​ Large language models (LLM) have made great strides recently, demonstrating amazing performance in tasks conversationally requiring natural language processing. Examples include the commercial products ChatGPT, Claude, Bard, text-only GPT-4, and community opensource LLama, Alpaca, Vicuna, ChatGLM, MOSS, etc. Thanks to their unheard-of powers, they… Read More »A New AI Research Introduces GPT4RoI: A Vision-Language Model based on Instruction Tuning Large Language Model (LLM) on Region-Text Pairs Aneesh Tickoo Artificial Intelligence Category – MarkTechPost

​ The human brain is one of the most complex systems nature has ever created. The neurons interact with each other by forming recurring neural links and transmitting information through impulses.  Due to their incredible logical reasoning and numerical analysis methods, researchers try to implement… Read More »The University Of Pennsylvania Researchers Introduced An Alternative AI Approach To Design And Program RNN-Based Reservoir Computers Mohammad Arshad Artificial Intelligence Category – MarkTechPost

​ Natural Language Processing, one of the primary subfields of Artificial Intelligence, is advancing at an extraordinary pace. With its ability to enable a computer to understand human language the way it is spoken and written, NLP has a number of use cases. One such… Read More »CarperAI Introduces OpenELM: An Open-Source Library Designed to Enable Evolutionary Search With Language Models In Both Code and Natural Language Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​Posted by Jerry Wei, Student Researcher, and Denny Zhou, Principal Scientist, Google Research A key feature of human intelligence is that humans can learn to perform new tasks by reasoning using only a few examples. Scaling up language models has unlocked a range of new… Read More »Symbol tuning improves in-context learning in language models Google AI Google AI Blog

​ Recent years have shown amazing growth in deep learning neural networks (DNNs). This growth can be seen in more accurate models and even opening new possibilities with generative AI: large language models (LLMs) that synthesize natural language, text-to-image generators, and more. These increased capabilities… Read More »Effectively solve distributed training convergence issues with Amazon SageMaker Hyperband Automatic Model Tuning Uri Rosenberg AWS Machine Learning Blog

​ Big foundational models like CLIP, Stable Diffusion, and Flamingo have radically improved multimodal deep learning over the past few years. Joint text-image modeling has gone from being a niche application to one of the (if not the) most relevant issues in today’s artificial intelligence… Read More »LAION AI Introduces Video2Dataset: An Open-Source Tool Designed To Curate Video And Audio Datasets Efficiently And At Scale Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost

​ A watershed moment on Nov. 22, 2022, was mostly virtual, yet it shook the foundations of nearly every industry on the planet. On that day, OpenAI released ChatGPT, the most advanced artificial intelligence chatbot ever developed. This set off demand for generative AI applications… Read More »AI-Fueled Productivity: Generative AI Opens New Era of Efficiency Across Industries Cliff Edwards – Archives Page 1 | NVIDIA Blog

​ A molecule’s structure dictates its properties and functions. That is why structure prediction is a major issue in molecular science. Molecular scientists are hailing the breakthrough accuracy of deep learning approaches like AlphaFold and RoseTTAFold in identifying the most probable structures for proteins from… Read More »Microsoft AI Research Introduce a Novel Deep Learning Framework Called Distributional Graphormer (DiG) to Predict the Equilibrium Distribution of Molecular Systems. Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost

​ For various downstream tasks, including language and code translation, compositional thinking, and fundamental arithmetic operations, large language models like GPT-3/4, PaLM, and LaMDA have shown general-purpose features, sometimes emergent skills. Perhaps surprisingly, the training objective of the model, which is often an auto-regressive loss… Read More »A New Study from the University of Wisconsin Investigates How Small Transformers Trained from Random Initialization can Efficiently Learn Arithmetic Operations Using the Next Token Prediction Objective Aneesh Tickoo Artificial Intelligence Category – MarkTechPost