@MatthewBerman covered our new vision model and speed upgrades. https://
hubs.la/Q02Pz0cr0
MULTIMODAL AI
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New Vision Model and Speed Upgrades Covered by Matthew Berman
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Small Multimodal Model for Food Image Nutrition Analysis
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i want a small multi modal model for converting food pics into nutritional facts
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Human Creativity Irreplaceable Magic Beyond Machine Capabilities
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Agreed, @greetpool
! Our creativity and emotions are what truly set us apart and bring a unique touch that machines simply can’t replicate. It’s this human magic that adds depth and meaning to our work. -
Apple’s Visual Intelligence: AI-powered task automation with your camera
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Tired of juggling all of your daily tasks? @Apple
's new Visual Intelligence will be here to help soon! Automate calendar events, find product info instantly, and even generate recipes from groceries—all with your camera. How could this boost your productivity? #AI -
MiniMax Presents Video-01, Its Revolutionary Text-to-Video Model
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[#Article] The Rise of GenAI in China: MiniMax Unveils Video-01, Its First Text-to-Video Model https://actuia.com/actualite/lessor-de-la-genai-en-chine-minimax-devoile-video-01-son-premier-modele-text-to-video/
… #AI #ArtificialIntelligence -
Aramco Digital Unveils Norous AI Model with Vocal Commands
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"In partnership with Groq…, @Aramco Digital unveiled Norous, an advanced generative AI model that uses vocal commands to increase productivity in the workspace." #GAIN2024
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AI Creates Lifelike Videos: Detecting Synthetic Content
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#AI Can Now Create Lifelike Videos. Can You Tell What’s Real?
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ScribblePrompt: AI-Powered Interactive Image Segmentation Tool
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Authors: Hallee Wong (
@HalleeWong
), Marianne Rakic (
@MarianneRakic
), John Guttag, and Adrian Dalca (
@AdrianDalca
)
Paper: https://
arxiv.org/abs/2312.07381 Website: https://
scribbleprompt.csail.mit.edu
Video: https://
bit.ly/3Tn76Ac -
ScribblePrompt: AI Algorithms Simulate Human Annotation in Medical Imaging
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To train ScribblePrompt, the team used algorithms to simulate how humans would scribble & click on different regions in medical images. In addition to commonly labeled regions, the team also used superpixel algorithms to identify potential new regions of interest to medical
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AI Systems Delineate Medical Image Regions for Biomedical Workers
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To the untrained eye, a medical image like an MRI or X-ray appears to be a murky collection of black-and-white blobs. 🩻
— MIT CSAIL (@MIT_CSAIL) 10 septembre 2024
When trained to understand the boundaries of biological structures, AI systems can delineate regions of interest for biomedical workers. MIT CSAIL, MGH, and… pic.twitter.com/0SGlzN7169To the untrained eye, a medical image like an MRI or X-ray appears to be a murky collection of black-and-white blobs. When trained to understand the boundaries of biological structures, AI systems can delineate regions of interest for biomedical workers. MIT CSAIL, MGH, and