From Research to Production, Minus the Boilerplate
From Research to Production, Minus the Boilerplate


Why code slow and cautiously when you can iterate on novel research rapidly? Doing breakthrough work requires all of your mental focus. Solving problems using deep learning means constant prototyping and iterating, but currently, this process is painfully slow and requires too much infrastructure and engineering expertise. Your attention is sliced and diced in every which way, where most of the time is spent on infrastructure, not on building models.

In this talk, we'll discuss how PyTorch Lightning is trying to mitigate this problem and remove roadblocks on the journey from Github to deployment, and help researchers and data scientists focus on the research, not engineering.


William Falcon is the creator of the popular open-source project PyTorch Lightning, and the recently announced Grid AI. William created Lightning while doing his PhD at NYU and as a PhD researcher at Facebook AI; Lightning allows users to scale models without the boilerplate and Grid enables large-scale training on the cloud. Previously he co-founded the now acquired NextGenVest and spent time at Goldman Sachs. His PhD (currently on leave to focus on Lightning), is funded by Google Deepmind and NSF Foundation. His research interest is in unsupervised learning and the intersection of AI and neuroscience. William is a native of Venezuela and holds a BA from Columbia University in Computer Science and Statistics, with a minor in Math.

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