Meet Deep-Seek: An Open Source Research Agent Designed as an Internet Scale Retrieval Engine

Practical Solutions and Value of KITA: A Programmable AI Framework Addressing Issues with Large Language Models (LLMs) Large Language Models (LLMs) often produce unjustified responses, known as hallucinations. KITA offers a solution by providing reliable and…

Meet Hawkish 8B: A Powerful Financial AI Model In today’s fast-changing financial world, having strong analytical models is essential. Traditional financial methods require deep knowledge of complex data and terms. Most AI models struggle to grasp…

Practical Solutions for Long-Context LLMs Accelerating Processing with MInference The MInference method optimizes sparse calculations for GPUs, reducing latency without altering pre-training or needing fine-tuning. It achieves up to a 10x speedup, cutting the pre-filling stage…

Large Language Models (LLMs) like OpenAI’s GPT have become more prevalent, enhanced by Generative AI for human-like textual responses. Techniques such as Retrieval Augmented Generation (RAG) and fine-tuning improve responses’ precision and contextuality. RAG uses external…

The Skywork-13B family of large language models (LLMs) addresses the need for transparent and commercially available LLMs. Researchers at Kunlun Technology developed Skywork-13B-Base and Skywork-13BChat, providing detailed information about the training process and data composition. They…

Guiding Instruction-based Image Editing via Multimodal Large Language Models Instruction-based image editing improves the controllability and flexibility of image manipulation via natural commands without elaborate descriptions or regional masks. Multimodal large language models (MLLMs) show promising…

Enhancing Security with Biometric Authentication Biometric authentication is a powerful way to improve security against cyber threats. As technology evolves, hackers are finding new ways to bypass traditional security methods like passwords and PINs, which can…

Enhancing Music Recommendation Systems with PISA Revolutionizing Music Discovery Music recommendation systems are essential for streaming platforms, helping users discover new songs and re-listen to favorites. Algorithms analyze listening patterns to provide personalized song recommendations based…

Relax is a compiler abstraction that optimizes machine learning models with dynamic shapes. It uses symbolic shape annotations to track dynamic shape computations and enables cross-level optimizations. The forward deduction method is used to infer annotations…

Researchers have introduced the GraphGPT framework to enhance the generalization capabilities of graph models in natural language processing. The framework incorporates domain-specific structural knowledge into language models and improves their understanding of graph structures. Extensive evaluations…

Large Language Models (LLMs) are revolutionizing natural language processing by leveraging vast amounts of data and computational resources. The capacity to process long-context inputs is a crucial feature for these models. However, accessible solutions for long-context…

Nvidia researchers have introduced a method called neural radiance field (NeRF) formulation for view synthesis. This approach efficiently transitions between volumetric and surface-based rendering by constructing a mesh envelope around a neural volumetric representation. The method…

Transforming Daily Tasks with AI Artificial Intelligence (AI) is changing how we handle daily tasks by making processes easier and more efficient. AI tools boost productivity and provide creative solutions for various challenges, such as managing…

The SWE-bench evaluation framework, developed by researchers from Princeton University and the University of Chicago, focuses on assessing the ability of language models (LMs) to solve real-world software engineering challenges. The findings reveal that even advanced…

AI language models have been used by scientists to create new tools for analyzing speech patterns in patients with schizophrenia, allowing them to identify subtle signatures.

This text introduces Survival Analysis and its application in Python. It is available on Towards Data Science.