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Breaking the Boundaries in 3D Scene Representation: How a New AI Technique is Changing the Game with Faster, More Efficient Rendering and Reduced Storage Demands
NeRF models scenes in 3D and learns from various viewpoints to create photorealistic images. Researchers from Sungkyunkwan University improved efficiency with a mask strategy, reducing memory requirements and increasing speed. Point-based rendering enhancements and ongoing research promise to further advance realistic 3D applications. Credit goes to the researchers and is shared via various online AI…
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Meet Meditron: A Suite of Open-Source Medical Large Language Models (LLMs) based on LLaMA-2
Researchers released MediTron, an open-source medical LLM suite with 7B and 70B parameter variants, excelling in benchmarks and tailored for tasks like medical QA. It uses an extensive medical dataset for training but requires further testing before clinical deployment to ensure safety.
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Microsoft Researchers Propose MAIRA-1: A Radiology-Specific Multimodal Model for the Task of Generating Radiological Reports from Chest X-rays (CXRs)
Microsoft researchers developed MAIRA-1, a model combining a chest X-ray-specific image encoder with a fine-tuned language model to generate accurate radiology reports. It leverages data augmentation and evaluation metrics tailored to clinical relevance to improve report quality. Future enhancements may include incorporating study histories to reduce inaccuracies.
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This AI Paper from Northeastern University and MIT Develop Interpretable Concept Sliders for Enhanced Image Generation Control in Diffusion Models
Researchers from Northeastern University, MIT, and an independent researcher developed Concept Sliders for text-to-image diffusion models, allowing fine-grained image control and editing. This method enables manipulation of visual concepts that are usually hard to describe in words and offers a practical, disentangling solution for more precise image customization through open-source code and trained sliders.
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Artists added to resubmitted Stability AI, Midjourney lawsuit
Artists seeking copyright infringement claims against Stability AI and others have refiled their lawsuit with seven additional plaintiffs. The original case was dismissed, but Judge William Orrick allowed for an amended resubmission. The updated lawsuit uses comments by Stability AI’s CEO and concerns over derivative works and AI’s use of copyrighted data to bolster its…
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Meet PGXMAN : The PostgreSQL Extension Manager
PGXMAN is a package manager for Postgres extensions, streamlining installation, update, and management processes. It handles dependencies automatically, saving developers time and effort. Installation is easy via pip, and a supportive community further enhances its utility. For more information, visit https://pgxman.com/.
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Researchers from Microsoft and Georgia Tech Introduce TongueTap: Multimodal Tongue Gesture Recognition with Head-Worn Devices
Researchers from Microsoft and Georgia Tech developed TongueTap, a wearable tech interface that uses tongue gestures to control devices without hands or eyes. It combines data from IMUs and PPG sensors in headsets for gesture recognition with 80-94% accuracy, promising improvements for AR interactions.
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Meet RAGs: A Streamlit App that Lets You Create a RAG Pipeline from a Data Source Using Natural Language
RAGs, an application by Streamlit, simplifies GPT pipeline creation and deployment with an intuitive interface. The latest version, RAGs v2, enhances user experience with features for building and customizing ChatGPTs, managing RAG pipelines, and supporting multiple large language models. To use it, install with ‘pip,’ create pipelines, deploy, and query via command line. It’s a…
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Unveiling the Power of Chain-of-Thought Reasoning in Language Models: A Comprehensive Survey on Cognitive Abilities, Interpretability, and Autonomous Language Agents
The study by Shanghai Jiao Tong University, Amazon, and Yale explores Chain-of-Thought reasoning in language models, examining its impact on the development and reliability of language agents. It investigates CoT techniques and verification methods, offering insights for both new and seasoned researchers in language intelligence.
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UC Berkeley Researchers Develop ALIA: A Breakthrough in Automated Language-Guided Image Augmentation for Fine-Grained Classification Tasks
UC Berkeley researchers have developed ALIA, an innovative language-guided image augmentation technique that improves dataset variety and classification model performance in fine-grained image tasks without extensive fine-tuning. It uses natural language to generate domain-specific image edits and employs filtering to maintain visual consistency, showing a significant enhancement over traditional methods in experiments.