{"id":5646569,"date":"2022-09-08T13:42:33","date_gmt":"2022-09-08T17:42:33","guid":{"rendered":"https:\/\/lightning.ai\/pages\/?p=5646569"},"modified":"2023-10-03T07:43:06","modified_gmt":"2023-10-03T11:43:06","slug":"pytorch-at-lightning-welcome-mike-ruberry","status":"publish","type":"post","link":"https:\/\/lightning.ai\/pages\/community\/announcements\/pytorch-at-lightning-welcome-mike-ruberry\/","title":{"rendered":"PyTorch Team at Lightning – Welcome Mike Ruberry"},"content":{"rendered":"

\"\"<\/p>\n

Today, I’m thrilled to share that Mike Ruberry, one of PyTorch’s core technical leads, will be joining Lightning.<\/h4>\n

If you\u2019re a PyTorch user, you\u2019ve benefited directly from Mike Ruberry\u2019s work. Today, I\u2019m super excited to announce the creation of the PyTorch Team at Lightning<\/a><\/span> (formerly known as PyTorch Lightning) that Mike will be leading.<\/p>\n

Mike Ruberry, a PyTorch core technical lead who\u2019s been with the project for over four years, joins us as the first member and Chief Engineer of the PyTorch Team at Lightning. Mike shares my passion (and that of our CTO Luca \u2014 more from him in a bit) for making PyTorch the go-to framework for deep learning. On behalf of the Lightning community, Luca and I are thrilled to welcome Mike Ruberry to Lightning AI!<\/p>\n

Some highlights of Mike\u2019s work at PyTorch include shepherding the design and upstreaming of automated mixed precision (AMP), efforts to make PyTorch consistent with NumPy, including the creation of torch.fft<\/a>, torch.linalg<\/a><\/span> and torch.special<\/a>.<\/span> Most recently, he\u2019s been focused on how PyTorch programs are represented to ensure they are fast and composable.<\/p>\n

Over the years, Mike and I have been building a bridge between the Lightning community (join our Slack here<\/a><\/span>) and the core PyTorch team at Meta, in order to improve usability for the PyTorch community. We did this by removing blockers and simplifying the API for scalable model development and deployment. Today, this sentiment is one we\u2019ve embraced in our community, to make it one of the most vibrant places to learn from each other, collaborate and collectively push AI forward.<\/p>\n

\u00b7 \u00b7 \u00b7<\/p>\n

PyTorch at Lightning<\/h2>\n

The PyTorch Team at Lightning is a major milestone in our community\u2019s evolution. It\u2019ll allow us to build on lightning.ai<\/a>,<\/span> which we launched earlier this year: a platform that provide templates for machine learning workflows. These templates allow you to connect AI models with the ML lifecycle \u2014 all without handling DIY infrastructure, cost management, scaling, and other headaches. The PyTorch Team at Lightning\u2019s mission is to not only deliver the best PyTorch + Lightning combination, but to help shape the direction of PyTorch itself.<\/p>\n

From day 1 in 2015, when I started working on Lightning for my own research as an undergrad, I believed that PyTorch\u2019s fundamental different approach to building ML would make it the dominant framework in deep learning. Today, my conviction is 100x stronger. First, the research community adopted it, and now enterprises have also followed suit. Even though PyTorch adoption is great, we\u2019re aware that there\u2019s always room to enhance the framework and make it even better for the community. We believe PyTorch has the ability to become bigger, better, faster, easier to use and more extensible. These are the core principles that the PyTorch team at Lightning will be pursuing. Our friend Soumith Chintala, core maintainer at Meta, summed it up best when he said, \u201cHaving a PyTorch core team balanced among many stakeholders is fundamental to our success. I’m really happy to see a PyTorch team at Lightning, and I couldn’t think of a better person to kick it off than Mike Ruberry.\u201d<\/p>\n

