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Announcing our latest open medical AI models for developers: MedGemma 1.5, which is small enough to run offline & improves performance on 3D imaging (CT & MRI), & MedASR, a speech-to-text model for medical dictation. Both available on Hugging Face + Vertex AI. #MedGemma #HealthAI #GenerativeAI

Google Research

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395,401 次观看 • 7 个月前 •via X (Twitter)

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Introducing MedGemma, our most capable open model for multimodal medical text and image comprehension. 🩻 MedGemma is available now as part of Health AI Developer Foundations →

Introducing MedGemma, our most capable open model for multimodal medical text and image comprehension. 🩻 MedGemma is available now as part of Health AI Developer Foundations →

Google DeepMind

144,441 次观看 • 1 年前

What’s MedGemma? 🤔 It’s our collection of open, multimodal medical models that are designed to help developers build AI tools for healthcare, such as analyzing radiology images or summarizing notes for physicians. We built this demo using MedGemma to help showcase the possibilities of the model. What other use cases can you foresee for this technology?

What’s MedGemma? 🤔 It’s our collection of open, multimodal medical models that are designed to help developers build AI tools for healthcare, such as analyzing radiology images or summarizing notes for physicians. We built this demo using MedGemma to help showcase the possibilities of the model. What other use cases can you foresee for this technology?

Google AI

65,083 次观看 • 1 年前

Thrilled to release SmolVLM-2, our newest model, which runs entirely on-device and in realtime, offering a strong foundation for healthcare applications. 🤗🔥 With proper domain-specific training, small models enable offline inference of 2D (ECGs, CXRs) and even 3D modalities (CT, MRI) while remaining HIPAA-compliant by design. 🔒 VLMs have come a long way this year and we're excited to share our SoTA solution.

Thrilled to release SmolVLM-2, our newest model, which runs entirely on-device and in realtime, offering a strong foundation for healthcare applications. 🤗🔥 With proper domain-specific training, small models enable offline inference of 2D (ECGs, CXRs) and even 3D modalities (CT, MRI) while remaining HIPAA-compliant by design. 🔒 VLMs have come a long way this year and we're excited to share our SoTA solution.

Cyril Zakka, MD

46,435 次观看 • 1 年前

So much exciting open-source 2d-to-3d research being shared open-source. Here is VAST AI Research implementation of Zehuan-Huang’s paper on Hugging Face Gradio MIDI: Multi-Instance Diffusion for Single Image to 3D Scene Generation

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Matt Hartman

25,113 次观看 • 1 年前

The speech on the FREE open source Sesame text to speech is astonishing. It just killed Google’s voice project for podcasts and the monetization they hoped for. Here is a Hugging Face Gradio link to test: But download it and clone your voice!

The speech on the FREE open source Sesame text to speech is astonishing. It just killed Google’s voice project for podcasts and the monetization they hoped for. Here is a Hugging Face Gradio link to test: But download it and clone your voice!

Brian Roemmele

87,908 次观看 • 1 年前

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Ettore Di Giacinto

55,955 次观看 • 2 个月前

🚀 The Segment Anything Model (SAM) has been upgraded to SAM2, featuring an efficient image encoder for segmenting images and videos. But does SAM2 outperform SAM1 in medical image and video segmentation? We're thrilled to present our paper "Segment Anything in Medical Images and Videos: Benchmark and Deployment"! We comprehensively benchmark SAM2 across 11 medical image modalities and videos. 📄 Paper: 💻 Code: **Highlights:** 1. SAM2 doesn’t always outperform SAM1 in 2D medical images, but excels in video segmentation, making it more accurate and efficient for 3D images, such as CT and MR scans. 2. MedSAM still outperforms SAM2 on most 2D modalities, but SAM2 surpasses MedSAM for 3D image segmentation in a slice-by-slice approach. 3. Segmentation performance varies with model size; sometimes the smallest model outperforms larger ones. 4. Fine-tuning SAM2 significantly boosts its performance for medical image segmentation. While SAM2 may struggle with challenging objects that have unclear boundaries or low contrast, it excels in generating good initial segmentation masks for common medical images and videos. However, the official interface doesn’t support medical data formats and has limitations on video length. To address this, we've developed a 3D Slicer Plugin and Gradio API for efficient 3D medical image and video segmentation. We invite you to try them out and provide feedback! 🔧 Deployment: - 3D Slicer Plugin: - Gradio API: (Note: Due to GPU limitations, the online API is available for only 12 hours and may be slow. We highly recommend deploying the Gradio API with your own computing resources: A big shoutout to Jun Ma (JunMa) who recently joined our UHN AI hub (UHN AI Hub) as Machine Learning Lead, and kudos to all co-authors: Sumin Kim, Feifei Li, Mohammed Baharoon (Mohammed Baharoon), Reza Asakereh, and Hongwei Lyu! This is true teamwork! Looking forward to collaborating with the community to advance 3D medical image and video segmentation foundation models! University Health Network U of T Department of Computer Science Department of Laboratory Medicine & Pathobiology Temerty Centre for AI in Medicine (T-CAIREM) Vector Institute #MedTech #AIinHealthcare #DeepLearning #MedicalImaging #SAM2 #MedSAM #AIResearch

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Bo Wang

178,579 次观看 • 2 年前

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79,673 次观看 • 2 年前

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Arduino

17,109 次观看 • 15 天前

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Poolside

94,338 次观看 • 3 个月前

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WELL3

10,507 次观看 • 1 年前

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Stability AI

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OpenRouter

22,767 次观看 • 21 天前

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Stability AI

1,024,598 次观看 • 2 年前

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elvis

88,518 次观看 • 3 年前

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NVIDIA AI

338,464 次观看 • 2 个月前

Moonshot AI is casually giving developers free daily access to Kimi K3 😳 no subscription no upfront payment just sign in and start using one of the largest open AI models available what you get for $0: - Kimi K3 with 2.8T parameters - 1M token context window - strong coding and reasoning performance - native vision capabilities - free daily credits that refresh automatically why this is worth checking: > access a frontier model without paying API fees > long context for large codebases and documents > works on web, desktop, mobile, and CLI getting started takes less than 2 minutes: 1. go to 2. create a free account 3. Kimi K3 is available as the default model 4. start chatting or coding with your daily free credits bonus: Moonshot Together lets you invite friends for a chance to earn 3, 7, 15, 30, or even 365 days of Kimi Membership through its rewards program benchmark highlights: > 2.8T parameter MoE model > 1M context window > strong performance across coding, browsing, and reasoning benchmarks important: free credits reset daily, rate limits apply on the free tier, and the open-weight release is expected on July 27 A simple way to try one of the latest frontier AI models without paying for API access

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K2S

23,110 次观看 • 1 个月前

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@levelsio

112,930 次观看 • 1 年前

Now available on secondary for .177Ξ, 🔗⤵️ Frag 002, a 1/1 from a series of 10 from the Native collection, a research project in which I set specific visual conditions to invite the AI to express itself, unprompted, using its own perceptual logic This gesture is expressing both Optics Logic and Phantom 3D, the AI behaving as though it’s running its own 3D engine Available at Read more at

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Misfits Studio

18,828 次观看 • 10 个月前