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Scientists at UC Berkeley suggest a Neural Diffusion method working on Syntax Trees for creating programs.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJune 8, 202440Views0Likes0Comments
Large language models (LLMs) have significantly advanced code generation, but they develop code in a linear fashion without access to a feedback loop that allows for corrections based on the previous outputs. This creates challenges in correcting mistakes or suggesting edits. Now, researchers at the University of California, Berkeley, have developed a new approach using…

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Jina AI has publicly released Jina CLIP: an advanced English multimodal (text-image) embedding model.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJune 7, 202437Views0Likes0Comments
The field of multimodal learning, which involves training models to understand and generate content in multiple formats such as text and images, is evolving rapidly. Current models have inefficiencies in dealing with text-only and text-image tasks, often excelling in one domain but underperforming in the other. This necessitates distinct systems to retrieve different forms of…

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BioDiscoveryAgent: Transforming Genetic Research Design with Insights Powered by Artificial Intelligence.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJune 7, 202436Views0Likes0Comments
LLM or Language Model-based systems have shown potential to accelerate scientific discovery, especially in the biomedical research field. These systems are able to leverage a large bank of background information to conduct and interpret experiments, particularly useful for identifying drug targets through CRISPR-based genetic modulation. Despite the promise they show, their usage in designing biological…

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Matrices of Quantized Eigenvectors for Second-Order Optimization of 4-bit Deep Learning Networks

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Staff, Tech News, Technology, UncategorizedJune 7, 202433Views0Likes0Comments
Deep neural networks (DNNs) have found widespread success across various fields. This success can be attributed to first-order optimizers such as stochastic gradient descent with momentum (SGDM) and AdamW. However, these methods encounter challenges in efficiently training large-scale models. As an alternative, second-order optimizers like K-FAC, Shampoo, AdaBK, and Sophia have demonstrated superior convergence properties,…

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