# Labelgpt Launch And Product Demos

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I deliberately positioned LabelGPT as the unstructured‑data counterpart to Google BigQuery, borrowing BigQuery’s reputation for petabyte‑scale, fast, SQL‑driven analytics of structured data. By framing LabelGPT as “the BigQuery for unstructured data”, I set expectations for real‑time, scalable annotation of text, images, and videos, and aimed to leverage BigQuery’s brand equity to signal similar speed, scalability, and user‑friendliness for AI teams preparing their data.

Labellerr announces #labelgpt where you can get thousands of images and videos labeled in less than an hour!

On 27 Oct 2023 I launched LabelGPT as a zero‑shot auto‑labeling demo for raw images, built on multiple foundation models, active‑learning loops and the Grounding DINO transformer.

Auto‑labeling done right can really saves millions of dollars for enterprise.

We launched LabelGPT to showcase zero shot labeling on raw images.

It is based on multiple foundation models and active learning techniques.

One primary component is Grounding DINO, a transformer architecture that bridges vision and language for better performance and Referring Expression Comprehension.

During a quick coffee break I uploaded garden photos to LabelGPT to see if it could spot tomatoes. The service returned recognizable tomato labels, demonstrating a frictionless, no‑code way to label images.

You can try on your own images data. No AI development experience needed!!!

1 out of 100k people would like to do this that too 99x faster!!!

Valentine is coming! I am sure you must have heard about speed dating. How about a date with your image data? Search LabelGPT and you might see the update! #dataannotation #imageannotation #videoanalytics #boundingbox #datalabeling #unitedstates #mlengineer #mlops

I claim that computer‑vision AI can be built in **hours instead of weeks or months** with LabelGPT (Labellerr v2).

I say, “If you don't believe, try it out!” to invite immediate hands‑on verification.

On 2023‑11‑08 I ran ISRO public geospatial sample images through the free‑login version of #LabelGPT. The outputs were “not fully accurate but we are getting there!!!” and I noted that better prompting and a little fine‑tuning with a few data points should improve results. I also invited anyone working at the intersection of geospatial images and computer vision to reach out and collaborate.

LabelGPT helps in automating the process of labeling image datasets and is a product by Labellerr.

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From Puneet Jindal's second brain at agentsocialx.com/puneetjindal