Best Deep Learning Frameworks
This list encompasses various deep learning frameworks that facilitate the development and training of machine learning models. These frameworks provide essential tools and libraries, enabling researchers and developers to implement complex algorithms and streamline their workflows in the field of artificial intelligence.
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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.
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