​ Amazon Textract is a machine learning (ML) service that automatically extracts text, handwriting, and data from any document or image. AnalyzeDocument Layout is a new feature that allows customers to automatically extract layout elements such as paragraphs, titles, subtitles, headers, footers, and more from… Read More »Amazon Textract’s new Layout feature introduces efficiencies in general purpose and generative AI document processing tasks Anjan Biswas AWS Machine Learning Blog

​ ChatGPT has revolutionized the capability of easily producing a wide range of fluent text on a wide range of topics. But how good are they really? Language models are prone to factual errors and hallucinations. This lets readers know if such tools have been… Read More »UC Berkeley Researchers Introduce Ghostbuster: A SOTA AI Method for Detecting LLM-Generated Text Mohammad Arshad Artificial Intelligence Category – MarkTechPost

​ In a recent announcement, Google’s DeepMind, in collaboration with YouTube, introduced Lyria, a music generation model poised to transform the landscape of artistic expression. This innovative technology, accompanied by two experimental toolsets, Dream Track and Music AI, marks a significant leap in AI-assisted music… Read More »Google Deepmind and YouTube Researchers Announce Lyria: An Advanced AI Music Generation Model Niharika Singh Artificial Intelligence Category – MarkTechPost

​ One of the main paradigms in machine learning is learning representations from several modalities. Pre-training broad pictures on unlabeled multimodal data and then fine-tuning ask-specific labels is a common learning strategy today. The present multimodal pretraining techniques are mostly derived from earlier research in… Read More »This AI Paper Proposes FACTORCL: A New Multimodal Representation Learning Method to Go Beyond Multi-View Redundancy Aneesh Tickoo Artificial Intelligence Category – MarkTechPost

​ KTRL+F task is a knowledge-augmented in-document search problem that requires real-time identification of semantic targets within a document, incorporating external knowledge through a single natural query. Existing models face challenges such as hallucinations, low latency, and difficulty leveraging superficial knowledge. To address this, researchers… Read More »KAIST AI Researchers Introduce KTRL+F: A Knowledge-Augmented in-Document Search Task that Necessitates Real-Time Identification of Semantic Targets within a Document Adnan Hassan Artificial Intelligence Category – MarkTechPost

​ Retrieval Augmented Generation (RAG) allows you to provide a large language model (LLM) with access to data from external knowledge sources such as repositories, databases, and APIs without the need to fine-tune it. When using generative AI for question answering, RAG enables LLMs to… Read More »Use Amazon SageMaker Studio to build a RAG question answering solution with Llama 2, LangChain, and Pinecone for fast experimentation Anastasia Tzeveleka AWS Machine Learning Blog

​ KT Corporation is one of the largest telecommunications providers in South Korea, offering a wide range of services including fixed-line telephone, mobile communication, and internet, and AI services. KT’s AI Food Tag is an AI-based dietary management solution that identifies the type and nutritional… Read More »KT’s journey to reduce training time for a vision transformers model using Amazon SageMaker Youngjoon Choi AWS Machine Learning Blog

​ Tencent AI Lab researchers address challenges in the reliability of retrieval-augmented language models (RALMs), which may retrieve irrelevant information, leading to misguided responses. The proposed approach, CHAIN-OF-NOTING (CON), aims to enhance RALM. CON-equipped RALMs exhibit substantial performance improvements across open-domain QA benchmarks, achieving notable… Read More »Tencent AI Lab Introduces Chain-of-Noting (CoN) to Improve the Robustness and Reliability of Retrieval-Augmented Language Models Adnan Hassan Artificial Intelligence Category – MarkTechPost

​ Reasoning efficiently across extended sequences is a major difficulty in machine learning. Recently, convolutions have emerged as a critical primitive for sequence modeling, supporting state-of-the-art performance in language modeling, time-series analysis, computer vision, DNA modeling, and more. Despite these impressive quality findings and additional… Read More »Stanford University Researchers Introduce FlashFFTConv: A New Artificial Intelligence System for Optimizing FFT Convolutions for Long Sequences Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost