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newsVirgo Transforms Endoscopy with AI-Driven Foundation Model EndoDINO to Improve Precision Medicine
AI assistants, AI models, Algorithms, Americas, Analytics, Artificial Intelligence, Healthcare, Machine learningSheryl Rivera
academic medical centers, AI, AI Benchmarks, anatomical landmark classification, artificial intelligence, AutoIBD, clinical outcomes, clinical trials, DINOv2, disease severity scoring, Dr. Ali Soroush, EndoDINO, EndoML, endoscopic procedure videos, endoscopy, feature extractor, foundation model, gastroenterology, HIPAA-compliant platform, IBD, Icahn School of Medicine, inflammatory bowel disease, Matt Schwartz, Meta, Mount Sinai, pharmaceutical companies, polyp segmentation, precision medicine, real-time detection, remission prediction, San Diego, self-supervised learning, ulcerative colitis, unsupervised learning, video data, Virgo, VirgoCloudMENLO PARK — Virgo, a San Diego-based company, is revolutionizing the field of endoscopy by integrating artificial intelligence (AI) with endoscopic video data to enhance patient care. The company’s goal is to leverage AI to improve clinical outcomes, including predicting responses to treatment and helping patients find clinical trials. Their work focuses on processing the…
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newsMeta Launches V-JEPA: A New Model for Video-Based Advanced Machine Intelligence
AI assistants, Algorithms, Americas, Analytics, Artificial Intelligence, Internet & Online, Machine intelligence, Machine learning, Media, Predictive analyticsOleg Lazarov
abstract representation space, action recognition, advanced machine intelligence, AI community, AI perception, AMI, CC BY-NC, Creative Commons NonCommercial, fine-grained object interactions, general machine intelligence, JEPA, machine learning, Meta, Meta AI, non-generative model, open science, planning, self-supervised learning, spatial-temporal events, V-JEPA, Video Joint Embedding Predictive Architecture, video streams, video-based AI, world models, Yann LeCunMENLO PARK — Meta has unveiled the Video Joint Embedding Predictive Architecture (V-JEPA), a pioneering model designed to push forward advanced machine intelligence (AMI). V-JEPA is a non-generative model that learns through predicting masked or missing sections of video in an abstract representation space, making it a crucial step toward AI that understands and interacts…
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newsMeta Unveils DINOv2 and FACET: Advancing Computer Vision with Open Source and Fairness Evaluation
AI assistants, AI models, Americas, Analytics, Artificial Intelligence, Datasets, Internet & Online, Open Source LLMs, Responsible AIOleg Lazarov
age group, AI innovation, Apache 2.0 license, benchmarking, bias mitigation, classification, collaboration, computer vision, computer vision community, demographic attributes, depth estimation, detection, DINOv2, FACET, fairness evaluation, fairness in AI, gender presentation, Meta, Meta AI, open source research, performance disparities, person-related classification, responsible AI, segmentation, self-supervised learning, semantic image segmentation, skin tone, state-of-the-art modelsMENLO PARK — Meta is advancing its efforts in computer vision technology, releasing new models and tools while ensuring fairness and transparency in AI development. Their latest development, DINOv2, a self-supervised learning-based model for computer vision, is now available under the Apache 2.0 license. This release includes models for semantic image segmentation and depth estimation, expanding…
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newsMeta AI Launches DINOv2, a Breakthrough in Self-Supervised Learning for Versatile Computer Vision Applications
Americas, Analytics, Artificial Intelligence, Computer vision, Datasets, Internet & Online, Machine learning, MediaSheryl Rivera
AI development, classification, computer vision, computer vision research, depth estimation, DINOv2, forest mapping, generalization, high performance, image analysis, labeled datasets, Meta AI, pretrained models, raw images, real-world application, scalability, scalable architecture, segmentation, self-supervised learning, text-image annotations, visual AI, visual embeddings, World Resources InstituteMENLO PARK — Meta AI has unveiled DINOv2, a next-generation self-supervised model designed to advance computer vision capabilities across various tasks without requiring labeled data. Unlike previous models that rely on text-image annotations, DINOv2 excels by learning directly from raw images, enhancing flexibility and effectiveness in tasks such as classification, depth estimation, and segmentation. This…
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newsRevolutionizing Online Safety: Facebook’s Latest AI Techniques in Content Moderation
AI assistants, Algorithms, Americas, Analytics, Artificial Intelligence, Internet & Online, Machine learning, SocietyOleg Lazarov
AI, artificial intelligence, Community Standards Enforcement Report, content moderation, drug sale content, Facebook, focal loss, gradient blending, harmful content, hate speech detection, multilingual data, online safety, proactive detection, self-supervised language models, self-supervised learning, technology advancements, Whole Post Integrity Embeddings, WPIE, XLM methodMENLO PARK — In an era where online safety is paramount, Facebook’s latest Community Standards Enforcement Report highlights groundbreaking strides made in artificial intelligence (AI) to enhance content moderation across its platforms. This comprehensive update sheds light on the significant progress achieved through advancements in self-supervised learning, a technique that has transcended the limitations of…
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RadicalShift.ai represents the paradigm shift the artificial intelligence (AI) brings upon all of us, from the way we live and work to the way we do business. To help cope with these fundamental changes across life, industries and the world in general, we are obsessively observing (30+ markets across multiple continents) and covering the AI industry while building a scalable open platform aimed at people, businesses and industry stakeholders to contribute across (benefit from) the entire spectrum of the AI industry from news, views, insights to knowledge, deployments, entities, people, products, tools, jobs, investors, pitch decks, and beyond, helping build what would potentially be a resourceful, insightful, knowledgeable and analytical source for AI related news, information and resources, ultimately becoming the AI industry graph/repository.
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