A NEW AI Model out for Text to 3D?! MVDream: explained in my most recent video! Learn more in the video: https://
youtu.be/uiVC9J-A_68 #ai #3d #MVDream #generativeai #genai
MULTIMODAL AI
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MVDream: New AI Model Transforms Text into 3D Models
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Edge Detection Limitations in Machine Learning Line Drawing
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Why Edge Detection Doesn’t Explain Line Drawing https://
bit.ly/3quKkLn #AI #MachineLearning #DeepLearning #LLMs #DataScience -
Hume AI Demo: Revolutionary AI Breakthrough Experience
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This is the COOLEST AI demo I've played with in forever… from @hume_ai
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Bria AI Launches Licensed Foundation Models With Getty Images
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Israel-based AI image generator Bria AI has created new foundation models trained with licensed content from stock image powerhouse Getty Images and other sources. Bria’s also made new data attribution tools for AI researchers & for compensating creators.
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Scene Representations in Latent Diffusion Models
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Beyond Surface Statistics: Scene Representations in a Latent Diffusion Model Chen : https://
arxiv.org/abs/2306.05720 #ArtificialIntelligence #DeepLearning #MachineLearning -
Large Language Models Beyond Text Generation: Diverse Use Cases
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#LLMs are not just a fad. We see #LargeLanguageModels doing much more than just generate text! Check out our recent blog to learn about the wide range of use cases with video demos.
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VideoGen: Reference-Guided Latent Diffusion for Video Generation
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We proposed a new text-to-video generation approach, VideoGen, which can generate high-definition video with high frame fidelity and strong temporal consistency using reference-guided latent diffusion. Learn more: https://t.co/HS5ALQv3GK pic.twitter.com/aEoUls78eS
— Baidu Research (@BaiduResearch) 7 septembre 2023We proposed a new text-to-video generation approach, VideoGen, which can generate high-definition video with high frame fidelity and strong temporal consistency using reference-guided latent diffusion. Learn more: https://
videogen.github.io/VideoGen/ -
Stanford AI algorithm analyzes medical images without extensive annotation
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A major hurdle in diagnostic AI is the lack of well-annotated data. Stanford researchers leveraged a trove of anonymized medical images from Twitter – er, X – to develop a powerful algorithm that can analyze previously unseen images.
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Computer Vision AI Solutions Showcase at Semicon Taiwan 2023
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Today was the first day at #SemiconTaiwan 2023 in the NL Pavilion! We're here to connect and share insights about our computer vision solutions for AI at the edge. Join us if you're around. Date: Sept 6/7 Location: TaiNEX Hall 1, 4th Floor, Booth No. L1006
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FACET: New Fairness Benchmark Dataset for Vision Models
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Last week we released FACET, a new comprehensive benchmark dataset for evaluating the fairness of models across a number of different vision tasks, constructed of 32K images from SA-1B, labeled by expert annotators.
— AI at Meta (@AIatMeta) 5 septembre 2023
Read the paper ➡️ https://t.co/OoYV2eiSYX pic.twitter.com/9Q7uk59TvTLast week we released FACET, a new comprehensive benchmark dataset for evaluating the fairness of models across a number of different vision tasks, constructed of 32K images from SA-1B, labeled by expert annotators. Read the paper https://
bit.ly/3EotZvg