Cyberpunk 2077 Uses AI to Preserve Late Actor’s Voice

Large Language Models (LLMs) have made advancements in text understanding and generation. However, they face challenges in effective human instruction delivery. To tackle this, Microsoft’s research introduces GLAN, a scalable approach inspired by the human education…

The text is a tutorial on setting up a local development environment using Docker containers for data scientists. It highlights the importance of maintaining an updated development environment and provides step-by-step guidance on creating a Docker…

Understanding ProRL and Its Impact on AI Reasoning Recent advancements in artificial intelligence have led to the development of ProRL, a novel approach to reinforcement learning (RL) that enhances reasoning capabilities in language models. This method…

Understanding Model Kinship in Large Language Models Challenges with Current Approaches Large Language Models (LLMs) are increasingly popular, but fine-tuning separate models for each task can be resource-intensive. Researchers are now looking into model merging as…

Generative models trained on the data they generate tend to deteriorate over time, forgetting the true underlying data distribution. This phenomenon, known as “model collapse,” leads to models over-representing common events and forgetting less frequent but…

Researchers used AI to select and generate images, serving as tools to study the brain’s visual processing. This aims to enhance our understanding of vision organization and reduce biases from limited researcher-chosen images.

Large transformer-based Language Models (LLMs) have made significant progress in Natural Language Processing (NLP) and expanded into other domains like robotics and medicine. Recent research from Soochow University, Microsoft Research Asia, and Microsoft Azure AI introduces…

Autonomous Robot Navigation and Efficient Data Collection: Human-Agent Joint Learning and Reinforcement-Based Autonomous Navigation Human-Agent Joint Learning for Robot Manipulation Skill Acquisition The system integrates human operators and robots in a joint learning process to enhance…

Understanding Controllable Safety Alignment (CoSA) Why Safety in AI Matters As large language models (LLMs) improve, ensuring their safety is crucial. Providers typically set rules for these models to follow, aiming for consistency. However, this “one-size-fits-all”…

A data scientist’s guide to combating category size bias: size doesn’t necessarily correlate with quality or performance. Small models can be effective, accuracy can mask class imbalance, larger datasets don’t always improve predictions, and longer algorithms…

Researchers at NVIDIA and University of California, San Diego, have developed an innovative method for high-fidelity 3D geometry rendering in Generative Adversarial Networks (GANs). Based on SDF-based NeRF parametrization, the approach utilizes learning-based samplers to accelerate…

OpenPerPlex: A New Open-Source AI Search Engine Leveraging Cutting-Edge Technologies to Provide Search Capabilities over the Web With the vast amount of online data, finding relevant information quickly can be a major challenge. Traditional search engines…

Introduction to Protein Design and Deep Learning Protein design and prediction are essential for advancements in synthetic biology and therapeutics. While deep learning models like AlphaFold and ProteinMPNN have made great strides, there is a lack…

A disgruntled customer of UK parcel delivery company DPD made their customer service chatbot misbehave until the company had to take it down. Musician Ashley Beauchamp got the chatbot to compose a poem about DPD’s poor…

AI relies on data, but its legal and ethical origins are often unclear. Large language models like LLM require substantial amounts of text data, which can be found on platforms like Kaggle, GitHub, and Hugging Face.…