Powering Breakthrough Vision AI with MLOps.

San Francisco
Joined January 2020
Datature retweeted
The @nvidia Cosmos Cookoff is here - a 4-week physical AI challenge that could reshape how we approach autonomous systems, and for us it's especially exciting since our CPO and Co-Founder @eranshir is judging alongside experts from @DatatureAI , @huggingface, and @nvidia. This isn't just another AI competition. With NVIDIA Cosmos Reason 2 and real-world validation requirements, teams will tackle the hardest problems in robotics and AV development - egocentric reasoning, traffic-aware models, and physical plausibility checks. Eran brings a unique perspective: while others simulate edge cases, Nexar has captured them from 10B+ miles of real-world driving. That's the foundation serious AV development needs. The industry is finally recognizing what forward-thinking leaders like Eran have advocated for years - simulated data isn't enough. Real roads demand real models. Jan 29 - Feb 26. Solo or teams up to 4. $5K grand prize plus NVIDIA DGX Spark. Sign up, and be a part of the future building the future of physical AI: luma.com/nvidia-cosmos-cooko… #PhysicalAI #Robotics #AV #EdgeCases #AIChallenge
🧑🏻‍🍳 Introducing the NVIDIA Cosmos Cookoff — a virtual, four-week physical AI challenge for robotics, AV, and vision AI builders, sponsored by @nebiusai and @milestonesys. Build with NVIDIA Cosmos Reason 2 and Cosmos Cookbook recipes—from egocentric robot reasoning to physical plausibility checks and traffic‑aware models. 🗓 Jan 29 – Feb 26 👥 Solo or teams (up to 4) 🏆 Prizes include $5,000, an NVIDIA DGX Spark, and more! 🧑‍⚖️ With judges from @DatatureAI, @huggingface, @nebiusai, @getnexar, and @nvidia Sign up and show what’s possible with physical AI ➡️ nvda.ws/3Z9lrCO
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ARBOR Technology Corp., a developer of Industrial Internet of Things (IIoT) and edge AI computing solutions, has formed a strategic alliance with @DatatureAI and MemryX Inc. #MachineVision #AI #Software Read more here: photonics.com/Articles/ARBOR…
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One of the most requested features on @DatatureAI is finally here 🎉 Our new t-SNE Embedding Visualization lets you instantly see how your #datasets cluster - making it easier to spot duplicates, catch anomalies, and speed up labeling. Really excited for our community to start using this → it’s been on the wishlist for a long time, and the team delivered 🚀
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Thanks @gkeechin & @DatatureAI for becoming @albumentations ' Silver sponsor. Appreciate the support for the project. Every dollar counts.
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At @DatatureAI we’re excited to announce IntelliMatch — our newest tool, powered by DETR and patch-prompting, designed to speed up annotation by detecting similar objects across scenes! ⚡ Perfect for Medical, Manufacturing, and Agriculture use cases with repetitive objects. Available now in early access - 🧵
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It's finally in ⚡️ At @DatatureAI, we are thrilled to announce the integration of Meta's Segment Anything Model 2 (SAM-2) into our annotator interface for advanced object segmentation in video #datasets Teams working with video datasets will experience significantly faster labeling and higher mask accuracy thanks to our latest video object tracking feature, powered by the updated Intellibrush with SAM-2 as its backbone. Kudos to the @AIatMeta team for open-sourcing such incredible technology, enabling developers to build critical applications for developers ⚡️ Here's a preview of the enhanced features, and we look forward to bringing more innovations to our users 👇
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20-Hour Mark Update - Integrated SAM-2 into our annotator interface for object segmentation in video #datasets 🏀 If you have a video dataset that you'd like to expedite labeling and run your model training on, ping me for early access - we could use some feedback on this feature!
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RT @gkeechin: Exciting news!☝️ @DatatureAI now supports @metaai Segment Anything Model 2 on our platform! Label your #computervision datas…
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Replying to @AIatMeta
@AIatMeta's Segment Anything Model 2.0 (SAM-2.0) is a groundbreaking advancement in computer vision, supporting real-time object segmentation in both images and videos. Here’s an in-depth look at what are the key differences with the previous SAM / 🧵
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Honored to speak at @superai_conf 2024 on the history of #computervision and #visiontransformers, especially around our experiments with PaliGemma. Proud to showcase how the @DatatureAI Team is pioneering fine-tuning to solve complex industry challenges! 🚀
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🚀 In an exciting step to introduce #AI to asset inspection, @trendspek and @DatatureAI develop a proof-of-concept to autodetect concrete cracks in large infrastructure. "We're looking at reducing a 100-hour process down to 3 hours" 👉 Read more: trendspek.com/blog/trendspek…
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Most folks might not know that there are different types of model pruning techniques. In our latest article, we showcase some of these distinctions, and explain why they matter. Delve into why pruning your models can be crucial for some applications 👇 datature.io/blog/a-comprehen…
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Thrilled to see that our #deeplearning technologies at @DatatureAI are poised to revolutionize the construction industry. Our cutting-edge vision models will soon be deployed in factories in #Thailand for early testing. Driving their #SmartFactory ambitions forward! 🇹🇭
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What's the catalyst for AI tools to gain large scale adoption? No code AI platforms for non technical users 1. Familiar drag & drop functionality like @DatatureAI 2. Wizard based systems like @AkkioHQ #Nocode is where the fun starts for non techs using AI
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The New Tool to Label Data 10x Faster by @ambervteng buff.ly/3KwTYTw
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Sharing my latest article about a cool new tool I found to label data 10x faster! Hope you guys can give it a read :) link.medium.com/5X3DpmGISsb @DatatureAI
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I've always loved using #TensorBoard for my #tensorflow experiments - especially when looking at the embedding projectors, images, and scalar tabs Today, we release a new feature that allows you to take the same, deep look into your #deeplearning models training performance ..🧶
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Two simple, but important toggles added to our augmentation preview✌️ @DatatureAI users have been asking for a way to check the sanity of their augmentation pipelines, with and without annotations. Now you can! Next up → Shuffling Images #NeuralNetworks #MachineLearning
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We just launched Intellibrush over at @ProductHunt ⚡️ (1/2) 🧶 Intellibrush allows developers to label complex objects in images with a few clicks. If you are a #MachineLearning engineer - definitely give Intellibrush a spin 👇 producthunt.com/posts/intell…
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