​We present Recurrent Drafter (ReDrafter), an advanced speculative decoding approach that achieves state-of-the-art speedup for large language models (LLMs) inference. The performance gains are driven by three key aspects: (1) leveraging a recurrent neural network (RNN) as the draft model conditioning on LLM’s hidden states,… Read More »Recurrent Drafter for Fast Speculative Decoding in Large Language Models Apple Machine Learning Research

​[[{“value”:” Artificial intelligence systems often struggle with retaining meaningful context over extended interactions. This limitation poses challenges for applications such as chatbots and virtual assistants, where maintaining a coherent conversation thread is essential. Most traditional AI models operate in a stateless manner, focusing solely on… Read More »Meet Memoripy: A Python Library that Brings Real Memory Capabilities to AI Applications Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Developments in simulating particulate flows have significantly impacted industries ranging from mining to pharmaceuticals. Particulate systems consist of granular materials interacting with each other and surrounding fluids, and their accurate modeling is critical for optimizing processes. However, traditional numerical methods like the Discrete Element… Read More »NeuralDEM: Pioneering High-Performance Simulation of Large-Scale Particulate Systems with Multi-Branch Neural Operator Architectures Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large Language Models (LLMs) have demonstrated exceptional capabilities across diverse applications, but their widespread adoption faces significant challenges. The primary concern stems from training datasets that contain varied, unfocused, and potentially harmful content, including malicious code and cyberattack-related information. This creates a critical need… Read More »H-DPO: Advancing Language Model Alignment through Entropy Control Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Multi-label text classification (MLTC) assigns multiple relevant labels to a text. While deep learning models have achieved state-of-the-art results in this area, they require large amounts of labeled data, which is costly and time-consuming. Active learning helps optimize this process by selecting the most… Read More »BEAL: A Bayesian Deep Active Learning Method for Efficient Deep Multi-Label Text Classification Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Model efficiency is important in the age of large language and vision models, but they face significant efficiency challenges in real-world deployments. Critical metrics such as training compute requirements, inference latency, and memory footprint impact deployment costs and system responsiveness. These constraints often limit… Read More »Google AI Introduces LAuReL (Learned Augmented Residual Layer): Revolutionizing Neural Networks with Enhanced Residual Connections for Efficient Model Performance Sajjad Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Data visualization is a powerful technique that transforms complex data into easily understandable visual representations. Let us explore how data visualization can help with graphs. Applying data visualization to graphs allows us to examine intricate relationships between entities, identify patterns, and uncover insights that… Read More »Top 7 Graph Database Visualization Tools Pragati Jhunjhunwala Artificial Intelligence Category – MarkTechPost

​[[{“value”:” A significant challenge in the field of artificial intelligence is to facilitate large language models (LLMs) to generate 3D meshes from text descriptions directly. Conventional techniques restrict LLMs from operating as text-based components and remove multimodal workflows that combine textual and 3D content creation.… Read More »LLaMA-Mesh: A Novel AI Approach that Unifies 3D Mesh Generation with Large Language Models by Representing Meshes as Plain Text Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Instruction-tuned large language models (LLMs) have redefined natural language processing (NLP), offering significant improvements in generating coherent, context-aware responses. However, a pressing challenge persists—access to high-quality, diverse, and task-specific instruction-response datasets. Traditional instruction-tuning approaches often depend on curated datasets that are costly and time-intensive… Read More »Microsoft AI Research Released 1 Million Synthetic Instruction Pairs Covering Different Capabilities Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Machine learning (ML) engineers face many challenges while working on end-to-end ML projects. The typical workflow involves repetitive and time-consuming tasks like data cleaning, feature engineering, model tuning, and eventually deploying models into production. Although these steps are critical to building accurate and robust… Read More »Meet NEO: A Multi-Agent System that Automates the Entire Machine Learning Workflow Asif Razzaq Artificial Intelligence Category – MarkTechPost