrate generative AI technologies into educational practices.
What is not generative AI?4 answersGenerative AI refers to the use of artificial intelligence systems that can produce original and creative content such as art, music, literature, and more. It involves the use of algorithms to generate new and unique outputs based on existing data or models. However, not all AI systems fall under the category of generative AI. For example, AI systems that are used for clinical pathways and can produce text that passes plagiarism detectors are not considered generative AI. Similarly, AI systems that are trained on publicly available data and do not have processes in place to return value to data producers and stakeholders are also not classified as generative AI. These systems may have their own distinct purposes and applications, but they do not possess the same generative capabilities as true generative AI systems.
What's new on generative ai ?4 answersGenerative AI, specifically ChatGPT, has gained significant attention and popularity. It reached one million users in just five days after its release. Generative AI, such as generative adversarial networks (GANs), has been successful in synthesizing photorealistic images and has found applications in various fields, including cognitive science. However, the potential for malicious misuse of generative AI in business is still not well understood. Co-creation design fictions with AI engineers have been used to explore the plausibility and severity of business misuse cases. Overall, generative AI is still in its infancy for business use, and more research is needed to understand its full potential and implications.