Bytedance Announces DiffPortrait3D: A Novel Zero-Shot View Synthesis AI Method that Extends 2D Stable Diffusion for Generating 3d Consistent Novel Views Given as Little as a Single Portrait

Understanding Large Language Models (LLMs) Large Language Models (LLMs) are advanced tools that can understand and generate human-like text. However, they can be vulnerable to attacks, particularly through a method known as jailbreaking. This occurs when…

Researchers have developed Eff-3DPSeg, a weakly supervised deep learning framework for 3D plant shoot segmentation. This innovative approach uses a low-cost photogrammetry system and a Meshlab-based Plant Annotator to acquire and annotate point clouds from individual…

Embedić: Revolutionizing Serbian Language Processing Key Highlights: – Novak Zivanic introduces Embedić, a suite of Serbian text embedding models. – Models optimized for Information Retrieval and Retrieval-Augmented Generation (RAG) tasks. – Efficient smallest model surpasses previous…

Researchers from FNii CUHKSZ and SSE CUHKSZ have introduced MVHumanNet, a vast dataset for multi-view human action sequences with comprehensive annotations, such as human masks, camera parameters, 2D and 3D key points, SMPL/SMPLX parameters, and textual…

The Metal.jl Framework provides Julia users on macOS the ability to utilize the GPU for better performance in scientific computing and machine learning. It tackles macOS’s transition to M-series chips, offering solutions amidst compatibility challenges. Users…

OpenPipe’s Mixture of Agents (MoA) Model: Revolutionizing AI Training Data Generation Achieving SOTA Results OpenPipe’s MoA model excels in generating high-quality synthetic training data, scoring 84.8 on Arena Hard Auto and 68.4 on AlpacaEval 2.0 benchmarks,…

Introduction to CelloType Cell segmentation and classification are crucial for understanding cellular structures and functions. With recent advancements in spatial omics technologies, we can achieve high-resolution analysis of tissues. This supports important projects like the Human…

Understanding the Connection Between Visual Data and Robot Actions Robots operate through a cycle of perception and action, known as the perception-action loop. They use control parameters for movement, while Visual Foundation Models (VFMs) are skilled…

Understanding Diverse Preference Optimization (DivPO) Large-scale language models (LLMs) are revolutionizing artificial intelligence by powering various applications. However, they often struggle with generating diverse responses, particularly in creative tasks like storytelling and data generation, where variety…

Enhancing LLMs’ Mathematical Reasoning with DotaMath Addressing Challenges in Mathematical Reasoning Large language models (LLMs) have made significant progress in natural language processing tasks but face challenges in complex mathematical reasoning. Researchers are working to enable…

Understanding AI in Video Processing Efficiently handling video sequences with AI is crucial for accurate analysis. Current challenges arise from models that fail to process videos as continuous flows, leading to missed motion details and disruptions…

This text provides a hands-on guide to building a language model for masked language modeling (MLM) tasks using Python and the Transformers library. It discusses the importance of large language models (LLMs) in the machine learning…

The text discusses techniques to improve the efficiency of large language models (LLMs) through prompt compression, focusing on methods such as AutoCompressors and LongLLMLingua. The goal is to reduce inference costs and enable faster and accurate…

Background Oriented Schlieren (BOS) imaging is an effective, low-cost method for visualizing fluid flow. A new approach using Physics-Informed Neural Networks (PINNs) has been developed to accurately deduce complete 3D velocity and pressure fields from Tomo-BOS…

Model Predictive Control (MPC) is widely used in fields such as power systems and robotics. A recent study from Carnegie Mellon University focused on the convergence characteristics of a sampling-based MPC technique called Model Predictive Path…

Data and machine learning professionals are wrapping up the year by enhancing skills and preparing for career progression. November’s popular reads in Towards Data Science (TDS) included guides on knowledge graphs, hardware benchmarks, job search tips,…

Understanding LLM Inference Challenges Large Language Model (LLM) inference requires a lot of memory and computing power. To solve this, we use model parallelism strategies that share workloads across multiple GPUs. This helps reduce memory issues…

Neural Magic Releases LLM Compressor: A Novel Library to Compress LLMs for Faster Inference with vLLM Neural Magic has launched the LLM Compressor, a cutting-edge tool for optimizing large language models. It significantly accelerates inference through…

Practical Solutions for AI Operations Guardrails for Reliable and Safe AI Portkey AI replaces the Gateway Framework with Guardrails, ensuring reliable interaction with large language models (LLMs). Guardrails format requests and responses according to predefined standards,…