​[[{“value”:” NVIDIA is taking an array of advancements in rendering, simulation and generative AI to SIGGRAPH 2024, the premier computer graphics conference, which will take place July 28 – Aug. 1 in Denver. More than 20 papers from NVIDIA Research introduce innovations advancing synthetic data… Read More »Mile-High AI: NVIDIA Research to Present Advancements in Simulation and Gen AI at SIGGRAPH Aaron Lefohn – Archives Page 1 | NVIDIA Blog

​[[{“value”:” One of the emerging challenges in artificial intelligence is whether next-token prediction can truly model human intelligence, particularly in planning and reasoning. Despite its extensive application in modern language models, this method might be inherently limited when it comes to tasks that require advanced… Read More »Beyond Next-Token Prediction: Overcoming AI’s Foresight and Decision-Making Limits Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Vision-language models have evolved significantly over the past few years, with two distinct generations emerging. The first generation, exemplified by CLIP and ALIGN, expanded on large-scale classification pretraining by utilizing web-scale data without requiring extensive human labeling. These models used caption embeddings obtained from… Read More »Google DeepMind Unveils PaliGemma: A Versatile 3B Vision-Language Model VLM with Large-Scale Ambitions Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Natural Language Processing (NLP) focuses on the interaction between computers and humans through natural language. It encompasses tasks such as translation, sentiment analysis, and question answering, utilizing large language models (LLMs) to achieve high accuracy and performance. LLMs are employed in numerous applications, from… Read More »This AI Paper from Cornell Introduces UCB-E and UCB-E-LRF: Multi-Armed Bandit Algorithms for Efficient and Cost-Effective LLM Evaluation Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Existing open-source large multimodal models (LMMs) face several significant limitations. They often lack native integration and require adapters to align visual representations with pre-trained large language models (LLMs). Many LMMs are restricted to single-modal generation or rely on separate diffusion models for visual modeling… Read More »Anole: An Open, Autoregressive, Native Large Multimodal Model for Interleaved Image-Text Generation Pragati Jhunjhunwala Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The rapid advancement of LLMs has enabled the creation of highly capable autonomous agents. However, multi-agent frameworks need help integrating diverse third-party agents due to ecosystem constraints and limited by single-device setups and rigid communication pipelines. Inspired by the Internet’s success in fostering human… Read More »Internet of Agents (IoA): A Novel Artificial Intelligence AI Framework for Agent Communication and Collaboration Inspired by the Internet Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Deep learning systems must be highly integrated and have access to vast amounts of computational resources to function properly. Consequently, building massive data centers with hundreds of specialized hardware accelerators is becoming increasingly necessary for large-scale applications. The best course of action is to… Read More »LayerShuffle: Robust Vision Transformers for Arbitrary Layer Execution Orders Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Significant issues arise when programming knowledge and task assistants based on Large Language Models (LLMs) carefully follow developer-provided policies. To satisfy the requests and demands of users, these agents must reliably retrieve and provide accurate and pertinent information. However, a typical problem with these… Read More »Researchers at Stanford Introduce KITA: A Programmable AI Framework for Building Task-Oriented Conversational Agents that can Manage Intricate User Interactions Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Pretrained large models have shown impressive abilities in many different fields. Recent research focuses on ensuring these models align with human values and avoid harmful behaviors. To achieve this, alignment methods are crucial, where two primary methods are supervised fine-tuning (SFT) and reinforcement learning… Read More »Generalizable Reward Model (GRM): An Efficient AI Approach to Improve the Generalizability and Robustness of Reward Learning for LLMs Sajjad Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models (LLMs) have been instrumental in various applications, such as chatbots, content creation, and data analysis, due to their capability to process vast amounts of textual data efficiently. The rapid advancement in AI technology has heightened the demand for high-quality training data,… Read More »Microsoft Research Introduces AgentInstruct: A Multi-Agent Workflow Framework for Enhancing Synthetic Data Quality and Diversity in AI Model Training Asif Razzaq Artificial Intelligence Category – MarkTechPost