Advancing Cantonese NLP: Bridging Development Gaps in Large Language Models with New Benchmarks and Open-Source Innovations

Feast is an operational data system designed to manage and serve machine learning features, providing solutions for data leakage, feature engineering, and model deployment challenges. It offers an offline store for historical data processing, a low-latency…

Practical Solutions and Value of Homomorphic Encryption Reinforcement Learning (HERL) Overview Federated Learning (FL) allows Machine Learning models to be trained on decentralized data sources while maintaining privacy, crucial in industries like healthcare and finance. However,…

Personalized Review Generation in Recommender Systems Practical Solutions and Value Personalized review generation within recommender systems is crucial for creating custom reviews based on users’ historical interactions and preferences. This enhances the overall effectiveness of recommender…

Practical Solutions for Efficient Deployment of Large Language Models Challenges in Real-World Applications Large language models (LLMs) have faced limitations in practical applications due to high processing power and memory requirements. Introducing LightLLM Framework LightLLM is…

The Value of Vision-Language Models Vision-Language Models in Practical Applications The research on vision-language models (VLMs) is gaining momentum due to their potential to revolutionize various applications, such as visual assistance for visually impaired individuals. Challenges…

The Evolution of Language Models The rapid advancement of Large Language Models (LLMs) is fueled by the belief that larger models and datasets will lead to human-like intelligence. As these models shift from research to commercial…

Practical AI Solution: Mistral-finetune Many developers and researchers struggle with efficiently fine-tuning large language models. Adjusting model weights demands substantial resources and time, hindering accessibility for many users. Introducing Mistral-finetune Mistral-finetune is a lightweight codebase designed…

The Frontiers of General Artificial Intelligence Technology Exhibition in Beijing unveiled a virtual robot toddler named Tong Tong, developed by the Beijing Institute for General Artificial Intelligence. Tong Tong exhibits human-like abilities and behaviors, mirroring those…

Researchers at ETH Zurich have developed a robotic system utilizing AI and reinforcement learning to master the BRIO labyrinth game in just five hours of training data. The AI-powered robot’s success highlights the potential of advanced…

Practical Solutions for Dynamic Image Classification Integrating Visual Memory for Adaptive Learning Deep learning models often struggle to adapt to evolving data needs. The proposed solution integrates deep neural networks with a visual memory database, allowing…

Enhancing Language Models with Continual Pre-training and Fine-Tuning Practical Solutions and Value Large language models (LLMs) have revolutionized natural language processing, making machines more effective at understanding and generating human language. They are pre-trained on vast…

Microsoft’s recent acquisition of top talent from OpenAI, including Sam Altman and Greg Brockman, suggests that the tech giant is positioning itself as a dominant force in the AI industry. With the possibility of 550 OpenAI…

Researchers from SLAC National Accelerator Laboratory, Stanford University, MIT, and Toyota Research Institute have developed a new approach using computer vision to analyze X-ray movies of lithium-ion batteries. By analyzing every pixel, they were able to…

Challenges in Using LLMs for Mainframe Modernization: 1. Limited Training on Mainframe Languages: Existing large language models (LLMs) lack sufficient training on mainframe languages like COBOL, hindering their ability to understand and interact with legacy codebases.…

IBM researchers have introduced LAB (Large-scale Alignment for chatbots) to address scalability challenges in instruction-tuning for large language models (LLMs). LAB leverages a taxonomy-guided synthetic data generation process and a multi-phase training framework to enhance LLM…

Enhancing AI Transparency and Safety Enhancing AI Transparency and Safety Introduction to Chain-of-Thought Reasoning Chain-of-thought (CoT) reasoning represents a significant advancement in artificial intelligence (AI). This approach allows AI models to articulate their reasoning steps before…

Data Science is a fast-moving field with new tools and workflows constantly emerging. This article highlights the most-read and discussed articles from the past month, covering topics such as coding, productivity, LLMs, data engineering, remote work,…

The text discusses justifying the existence of Data Mesh, a decentralized data architecture. It traces the evolution of data landscape from relational databases to cloud data warehouses, highlighting the limitations of centralized data architecture. The concept…

Fine-tuning commercial language models (LLMs) can bypass safety measures and lead to dangerous responses. Researchers found that fine-tuning GPT-3.5 with malicious examples deactivated its safety switch. This raises concerns about the safety and liability of fine-tuned…