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MIT Generative AI Week fosters dialogue across disciplines
MIT Generative AI Week featured a flagship full-day symposium and four subject-specific symposia, aiming to foster dialogue about generative artificial intelligence technologies. The events included panels, roundtable discussions, and keynote speeches, covering topics such as AI and education, health, creativity, and commerce. The week concluded with a screening of the documentary “Another Body,” followed by…
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Enhancing Machine Learning Reliability: How Atypicality Improves Model Performance and Uncertainty Quantification
Cognitive science studies suggest typicality is vital for category knowledge, affecting human judgment. Machine learning methods offer assurance in predictions, but considering atypicality alongside confidence improves accuracy and uncertainty quantification. Recalibration techniques with atypicality-aware measures elevate performance across subgroups. Atypicality should be integrated into models for enhanced reliability in AI.
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Meta AI Introduces Relightable Gaussian Codec Avatars: An Artificial Intelligence Method to Build High-Fidelity Relightable Head Avatars that can be Animated to Generate Novel Expressions
Meta AI has introduced “Relightable Gaussian Codec Avatars,” a revolutionary method for achieving high-fidelity relighting of dynamic 3D head avatars. The approach relies on a 3D Gaussian geometry model and a learnable radiance transfer appearance model to capture sub-millimeter details and enable real-time relighting. This innovation elevates the realism and interactivity of avatar animation, marking…
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Researchers perform speech recognition with living human brain cells
Brain organoids, lab-grown mini-brains created from human stem cells, have been integrated with computers to achieve speech recognition. This innovative “Brainoware” system, described in a study in Nature Electronics, represents a shift from traditional AI using silicon chips. Despite challenges, its potential for creating energy-efficient AI hardware with human brain-like functionality is evident.
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AI matches doctors in X-ray analysis, University of Warwick Study finds
A University of Warwick study unveils an AI system, X-Raydar, trained on 2.8 million chest X-rays, demonstrating comparable accuracy to doctors in diagnosing 94% of conditions. It highlights potential for efficient diagnosis, particularly in addressing radiologist shortages. X-Raydar has been open-sourced to foster further advancements in AI medical technology.
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LiDAR: Sensing Linear Probing Performance in Joint Embedding SSL Architectures
This paper introduces LiDAR, a metric designed to measure the quality of representations in Joint Embedding (JE) architectures, addressing the challenge of evaluating learned representations. JE architectures have potential for transferable data representations, but evaluating them without access to a task and dataset is difficult. LiDAR aims to facilitate efficient and reliable evaluation.
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Five things you need to know about the EU’s new AI Act
After months of negotiations, EU lawmakers have reached a deal on the groundbreaking AI Act, introducing strict rules on transparency and ethics for tech companies, creating enforcement mechanisms, and setting up fines for noncompliance. The Act covers regulations on powerful AI models, governance mechanisms, fines for noncompliance, and bans on certain AI uses.
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Data generation with diffusion models. Part 3: Generating custom data in the blink of an eye
This blog post outlines the capabilities of diffusion models for generating custom data by using additional conditioning. It introduces methods such as Stable Diffusion Inpainting, ControlNet, and GLIGEN, and highlights how fine-tuning with the Low-Rank Optimization technique, or LoRA, can efficiently adapt these methods to specific use cases. The article emphasizes the benefits of enhancing…
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Stanford Researchers Introduce the Anticipatory Music Transformer: A Groundbreaking AI Tool for Enhanced Creative Control in Music Composition
The Anticipatory Music Transformer, developed by Stanford scholars, empowers composers with unique control over generative AI music composition. Differentiating itself from other tools, it focuses on symbolic music and incorporates users’ preferences. Integrated with the GPT architecture, it offers more interactive and controllable outputs. Anticipated to revolutionize music composition, it aims to make music creation…
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How Do Schrodinger Bridges Beat Diffusion Models On Text-To-Speech (TTS) Synthesis?
The introduction of Large Language Models (LLMs) has brought attention to Natural Language Processing, Natural Language Generation, and Computer Vision. Researchers from Tsinghua University and Microsoft Research Asia introduced Bridge-TTS, an alternative to noisy prior models, achieving better TTS synthesis than Grad-TTS and FastGrad-TTS while demonstrating improved speed and generation quality. Find out more at…