{"id":5646661,"date":"2022-09-20T12:48:57","date_gmt":"2022-09-20T16:48:57","guid":{"rendered":"https:\/\/lightning.ai\/pages\/?p=5646661"},"modified":"2022-12-22T12:23:03","modified_gmt":"2022-12-22T17:23:03","slug":"train-models-synthetic-data","status":"publish","type":"post","link":"https:\/\/lightning.ai\/pages\/community\/announcements\/train-models-synthetic-data\/","title":{"rendered":"Train Machine Learning Models with Synthetic Data"},"content":{"rendered":"

The Lightning App built with NVIDIA Omniverse Replicator (try it for free today!<\/strong><\/span><\/a>) lets you generate synthetic data to enhance the training and performance of your AI models.<\/span><\/i><\/h4>\n

Why did we build the NVIDIA Omniverse Replicator Lightning App?<\/b><\/h3>\n

We built this Lightning App because we’re confident that synthetic data will transform how researchers and engineers train models and implement AI solutions.<\/p>\n

For all the talk about how technology powered by artificial intelligence will automate away many aspects of the way we work, there remains a large obstacle in the way of achieving that automation: data. Data is the beginning \u2013 and, depending on who you ask, the key \u2013 of any machine learning project. That\u2019s because machine learning models, the things that power artificial intelligence, need to learn <\/span>from <\/span><\/i>something. In order for a computer to, say, spot a crack in the windshield of a car or determine whether a human is standing on an oil rig, it has to first learn what those things look like. That means giving a computer thousands (if not more) pictures of cracked windshields to learn from.<\/span><\/p>\n

 <\/p>\n

No data? No project.<\/b><\/h3>\n

But what happens if you don\u2019t have those datasets at your disposal? That’s where synthetic data comes in. You can always go and take a few thousand photos of cracked windshields yourself, but that\u2019s the kind of project that would be an artist\u2019s life work \u2013 not the first step in the agile implementation of a machine learning tool that can automate a process in a factory or garage. In the past, the lack of high-quality, labeled datasets could simply stop a project dead in its tracks.<\/span><\/p>\n

So, what alternatives are there? You can hire a dedicated team to gather, label, and prepare this data to train your model, but that\u2019s a nonstarter if your organization doesn\u2019t have the resources to commit to a project of that magnitude. Whether you\u2019re a solo researcher or a machine learning engineer, acquiring this ground truth data is an expensive, lengthy process that is often subject to human error. Not exactly an automated utopia.<\/span><\/p>\n

 <\/p>\n

More high-quality data, faster.<\/b><\/h3>\n

That\u2019s why we teamed up with NVIDIA to bring NVIDIA Omniverse Replicator, a software development kit for synthetic data generation, to a Lightning App. With it, you can generate physically accurate 3D datasets, complete with ground-truth annotations that can be used to train models \u2013 all from your browser. This gives you access to synthetic data much faster and easier than ever before. You can also run this App on the Lightning Cloud (backed by AWS), or on your own private cluster, if you\u2019re working with stricter compliance guidelines.<\/span><\/p>\n

 <\/p>\n

Lightning + NVIDIA Omniverse Replicator = less time and money spent on data.<\/b><\/h3>\n

If you\u2019re a company looking to streamline a process by implementing artificial intelligence, you no longer need to spend countless hours and a mountain of resources collecting and preparing data. In industries like retail, for instance \u2013 where artificial intelligence has already transformed the way we shop for everything from books to baby food \u2013 synthetically-generated datasets can be used to train models for use in warehouse logistics and inventory management. You can train a machine learning model to spot defective windshields in a factory, all without ever having to crack a single pane of glass yourself.<\/span><\/p>\n

In short, you can use the Lightning App built on NVIDIA Omniverse Replicator<\/a><\/strong><\/span> to generate a dataset for use in any situation where a computer needs to see something \u2013 like AI perception models.<\/span><\/p>\n

