OpenAI in ChatGPT partnership with Arizona State University

MIT had a remarkable year in 2023, from President Sally Kornbluth’s inauguration to breakthroughs in various fields. Highlights include AI developments, Nobel Prize wins, climate innovations, and advancements in health and art. MIT remained at the…

Large Language Models, like GPT-3, have revolutionized Natural Language Processing by scaling to billions of parameters and incorporating extensive datasets. Researchers have also introduced Speech Language Models directly trained on speech, leading to the development of…

Automated Design of Agentic Systems (ADAS): Revolutionizing AI System Design Practical Solutions and Value Automated design in artificial intelligence (AI) is a cutting-edge field focused on developing systems capable of independently generating and optimizing their components.…

Large Language Models (LLMs) have revolutionized the AI community with their versatile applications in Natural Language Processing, Natural Language Generation, and Computer Vision. Bytedance’s research introduces DiffPortrait3D, a groundbreaking conditional diffusion model capable of creating photorealistic…

A study involving 32 papers reviewed the application of explainable AI in poverty estimation using satellite imagery and deep learning. It found that transparency, interpretability, and domain knowledge—key elements of explainable machine learning—vary and often fall…

OpenAI unveils a comprehensive strategy to counter misinformation during elections using advanced AI tools. The company aims to prevent misuse of its technology by blocking creation of deceptive chatbots and pausing its use in political campaigning.…

Researchers at Anthropic have addressed Claude 2.1’s hesitation in answering questions about individual sentences within its 200K token context. By introducing a prompt containing the sentence “Here is the most relevant sentence in the context,” they…

Text-to-image diffusion models have revolutionized AI image generation, simulating human creativity. Orthogonal Finetuning enhances control over these models, maintaining semantic generation ability. It enables subject-driven image generation, improves efficiency, and has applications in digital art, advertising,…

Challenges of Traditional LLM Agents Traditional large language model (LLM) agents struggle in real-world applications because they lack flexibility and adaptability. These agents rely on a fixed set of actions, making them less effective in complex,…

Apple researchers have developed DeepPCR, an innovative algorithm to speed up neural network training and inference. It reduces computational complexity from O(L) to O(log2 L), achieving significant speed gains, particularly for high values of L. DeepPCR…

Understanding and Mitigating Knowledge Contamination in Large Language Models Understanding and Mitigating Knowledge Contamination in Large Language Models Introduction to Large Language Models (LLMs) Large language models (LLMs) are advanced AI systems that learn from extensive…

Alibaba researchers have developed Qwen-Audio, a series of large-scale audio-language models that address the challenge of limited pre-trained audio models. Qwen-Audio achieves impressive performance across diverse benchmark tasks without task-specific fine-tuning. Qwen-Audio-Chat extends these capabilities to…

Understanding Meta Chain-of-Thought (Meta-CoT) Large Language Models (LLMs) have made great strides in artificial intelligence, especially in understanding and generating language. However, they struggle with complex reasoning tasks that require multiple steps and non-linear thinking. Traditional…

Advancing Real-World Graph Question Answering with G-Retriever Practical Solutions and Value Large Language Models (LLMs) have made significant strides in artificial intelligence, but their ability to process complex structured data, particularly graphs, remains challenging. In our…

Modern Visualization Tools and Their Challenges Many popular visualization tools, such as Charticulator, Data Illustrator, and ggplot2, require data to be organized in a specific way called “tidy data.” This means each variable should be in…

Cohere For AI Launches Aya Vision: A New Era in Multilingual and Multimodal Communication Cohere For AI has introduced Aya Vision, an innovative open-weights vision model designed to enhance multilingual and multimodal communication. This advancement aims…

Amazon introduced Amazon Q, an AI chatbot for workplace assistance from AWS, focusing on streamlining office tasks while prioritizing data security. Competing with Microsoft and Google, it’s priced at $20/user/month. Amazon also plans to enhance AI…

UC Berkeley and Stanford researchers have developed a parameter-efficient fine-tuning method called Low-Rank Adaptation (LoRA) for deploying language models. The method, S-LoRA, allows thousands of adapters to run efficiently on a single GPU or across multiple…

L1 and L2 regularization are techniques used in machine learning to prevent overfitting. Overfitting occurs when a model is too complex and learns from both the underlying patterns and the noise in the training data, resulting…