A significant bottleneck in large language models (LLMs) that hampers their deployment in real-world applications is the slow inference speeds. LLMs, while powerful, require substantial computational resources to generate outputs, leading to delays that can negatively impact user experience, increase operational costs, and limit the practical use of these models in time-sensitive scenarios. As LLMs… →
Speculative decoding is emerging as a vital strategy to enhance high-throughput long-context inference, especially as the need for inference with large language models (LLMs) continues to grow across numerous applications. Together AI’s research on speculative decoding tackles the problem of improving inference throughput for LLMs that deal with long input sequences and large batch sizes.… →
In computer vision, backbone architectures are critical in image recognition, object detection, and semantic segmentation tasks. These backbones extract local and global features from images, enabling machines to understand complex patterns. Traditionally, convolutional layers have been the primary component in these models, but recent advancements incorporate attention mechanisms, which enhance the model’s ability to capture… →
Online social networks have become essential to modern communication, shaping how individuals share information, express opinions, and engage. Platforms like Reddit facilitate large-scale discussions, enabling millions of users to participate in conversations about various topics. One area of interest for researchers is understanding how these online conversations evolve when users are asked to make moral… →
Building on LG AI Research’s remarkable achievements in AI language models, especially with the launch of EXAONE 3.0, the development of EXAONEPath represents another significant milestone. This new chapter in EXAONE’s journey focuses on transforming digital histopathology, a critical area in medical diagnostics, by addressing the complex challenges of Whole Slide Images (WSIs) in histopathology… →
Medical LLMs like ClinicalCamel 70B and Llama3-OpenBioLLM 70B have shown strong performance in various medical NLP tasks, but no model specifically tailored to the cancer domain currently exists. Additionally, these models, with billions of parameters, are computationally demanding for many healthcare systems. A cancer-focused LLM, integrating specialized cancer knowledge, could significantly improve diagnosis and treatment… →
Apple’s latest release, the iPhone 16, places a strong emphasis on on-device artificial intelligence (AI), powered by its new Apple Intelligence platform. Unlike cloud-reliant AI systems, Apple is focusing on maintaining privacy by processing AI functions directly on the device with the A18 Bionic chip. This enables faster, more personalized, and more secure interactions, marking… →
Text classification has become a crucial tool in various applications, including opinion mining and topic classification. Traditionally, this task required extensive manual labeling and a deep understanding of machine learning techniques, presenting significant barriers to entry. The advent of large language models (LLMs) like ChatGPT has revolutionized this field, enabling zero-shot classification without additional training.… →
The field of Artificial Intelligence (AI-driven) agentic systems has seen significant change in recent times. The deployment of sophisticated, scalable systems depends heavily on workflows. A team of researchers has introduced llama-deploy, a unique and user-friendly solution designed to make agentic workflows constructed using LlamaIndex easier to scale and deploy. With just a few lines… →