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Hacking on LLMs, curating multimodal datasets, and writing a book about RAG.
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Had a fun time hacking with this model and integrating it into FiftyOne. My biggest gripe is that it's not optimized to return bounding boxes. However, it doesn't do too badly when asking for bounding boxes around text elementsβlikely due to its extensive OCR training. This was interesting because it seems spot-on when asked to place key points on an image. I suspect this is due to the model's training on GUI interaction data, which taught it precise click positions across desktop, mobile, and web interfaces. Makes sense - for UI automation, knowing exactly where to click is more important than drawing boxes around elements. A neat example of how training focus shapes real-world performance in unexpected ways. Shoutout to Vaibhav Srivastav and Merve Noyan for putting it on my radar! Anyways, you can check out the integration with FO here: https://lnkd.in/gsfVHcXT
Shipped an integration with LlamaIndexβs VDR-2B-v1 model into FiftyOne, so you can now search your docuimage dataset using natural language! Check it out and get started here:
Looking forward to being back in Boston!
Voxel51
Join us on April 18 for the Boston AI, ML and Computer Vision Meetup. Reserve your spot: https://lnkd.in/g2hdwGBY Talks will include: * In-House Evaluation is Not Enough. Towards Robust Third-Party Flaw Disclosure for General-Purpose AI - Shayne Longpre at MIT * It Takes a Village: How Parenting Helped Me Understand Model Context Protocol - Rizel Scarlett at Block * RAG with vision based LLM using Vision Language Model (ColPali) - Suman Debnath at Amazon Web Services * Agentic Visual AI: Bridging Autonomous Intelligence and Visual Perception - Harpreet Sahota π₯ at Voxel51 #computervision #ai #artificialintelligence #machinevision #machinelearning #datascience #boston
Looking forward to be back in Boston!
Jimmy Guerrero
Join us on April 18 for the Boston AI, ML and Computer Vision Meetup. Reserve your spot: https://lnkd.in/gd2_qvQA Talks will include: * In-House Evaluation is Not Enough. Towards Robust Third-Party Flaw Disclosure for General-Purpose AI - Shayne Longpre at MIT * It Takes a Village: How Parenting Helped Me Understand Model Context Protocol - Rizel Scarlett at Block * RAG with vision based LLM using Vision Language Model (ColPali) - Suman Debnath at Amazon Web Services * Agentic Visual AI: Bridging Autonomous Intelligence and Visual Perception - Harpreet Sahota π₯ at Voxel51 Got an interesting use case or research project youβd like to share? DM me about speaking opportunities at the next Boston Meetup! #computervision #ai #artificialintelligence #machinevision #machinelearning #datascience #boston
New Llama4 Drop and NVIDIA making it good brrrrrr
NVIDIA AI
π Accelerate performance of AI at Meta Llama 4 Maverick and Llama 4 Scout using our optimizations in #opensource TensorRT-LLM.β‘ β NVIDIA Blackwell B200 delivers over 42,000 tokens per second on Llama 4 Scout, over 32,000 tokens per seconds on Llama 4 Maverick. β 3.4X more performance and 2.6X lower cost compared to Hopper H200.
The first ever Voxel51 meetup in Chicago is popping off! Huge shout out to our speakers: Arjun Patel, Ari Kaplan, Jack Blandin, and Milica Cvetkovic!
The FiftyOne Florence2 Plugin has been revamped! Florence2 is a powerful model and highly slept on! I know it's already several months old, but it's one of my favourites for initial data curation and filtering. With the new updates to the plugin, it's now easier to: - Use the best available device - Leverage float16 for inference is cuda is available - Use the operators via the SDK Enjoy!
Another great turnout at the Boston AI, ML, and CV meetup! Thanks to everyone that came and all the presenters: - Rizel Scarlett (forgot to snap a picture cuz I was in a frantic rush getting my slides together!) - Shayne Longpre - Suman Debnath It was great to see so many familiar faces in the crowd, looking forward to seeing yβall again in June! If youβre in the Boston area and want to give a talk at the next meetup, hit me up!
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