​ In-context learning is a natural language paradigm that demonstrates the ability of pre-trained models to pick up new behaviors using only a small number of example prompts as input. Most recent research indicates that large language models (LLMs), such as GPT-3 and the newest… Read More »Meet RECITE: A New Paradigm To Help Large Language Models (LLMs) Generate More Accurate Factual Knowledge Without Retrieving From An External Corpus Khushboo Gupta Artificial Intelligence Category – MarkTechPost

​ With the growing popularity and advancements in Artificial Intelligence, AI has successfully stepped into the field of Robotics. Robotics is a branch of engineering in which machines are developed and programmed to perform tasks without human involvement. A number of AI technologies are being… Read More »Researchers From Stanford Introduce Voltron: A Framework For Language-Driven Representation Learning From Human Videos Associated Captions Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​ Nowadays, text-based generative picture models are capable of creating a wide range of photorealistic images. Many recent efforts have expanded the text-to-image models to further accomplish customized generation by adding conditions such as segmentation maps, scene graphs, drawings, depth maps, and inpainting masks or… Read More »Alibaba AI Research Proposes Composer: A Large (5 Billion Parameters) Controllable Diffusion Model Trained on Billions of (Text, Image) Pairs Aneesh Tickoo Artificial Intelligence Category – MarkTechPost

​Posted by Florian Hartmann, Software Engineer, and Peter Kairouz, Research Scientist, Google Research Federated learning is a distributed way of training machine learning (ML) models where data is locally processed and only focused model updates and metrics that are intended for immediate aggregation are shared… Read More »Distributed differential privacy for federated learning Google AI Google AI Blog

​ Financial market participants are faced with an overload of information that influences their decisions, and sentiment analysis stands out as a useful tool to help separate out the relevant and meaningful facts and figures. However, the same piece of news can have a positive… Read More »Accelerate hyperparameter grid search for sentiment analysis with BERT models using Weights & Biases, Amazon EKS, and TorchElastic Ankur Srivastava AWS Machine Learning Blog

​ Amazon Kendra is an easy-to-use intelligent search service that allows you to integrate search capabilities with your applications so users can find information stored across data sources like Amazon Simple Storage Service , OneDrive and Google Drive; applications such as SalesForce, SharePoint and Service Now;… Read More »Search for answers accurately using Amazon Kendra S3 Connector with VPC support Maran Chandrasekaran AWS Machine Learning Blog

​ As deep learning models grow in size and complexity, it becomes more difficult to articulate why and how they arrive at a given result. There are several different directions that researchers are exploring to improve the interpretability of AI systems. Attempts at mechanistic interpretability… Read More »Deepmind Open Sources Tracr: A Tool for Compiling Human-Readable Code to the Weights of a Transformer Model Tanushree Shenwai Artificial Intelligence Category – MarkTechPost

​ Neural rendering is a cutting-edge technology that uses artificial intelligence and deep learning to create photorealistic images and animations. Unlike traditional rendering techniques that rely on mathematical models, neural rendering algorithms learn to replicate the complex interactions between light and materials in the real… Read More »A New Artificial Intelligence (AI) Study From CMU and Meta Proposes a Framework for Efficient Neural Relighting of Articulated Hand Models Daniele Lorenzi Artificial Intelligence Category – MarkTechPost