Along with the concept of Lightning Apps, Lightning introduces the Lightning Gallery. The Gallery is the community’s one-stop-shop for a diverse set of curated applications and components. The value of the app and component galleries are endless and only limited by the developer’s imagination. For example, there could be components for:

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Lighting AI is the evolution of Grid.ai. The Grid platform enables users to scale their ML training workflows and remove all the burden of having to maintain or even think about cloud infrastructure. Lightning AI takes advantage of a lot of things Grid.ai does well, in fact Grid.ai is the backend that powers Lightning AI. Lightning AI builds upon Grid.ai by expanding further into the world of MLOps, helping to facilitating the entire end-to-end ML workflow. That is how powerful the framework is. It is a platform for ML practitioners by ML practitioners and engineers.

To convert your code to a Lightning App is a seamless task today with some of our convenient components. Both the PopenPythonScript and TracerPythonScript components are near-zero code change solutions for converting Python code to Lightning Apps! See here for all the code changes required to convert this official PyTorch Lightning image classification model to a Lightning App with the TracerPythonScript component.

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Prior to launching Lightning as a product we thought about the need to have some existing apps to give the community a flavor of what can be created and showcase how easy it is.

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By design Lightning AI is a minimally opinionated framework to guard developers against unorganized code and is flexible enough to build cool and interesting AI applications in a matter of days depending on complexity. It is truly a product made for engineers and creatives and built by engineers and creatives.

A great future lies ahead of Lightning AI and we are excited to share you a list of enhancements to come! Within the next months – year we plan to enable the following:

The current problem today is that the AI ecosystem is fragmented, which makes building AI slower and more expensive than it needs to be. For example, getting a model into production and maintaining it takes hundreds, if not thousands, of hours spent maintaining infrastructure. Lightning AI solves this by providing an intuitive user experience for building, running, sharing, and scaling fully functioning Lightning Apps. A nice consequence of this is it will now only take days (not years) to build AI applications.

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Lightning is a free, modular, distributed, and open-source framework for building Lightning Apps where the components you want to use interact together.

Using only these 4 components a fully qualified MLOps pipeline can be built. For example, an anomaly detection app with the following characteristics could be built from them:

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Lightning Apps! Lightning Apps can be built for any AI use case, ranging from AI research to production-ready pipelines (and everything in between!). By abstracting the engineering boilerplate, Lightning AI allows researchers, data scientists, and software engineers to build highly-scalable, production-ready Lightning Apps using the tools and technologies of their choice, regardless of their level of engineering expertise.

We work closely with our vendors to provide high-quality LED lighting for machine vision applications. Visit our PRODUCTS section to discover an LED lighting solution for your vision application and choose "CONFIGURE THIS LIGHT" to customize a light to meet your needs.