At Ripplix, we’re passionate about the small details that make digital products truly delightful. In a world filled with interfaces, it’s often the subtle animations and thoughtful micro-interactions that create a lasting impression. They make apps feel alive, guide users effortlessly, and elevate the overall experience.
At Ripplix, we’re passionate about the small details that make digital products truly delightful. In a world filled with interfaces, it’s often the subtle animations and thoughtful micro-interactions that create a lasting impression. They make apps feel alive, guide users effortlessly, and elevate the overall experience.
Lightning AI is the company behind PyTorch Lightning, the deep learning framework for training, finetuning and serving AI models (80+ million downloads).
PyTorch Lightning started in 2015 by Lightning founder William Falcon while working on computational neuroscience research at Columbia University scaling Generative Adversarial Networks and Autoencoders in the context of neural decoding working under Liam Paninski. He open sourced it in 2019 while pursuing a PhD in self-supervised learning (SSL) at NYU and Facebook AI Research (FAIR) supervised by Kyunghyun Cho and Yann Lecun. SSL techniques are at the heart of models like Chat GPT (next word prediction).
In 2019 PyTorch Lightning started to be used to train huge models on 1024+ GPUs inside Facebook AI. Today, it’s used by over 10,000 companies and 1+ million developers to train, finetune and deploy the world’s largest models.
Lightning AI started in 2020 as a platform to train models on the cloud across 1000s of GPUs. Today, the platform has evolved to a fully end-to-end platform covering everything from distributed data processing, training, finetuning foundation models, to serving and deploying AI apps.
Lightning Studios expand on PyTorch Lightning’s core ethos of “You do the science, we do the engineering” by delivering the world’s most intuitive, easy to use, fastest platform for working on AI. From prototyping research ideas to deploying foundation models.
Lightning AI is the company behind PyTorch Lightning, the deep learning framework for training, finetuning and serving AI models (80+ million downloads).
PyTorch Lightning started in 2015 by Lightning founder William Falcon while working on computational neuroscience research at Columbia University scaling Generative Adversarial Networks and Autoencoders in the context of neural decoding working under Liam Paninski. He open sourced it in 2019 while pursuing a PhD in self-supervised learning (SSL) at NYU and Facebook AI Research (FAIR) supervised by Kyunghyun Cho and Yann Lecun. SSL techniques are at the heart of models like Chat GPT (next word prediction).
In 2019 PyTorch Lightning started to be used to train huge models on 1024+ GPUs inside Facebook AI. Today, it’s used by over 10,000 companies and 1+ million developers to train, finetune and deploy the world’s largest models.
Lightning AI started in 2020 as a platform to train models on the cloud across 1000s of GPUs. Today,...
Ripplix focuses on enhancing user experience through subtle animations and micro-interactions, making it ideal for creating delightful digital products. In contrast, Lightning AI is specifically designed for building, training, and deploying AI models, offering features like end-to-end AI solutions and the ability to scale models across multiple GPUs. If your primary goal is to develop AI applications, Lightning AI would be the better choice.
Lightning AI provides collaboration features that allow teams to work together on the cloud, making it highly suitable for collaborative AI development. Ripplix, while focused on enhancing user interfaces, does not emphasize collaborative features for AI development. Therefore, for teamwork in AI projects, Lightning AI is the more appropriate platform.
Ripplix excels in creating engaging user experiences through its focus on micro-interactions and animations, which can make applications feel more intuitive and alive. Lightning AI, however, is primarily focused on the technical aspects of AI model training and deployment. If user experience is a priority for your project, Ripplix may have the edge, but for AI functionality, Lightning AI is more specialized.
Ripplix is a digital product design company that focuses on enhancing user experiences through subtle animations and thoughtful micro-interactions. Their goal is to create delightful interfaces that make apps feel alive and guide users effortlessly.
Ripplix stands out in digital product design by emphasizing the small details that contribute to a delightful user experience. They believe that subtle animations and micro-interactions can significantly elevate the overall experience of an app, making it more engaging and intuitive for users.
Currently, there are no user-generated pros and cons available for Ripplix. However, based on their focus on enhancing user experience through thoughtful design, one could infer that the pros may include improved user engagement and satisfaction. The cons are not specified at this time.
Lightning AI is the company behind PyTorch Lightning, a deep learning framework for training, finetuning, and serving AI models. The platform offers a comprehensive end-to-end solution for AI development, from distributed data processing and model training to deployment and serving AI applications.
Pros of Lightning AI include the ability to build end-to-end AI solutions, scale models to dozens of GPUs with just a few clicks, and collaborate with your team on the cloud. Currently, no cons have been listed.
PyTorch Lightning was founded by William Falcon in 2015 during his computational neuroscience research at Columbia University. He open-sourced the project in 2019 while pursuing a PhD at NYU and Facebook AI Research (FAIR).
PyTorch Lightning is used for training, finetuning, and deploying AI models. It is utilized by over 10,000 companies and more than 1 million developers to handle large-scale models on extensive GPU clusters.
The core ethos of Lightning Studios is 'You do the science, we do the engineering.' This philosophy aims to provide an intuitive, easy-to-use, and fast platform for AI research and deployment, enabling users to focus on scientific innovation while Lightning Studios handles the engineering complexities.