Typically, in the past these kinds of tools have only been available to organizations with deep pockets and plenty of resources to spare. In our ongoing efforts to expand access to the tools that are defining the next generation of industry, this Lightning App is available for use by anyone, anywhere. You don\u2019t need to spend countless hours and resources building your own solution \u2013 we\u2019ve done that for you.<\/span><\/p>\n

 <\/p>\n

Try the Lightning App for free today!<\/a><\/span><\/strong> We\u2019re always on the lookout for the amazing things our community creates with Lightning. Get in touch by joining our Slack<\/a><\/span><\/strong>, whether you want to give us feedback or show off what you\u2019ve built.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

The Lightning App built with NVIDIA Omniverse Replicator (try it for free today!) lets you generate synthetic data to enhance the training and performance of your AI models. Why did we build the NVIDIA Omniverse Replicator Lightning App? We built this Lightning App because we’re confident that synthetic data will transform how researchers and engineers… Read more »<\/a><\/p>\n","protected":false},"author":16,"featured_media":5646662,"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":[96,97,100,99],"glossary":[],"acf":{"additional_authors":false,"hide_from_archive":false},"yoast_head":"\nTrain Machine Learning Models with Synthetic Data - Lightning AI<\/title>\n<meta name=\"description\" content=\"This Lightning App built on NVIDIA Omniverse Replicator lets you generate synthetic data to enhance the training of your AI models.\" \/>\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\/train-models-synthetic-data\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Train Machine Learning Models with Synthetic Data - Lightning AI\" \/>\n<meta property=\"og:description\" content=\"This Lightning App built on NVIDIA Omniverse Replicator lets you generate synthetic data to enhance the training of your AI models.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/lightning.ai\/pages\/community\/announcements\/train-models-synthetic-data\/\" \/>\n<meta property=\"og:site_name\" content=\"Lightning AI\" \/>\n<meta property=\"article:published_time\" content=\"2022-09-20T16:48:57+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2022-12-22T17:23:03+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/lightningaidev.wpengine.com\/wp-content\/uploads\/2022\/09\/NVIDIA.png\" \/>\n\t<meta property=\"og:image:width\" content=\"2320\" \/>\n\t<meta property=\"og:image:height\" content=\"1200\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"JP Hennessy\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:image\" content=\"https:\/\/lightningaidev.wpengine.com\/wp-content\/uploads\/2022\/09\/NVIDIA.png\" \/>\n<meta name=\"twitter:creator\" content=\"@LightningAI\" \/>\n<meta name=\"twitter:site\" content=\"@LightningAI\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"JP Hennessy\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"4 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/lightning.ai\/pages\/community\/announcements\/train-models-synthetic-data\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/lightning.ai\/pages\/community\/announcements\/train-models-synthetic-data\/\"},\"author\":{\"name\":\"JP Hennessy\",\"@id\":\"https:\/\/lightning.ai\/pages\/#\/schema\/person\/2518f4d5541f8e98016f6289169141a6\"},\"headline\":\"Train Machine Learning Models with Synthetic Data\",\"datePublished\":\"2022-09-20T16:48:57+00:00\",\"dateModified\":\"2022-12-22T17:23:03+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/lightning.ai\/pages\/community\/announcements\/train-models-synthetic-data\/\"},\"wordCount\":712,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/lightning.ai\/pages\/#organization\"},\"image\":{\"@id\":\"https:\/\/lightning.ai\/pages\/community\/announcements\/train-models-synthetic-data\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/lightningaidev.wpengine.com\/wp-content\/uploads\/2022\/09\/NVIDIA.png\",\"keywords\":[\"ai\",\"ml\",\"nvidia\",\"synthetic data\"],\"articleSection\":[\"Announcements\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/lightning.ai\/pages\/community\/announcements\/train-models-synthetic-data\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/lightning.ai\/pages\/community\/announcements\/train-models-synthetic-data\/\",\"url\":\"https:\/\/lightning.ai\/pages\/community\/announcements\/train-models-synthetic-data\/\",\"name\":\"Train Machine Learning Models with Synthetic Data - 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