Contents
TLDR
Workflows Leaves Beta
Editor Power Ups
AI Support
Active Improves Data Curation and Model Evaluation
Label Snapshot Versioning
Opt-in to Beta Features Faster with Encord Labs
Encord Blog
Product Updates [October 2023]
TLDR
- Workflows leaves Beta!
- Label snapshot versioning
- AI support is now in the platform - instant-access to support
- Encord Active improves Data Curation, Model Observability
- Introducing Encord Labs
- Encord @ RSNA - Come and see us at Booth #3772!
All this and more! Read on to make your day.
Workflows Leaves Beta
We are thrilled to announce that our highly-anticipated feature, Workflows, has officially transitioned from beta to general availability! This milestone could not have been achieved without the invaluable feedback from our dedicated users throughout the beta phase.
Workflows are designed to give you full control of the annotation process, ensuring a blend of high performance, usability, and extensibility that scales with the rapid pace and change of the AI industry. Some of the major improvements are:
- Performance: Handle larger projects efficiently (a tenfold increase from the previous benchmark), with significant speed enhancements across the platform.
- Usability: A new drag-and-drop UI simplifies workflow creation and the updated queue gives you full insight into the progress of your project.
- Extensibility: Advanced routing, better review functionality, and integration with Encord Active tailored to evolving AI demands.
Editor Power Ups
Workflow scalability means more tasks and more labels in your annotation projects. We're also juicing up the editor to be more performant -- which means more labels per task, faster. Backend improvements mean your data will save faster and more seamlessly, and we're introducing raised limits on labels per task to benefit from those improvements as well -- contact us to work with more data per task! Arriving soon are further performance improvements to enhance the user experience when dealing with many objects and complex label timelines. This all adds up to create a more natural pre-processing and editing experience, even on long, label intense, video annotation workloads. Exciting!
AI Support
We understand that searching our documentation isn’t always your first thought when you need to learn about the platform. To address this, we've integrated AI support directly into our platform, ensuring you have quick access to the assistance you need, precisely when needed.
Whether you're onboarding for the first time, looking for a quick refresher on using the Label Editor, or need help understanding terminology, our AI assistant is here to help. It is regularly trained on all our platforms & SDK documentation, enabling it to provide intelligent and up-to-date responses to any questions you may have about our application!
Active Improves Data Curation and Model Evaluation
We know that curating the best images, frames from a video, or slices from a scan is a daunting, difficult, and time-intensive task. First, ensuring that your dataset is free of outliers, duplicates, and irrelevant images, and second, selecting the best samples is crucial for building robust and performant models.
Encord is your trusted partner along your journey and based on your feedback we have designed Active's new Explorer to simplify this process, incorporating best practices into intuitive user journeys:
- Automated data quality checks: Active automatically identifies potential issues in your datasets, such as duplicates, blurry images, or corrupted frames. By filtering out these problematic frames, you can reduce annotation costs and prevent detrimental effects on your model's performance.
- Intelligent curation: Use Active to curate a balanced and diverse dataset. Whether you're establishing a dataset for an initial model run or curating targeted data for critical edge cases or blind spots, Active has a tailored workflow ready for you.
After your data is annotated and your model is trained, Encord Active simplifies the shift to evaluation. Simply import your model predictions and access a detailed analysis of your model’s performance, with options to break it down by class, data collections, and splits such as train, test, and validation.
You can also use the Explorer to investigate your prediction types following a series of best-practice workflows:
- Prediction inspection: Use the Explorer to delve into the types of model predictions – True Positives (TP), False Positives (FP), and False Negatives (FN), to understand your model's accuracy and behavior.
- Spot and address blind spots: When an edge case or a blind spot is detected, Active's similarity search allows you to surface and curate additional samples from your unlabeled data pool that resemble these critical cases.
- Continuous improvement cycle: Integrate these new samples into your annotation workflow, retrain your model, and directly compare performance improvements against previously identified edge cases.
Label Snapshot Versioning
Labeling training data is, like the model training process it supports, an iterative process. You’ve asked for ways to snapshot your progress — whether it’s to save a checkpoint before re-labeling, check-in progress as you work through a large project, or name different subsets for purposes such as training, testing, and validation. We’ve listened, and are happy to introduce label versioning for workflow projects. Navigate to the labels tab, select your tasks, and press ‘Save new version’ — you can refer to these snapshots by name and time.
Initially, we’re rolling out support for exporting labels from saved checkpoints, but look out for coming improvements such as restoring to different projects. As always, let us know how it helps and what more we can do to enhance your AI initiatives with labels and label set management tools!
Opt-in to Beta Features Faster with Encord Labs
Many of you have shown interest in working closely with our product development team and helping us create the best features — as such, we’re very happy to be introducing Encord Labs! Encord Labs will give you access to features at the bleeding edge, but give you control over how features appear in the platform. This means you will get all the power of rapidly evolving technology with none of the risks. Getting in on the ground floor means you can shape how features evolve faster, helping us ensure we build with tight customer feedback in mind. Encord Labs will be rolling out several select features in Q4 — contact us if you’re interested or would like to join our collaborative early tester program!
Thanks for reading, feel free to email product@encord.com with any questions or suggestions, and let us know if you're attending RSNA 2023!
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Justin Sharps
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