\u00b7 \u00b7 \u00b7<\/p>\n

By Researchers, for Researchers<\/h2>\n

I chose PyTorch to power Lightning because of its flexibility, and the fact that it was written by<\/strong> researchers for<\/strong> researchers. Today, our team is humbled to find that over 46% of PyTorch users use Lightning alongside it. As a researcher, this is the foundational idea behind Lightning: a framework designed first for flexibility, and that has now evolved to power some of the largest production systems in the world, ranging from core products at Meta to Amazon Search.<\/p>\n

As we invest in PyTorch as the framework to power Lightning, we decided to build an in-house team who have been crucial in shaping the project\u2019s trajectory. With our CTO Luca Antiga as an early key contributor to PyTorch, the addition of Mike Ruberry signals the start of a deliberate effort to formalize a proper PyTorch Team at Lightning.<\/p>\n

Meta has been a design partner on Lightning since I left FAIR in 2019. Today we\u2019re creating this new team to further the collaboration and work on the core framework together. Mike, Luca and I are personally excited to reaffirm our commitment to PyTorch as the ideal framework to power Lightning today, and to ensure that the PyTorch and Lightning teams collectively towards the success of the ML community.<\/p>\n

\u00b7 \u00b7 \u00b7<\/p>\n

A Word from Luca Antiga, our CTO<\/h2>\n

Ever since PyTorch was released in early 2017 and I started contributing to it in the early days, I\u2019ve always been amazed by the developer-first stance that the creators of PyTorch took very early on, and the strong community ethos that came with it. I believe that this is one of the key reasons why PyTorch powers much of the AI landscape today, beyond the technical achievements.<\/p>\n

Lightning was born on very similar core principles and this has always been a strong motivating factor for me. The value we place on the community allows researchers to participate in shaping their favorite framework, and more recently to extend their reach from building models to building entire AI products end-to-end.<\/p>\n

Today, with Mike joining and the PyTorch team at Lightning kicking off, we have the concrete opportunity to help propelling PyTorch into the future, and at the same time to establish our vision for Lightning as the best framework for developers and AI creators.<\/p>\n

Ever since I stopped being a core contributor to PyTorch in late 2018, I\u2019ve been mesmerized at the progress that the core PyTorch team has made and how far the project has evolved. This was thanks to an exceptional team of researchers and engineers that worked at very hard problems while keeping the experience for users consistent. One of most prominent figures among those was and still is Mike, and I feel extremely fortunate to have the opportunity to work alongside him today, improving PyTorch and making sure Lightning leverages its evolutions.<\/p>\n

I can\u2019t wait for what the next few months will unlock, for PyTorch, for Lightning and for the combination of the two.<\/p>\n","protected":false},"excerpt":{"rendered":"

Today, I’m thrilled to share that Mike Ruberry, one of PyTorch’s core technical leads, will be joining Lightning. If you\u2019re a PyTorch user, you\u2019ve benefited directly from Mike Ruberry\u2019s work. Today, I\u2019m super excited to announce the creation of the PyTorch Team at Lightning (formerly known as PyTorch Lightning) that Mike will be leading. Mike… Read more »<\/a><\/p>\n","protected":false},"author":23,"featured_media":5646623,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[101],"tags":[96,97,51],"glossary":[],"acf":{"additional_authors":false,"hide_from_archive":false,"mathjax":false,"default_editor":true,"show_table_of_contents":false,"content_type":"Blog Post","sticky":false,"code_embed":false,"tabs":false,"custom_styles":""},"yoast_head":"\nPyTorch Team at Lightning - Welcome Mike Ruberry - Lightning AI<\/title>\n<meta name=\"description\" content=\"Mike Ruberry, one of PyTorch's core technical leads, brings his deep expertise to lead the expanding PyTorch team at Lightning AI.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/lightning.ai\/pages\/community\/announcements\/pytorch-at-lightning-welcome-mike-ruberry\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"PyTorch Team at Lightning - 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