Data Development Platform Encord Expands to Multimodal AI Data Development
Data development platform Encord is going beyond business analysis to become “the world’s only multimodal AI data development platform.”
New Multi-Modal Data Annotation Capabilities
On Thursday, the company announced new multi-modal data annotation capabilities for classifying audio and documents — all in one interface. The update expands on Encord’s existing support for medical, computer vision, and video data.
The Need for Multi-Modal Capabilities
By now, AI chatbots and image generators are relatively commonplace. But it’s much harder to generate convincing video or audio than it is to generate text. The AI industry is focused increasingly on multi-modal capabilities, especially with the release of features like ChatGPT’s Voice Mode.
Fine-Tuning AI Models
To fine-tune an AI model, you need quality — and sometimes hyper-specific — data. Text-based data doesn’t provide the nuance these complex models need, and accuracy is even more important in high-stakes contexts like medicine. Builders need platforms that can annotate and evaluate all kinds of data — video, audio, images, graphs, reports, retail listings, PDFs, and more, ideally in one place.
Encord’s Update
Encord’s update includes new annotation and curation features for documents, audio files, vision, and medical data. With multimodal annotation, AI teams can customize an interface to review and edit different file types side by side. Currently, different data types often are siloed across multiple services and platforms, adding time and costs to data annotation.
Benefits of Encord’s Update
With Encord, AI teams can filter through their data to identify and curate exactly what they need to build a model. Its evaluation dashboard can also flag data that’s hampering a model’s performance so that teams can remove or replace it.
“On average, Encord customers use 35% smaller data sets, which leads to models performing 20% more accurately,” an Encord rep told ZDNET via email.
Artificial General Intelligence (AGI)
Encord co-founder and president Ulrik Stig Hansen told ZDNET that he sees the company’s focus on quality and centralization as eventually enabling artificial general intelligence (AGI).
Conclusion
Encord’s expansion to multimodal AI data development is a significant step forward in the AI industry. By providing a platform that can annotate and evaluate all kinds of data, Encord is helping AI teams build more accurate and effective models. As the company continues to innovate and expand its capabilities, it will be interesting to see how it shapes the future of AI development.
FAQs
Q: What is Encord’s new multimodal data annotation capability?
A: Encord’s new multimodal data annotation capability allows AI teams to classify audio and documents in one interface, expanding on its existing support for medical, computer vision, and video data.
Q: Why is multimodal capability important in AI development?
A: Multimodal capability is important in AI development because it allows AI models to be trained on a wide range of data types, including video, audio, images, and text, which is essential for building accurate and effective models.
Q: How does Encord’s update benefit AI teams?
A: Encord’s update benefits AI teams by allowing them to filter through their data to identify and curate exactly what they need to build a model, and flagging data that’s hampering a model’s performance so that teams can remove or replace it.
Q: What is the potential impact of Encord’s update on the AI industry?
A: The potential impact of Encord’s update on the AI industry is significant, as it could enable the development of more accurate and effective AI models, and potentially even artificial general intelligence (AGI).
