​[[{“value”:” The surge of advertisements across online platforms presents a formidable challenge in maintaining content integrity and adherence to advertising policies. While foundational, traditional mechanisms of content moderation grapple with the dual challenges of scale and efficiency, often becoming a bottleneck in the dynamic and… Read More »Revolutionizing Content Moderation in Digital Advertising: A Scalable LLM Approach Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large Multimodal Models (LMMs), driven by AI advancements, revolutionize vision and language tasks but are mainly centered on English, neglecting non-English languages. This oversight excludes billions of speakers of languages like Chinese, Hindi, Spanish, French, Arabic, Bengali, Russian, Urdu, and Japanese. The lack of… Read More »Researchers from Mohamed bin Zayed University of AI Developed ‘PALO’: A Polyglot Large Multimodal Model for 5B People Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Efficiently supporting LLMs is becoming more critical as large language models (LLMs) become widely used. Since getting a new token involves getting all of the LLM’s parameters, speeding up LLM inference is difficult. The hardware is underutilized throughout generation due to this I/O constraint.… Read More »CMU Researchers Introduce Sequoia: A Scalable, Robust, and Hardware-Aware Algorithm for Speculative Decoding Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In artificial intelligence, achieving efficiency in neural networks is a paramount challenge for researchers due to its rapid evolution. The quest for methods minimizing computational demands while preserving or enhancing model performance is ongoing. A particularly intriguing strategy lies in optimizing neural networks through… Read More »The University of Calgary Unleashes Game-Changing Structured Sparsity Method: SRigL Muhammad Athar Ganaie Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The challenge of tailoring general-purpose LLMs to specific tasks without extensive retraining or additional data persists even after significant advancements in the field. Adapting LMs for specialized tasks often requires substantial computational resources and domain-specific data. Traditional methods involve finetuning the entire model on… Read More »This AI Paper from Harvard Introduces Q-Probing: A New Frontier in Machine Learning for Adapting Pre-Trained Language Models Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The quest for clean, usable data for pretraining Large Language Models (LLMs) resembles searching for treasure amidst chaos. While rich with information, the digital realm is cluttered with extraneous content that complicates the extraction of valuable data. This challenge becomes particularly pronounced when considering… Read More »NeuScraper: Pioneering the Future of Web Scraping for Enhanced Large Language Model Pretraining Adnan Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The CHiME-8 MMCSG task focuses on the challenge of transcribing conversations recorded using smart glasses equipped with multiple sensors, including microphones, cameras, and inertial measurement units (IMUs). The dataset aims to help researchers to solve problems like activity detection and speaker diarization. While the… Read More »Meta AI Releases MMCSG: A Dataset with 25h+ of Two-Sided Conversations Captured Using Project Aria Pragati Jhunjhunwala Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Point clouds serve as a prevalent representation of 3D data, with the extraction of point-wise features being crucial for various tasks related to 3D understanding. While deep learning methods have made significant strides in this domain, they often rely on large and diverse datasets… Read More »Meet Swin3D++: An Enhanced AI Architecture based on Swin3D for Efficient Pretraining on Multi-Source 3D Point Clouds Mohammad Arshad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” At AWS re:Invent 2023, we announced the general availability of Knowledge Bases for Amazon Bedrock. With a knowledge base, you can securely connect foundation models (FMs) in Amazon Bedrock to your company data for fully managed Retrieval Augmented Generation (RAG). In a previous post,… Read More »Knowledge Bases for Amazon Bedrock now supports hybrid search Mani Khanuja AWS Machine Learning Blog

​[[{“value”:” Creating a model that excels at understanding, holding conversations, and solving complex problems has always been challenging in artificial intelligence. The goal is to develop a system that can chat like a human and think and reason through difficult questions. This balancing act is… Read More »Meet AlphaMonarch-7B: One of the Best-Performing Non-Merge 7B Models on the Open LLM Leaderboard Niharika Singh Artificial Intelligence Category – MarkTechPost