Hey ,
We've been working hard on the open-source visual data ETL tool VDP for the last few months. A lot of gooooodies π¬ π° π§ to share with our community!
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VDP: the future for unstructured data ETL
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A few months ago, we announced that we're building VDP, an open-source data tool to streamline the end-to-end visual data processing pipeline:
- Extract unstructured visual data from pre-built data sources such as cloud/on-prem storage, or IoT devices
- Transform it into analysable structured data by Vision AI models
- Load the transformed data into warehouses, applications, or other destinations
We believe VDP is the future for unstructured data ETL, where developers won't need to build their own data connectors, high-maintenance model serving platform or ELT pipeline automation tool.
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Pre-built ETL data connectors
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VDP integrates with Airbyte to provide open-source data connectors.
By leveraging the pre-built and ready-to-use data connectors, VDP is the single point of visual data integration. You can sync visual data from anywhere into a centralised warehouse and focus on gaining insights across all your data sources, instead of maintaining pipelines.
π Learn more
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VDP integrates with the best ML tools to make importing models super easy.
No need to change how you manage your models. No matter the model is on your computer, in a GitHub or Hugging Face repository, or in cloud storage managed by version control tools like ArtiVC or DVC, import & deploy it with one click π±οΈ.
π Learn more
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Data pipelines for diverse scenarios
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VDP supports data pipelines for diverse scenarios - no need to build from scratch
β‘ SYNC mode for real-time tasks: process your data with HTTP or gRPC APIs to get results immediately, suitable for tasks that have low-latency requirements.
π ASYNC mode for on-demand workload: set up your data pipeline to process data on demand or schedule, so it processes data only when the trigger criteria are met.
π Learn more
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Standardise Computer Vision tasks
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VDP solves popular vision tasks out of the box:
- Image classification
- Object detection
- Keypoint detection
- OCR (coming soon!)
- The list is growingβ¦π±
For each task, you can import corresponding STOA models into VDP to use in the data pipelines. The prediction results are automatically converted to a standardised format ready for future analysis.
π Learn more
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The Console provides a unified, clean and intuitive user experience of VDP without writing any code.
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Build end-to-end data pipelines 10x faster
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With VDP, you can build an end-to-end pipeline to connect your visual data, convert them to structured insights and send the results to your database in less than 5 minutes. Click here to get started.
To learn more, please check the VDP documentation.
Give VDP a β for future updates and π join our community.
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Instill Cloud - fully managed VDP (coming soon!)
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βοΈ We offer fully managed VDP service on Instill Cloud (coming soon!) with Team and Enterprise tiers to organisations that want to get all the power of VDP for their teams, without any hassle.
- Painless setup
- Maintenance-free infrastructure
- Production-ready services
- Start for free, pay as you grow π±
Access to Instill Cloud is currently by invitation only. If you're interested in the hosting service of VDP, join the waitlist and we'll contact you when we're ready.
Our mission is to make Vision AI accessible to everyone. If you are from academic groups and have any showcase of Vision AI in your research, please fill out the form to tell us about yourself and your project, and we will be in touch π.
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π Community for Vision AI Enthusiasts
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YOLOv4 vs. YOLOv7 demo powered by VDP
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We've built this live demo to play around with VDP and the STOA object detectors. You can compare the performance of YOLOv4 and YOLOv7 side-by-side.
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Interested in whatβs behind the curtains? VDP provides a model inference server out of the box to serve as the foundation for building real-world vision applications.
For the demo, we built two VDP pipelines with YOLOv4 and YOLOv7 respectively. By triggering them with low-code, the inference results are sent and displayed on the demo.
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#HowToGrow series for Data/AI practitioners
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In the last few years, we observed the converging of Data and AI. New practices, new toolings, and even new roles with shifting responsibilities are emerging.
As Vision AI practitioners, we are optimistic and excited, but we also see the whole ecosystem in a frenzied state. How do we understand each other, find the common ground to collaborate, and move forward together in this big messy fun world?
That's why we started the #HowToGrow series where experienced practitioners share valuable lessons from their Data and AI journey ο»Ώπο»Ώ.
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π‘ How to ο»Ώgrow as an AI Researcher?
By Xiaofei Du, Co-founder & COO @ Instill AI
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In 7 years of working as an AI researcher (4-year PhD + 3 years at AI/CV startup) and 2 years of do-a-bit-of-everything (AI eng, backend, frontend, PM, etc.), here are three lessons I've learnt along the way:
βΆ Learn more about data pipeline to have better control of your data
β· Explain your work on a common ground
βΈ Prove the value of your work: avoid optimal on paper, broken in reality
ο»Ώπο»Ώ Continue reading
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π‘ How to ο»Ώgrow as an AI Engineer?
by Nguyα»
n VΔn TΓ’m, AI Engineer @ Instill AI
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After 7 years of working as a software engineer (firmware/middleware, mobile and backend application), I switched to AI engineer role 4 years ago. Here are my takeaways from a +10-year software industry journey:
β
βΆ Polish your MLOps tooling skill
β· Monitor production domain drift and iterate fast
βΈ Collaborate across different roles
ο»Ώπο»Ώ Continue reading
We'd love to hear more about your story. What's your most valuable lesson? What frustrates you most in your daily work? Share your story on Twitter and tag us @instill_tech  !
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Stay tuned and stay well!
Cheers π»,
Xiaofei
Co-founder & COO @ Instill AI
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