PlanRAG: A Plan-then-Retrieval Augmented Generation for Generative Large Language Models as Decision Makers

The Biden administration is compelling cloud service providers to disclose foreign users developing AI technologies, particularly in China. This aims to restrict access to essential data centers and servers and curb perceived malicious cyber-enabled activities. US-China…

Billionaire Vinod Khosla, an early AI backer, predicts that AI will have a profound impact on the global economy. He anticipates significant deflation over the next twenty-five years, with traditional economic gauges becoming less relevant. Khosla’s…

Fine-Tuning Mistral 7B with QLoRA Using Axolotl Overview In this guide, we will learn how to fine-tune the Mistral 7B model using QLoRA with Axolotl. This approach allows us to effectively manage limited GPU resources while…

Practical AI Solutions for Your Business Dynamic View Synthesis with AI Rendering scenes observed in a monocular video from novel viewpoints is a challenging problem. For static scenes, we offer scene-specific optimization techniques and generalized techniques.…

7 Emerging Generative AI User Interfaces: How Emerging User Interfaces Are Transforming Interaction The Chatbot Chatbots like ChatGPT, Claude, and Perplexity simulate human-like interactions, offering tasks such as answering queries, providing recommendations, and assisting with customer…

Practical AI Solutions for Your Company Consistency Large Language Models (CLLMs): A New Family of LLMs Specialized for the Jacobi Decoding Method for Latency Reduction Consistency Large Language Models (CLLMs) are designed to improve the efficiency…

The Practical Solutions and Value of Meta AI’s CYBERSECEVAL 3 Addressing AI Cybersecurity Risks Meta AI introduces CYBERSECEVAL 3 to assess the cybersecurity risks, benefits, and capabilities of AI systems, focusing on large language models (LLMs)…

Practical Solutions in Advancing AI Research Challenges in Neural Network Flexibility Neural networks often face limitations in practical performance, impacting applications such as medical diagnosis, autonomous driving, and large-scale language models. Current Methods and Limitations Methods…

Astronomical Research Transformation Astronomical research has advanced significantly, changing from basic observations to advanced data collection methods. Modern telescopes now create large datasets across different wavelengths, providing detailed insights into celestial objects. The astronomical field produces…

Understanding the Challenges of Training Large AI Models Training large AI models, like transformers and language models, is essential but very resource-intensive. These models, such as OpenAI’s GPT-3 with 175 billion parameters, require a lot of…

Researchers critically evaluated foundational models scGPT and Geneformer for single-cell biology, assessing zero-shot performance on tasks like cell clustering and batch effect correction. Despite efforts, both models demonstrated suboptimal performance, often underperforming compared to baseline models.…

Researchers from MIT and NVIDIA have developed two techniques that can accelerate the processing of sparse tensors, a type of data structure used for high-performance computing. The techniques, called HighLight and Tailors/Swiftiles, can improve the performance…

Cutie is a new video object segmentation method that improves performance in challenging situations with occlusions and distractions. It uses object-level memory reading, combining pixel-level features with high-level queries for effective segmentation. The method incorporates masked…

Transformer Models for Relational Reasoning We explore the capabilities of transformer models in solving relational reasoning tasks. These models are trained on abstract relations and can generalize to new data, even with symbols not seen during…

Large language models (LLMs) like GPT-4 have wide-ranging uses but also raise concerns about potential misuse and ethical implications. FAR AI’s study highlights the susceptibility of LLMs to unethical use, emphasizing the need for proactive security…

The Evolution of Information Retrieval The field of information retrieval (IR) has seen rapid advancements with the integration of neural networks, particularly dense and multi-vector models, transforming data retrieval and processing. These models encode queries and…