​[[{“value”:” In computational linguistics and artificial intelligence, researchers continually strive to optimize the performance of large language models (LLMs). These models, renowned for their capacity to process a vast array of language-related tasks, face significant challenges due to their expansive size. For instance, models like… Read More »Seeking Faster, More Efficient AI? Meet FP6-LLM: the Breakthrough in GPU-Based Quantization for Large Language Models Adnan Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” For LLMs, auto-regressive decoding is now considered the gold standard. Because LLMs generate output tokens individually, the procedure is time-consuming and expensive. Methods based on speculative sampling provide an answer to this problem. In the first, called the “draft” phase, LLMs are hypothesized at… Read More »Seeking Speed without Loss in Large Language Models? Meet EAGLE: A Machine Learning Framework Setting New Standards for Lossless Acceleration Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In the realm of artificial intelligence, Large Multimodal Models (LMMs) have exhibited remarkable problem-solving capabilities across diverse tasks, such as zero-shot image/video classification, zero-shot image/video-text retrieval, and multimodal question answering (QA). However, recent studies highlight a substantial gap between powerful LMMs and expert-level artificial… Read More »Meet CMMMU: A New Chinese Massive Multi-Discipline Multimodal Understanding Benchmark Designed to Evaluate Large Multimodal Models LMMs Vineet Kumar Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In the dynamic field of software development, integrating large language models (LLMs) has initiated a new chapter, especially in code intelligence. These sophisticated models have been pivotal in automating various aspects of programming, from identifying bugs to generating code, revolutionizing how coding tasks are… Read More »DeepSeek-AI Introduce the DeepSeek-Coder Series: A Range of Open-Source Code Models from 1.3B to 33B and Trained from Scratch on 2T Tokens Muhammad Athar Ganaie Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Evaluating LLMs as versatile agents is crucial for their integration into practical applications. However, existing evaluation frameworks face challenges in benchmarking diverse scenarios, maintaining partially observable environments, and capturing multi-round interactions. Current assessments often focus on a simplified final success rate metric, providing limited… Read More »This AI Paper from China Introduces ‘AGENTBOARD’: An Open-Source Evaluation Framework Tailored to Analytical Evaluation of Multi-Turn LLM Agents Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Transformers have found widespread application in diverse tasks spanning text classification, map construction, object detection, point cloud analysis, and audio spectrogram recognition. Their versatility extends to multimodal tasks, exemplified by CLIP’s use of image-text pairs for superior image recognition. This underscores transformers’ efficacy in… Read More »Researchers from the Chinese University of Hong Kong and Tencent AI Lab Propose a Multimodal Pathway to Improve Transformers with Irrelevant Data from Other Modalities Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models (LLMs) based on transformer architectures have emerged in recent years. Models such as Chat-GPT and LLaMA-2 demonstrate how the parameters of LLMs have rapidly increased, ranging from several billion to tens of trillions. Although LLMs are very good generators, they have… Read More »Meet BiTA: An Innovative AI Method Expediting LLMs via Streamlined Semi-Autoregressive Generation and Draft Verification Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Resilience plays a pivotal role in the development of any workload, and generative AI workloads are no different. There are unique considerations when engineering generative AI workloads through a resilience lens. Understanding and prioritizing resilience is crucial for generative AI workloads to meet organizational… Read More »Designing generative AI workloads for resilience Jennifer Moran AWS Machine Learning Blog

​[[{“value”:” Data is the foundation to capturing the maximum value from AI technology and solving business problems quickly. To unlock the potential of generative AI technologies, however, there’s a key prerequisite: your data needs to be appropriately prepared. In this post, we describe how use… Read More »Analyze security findings faster with no-code data preparation using generative AI and Amazon SageMaker Canvas Sudeesh Sasidharan AWS Machine Learning Blog

​[[{“value”:” One of the more intriguing developments in the dynamic field of computer vision is the efficient processing of visual data, which is essential for applications ranging from automated image analysis to the development of intelligent systems. A pressing challenge in this area is interpreting… Read More »UC Berkeley and UCSF Researchers Propose Cross-Attention Masked Autoencoders (CrossMAE): A Leap in Efficient Visual Data Processing Adnan Hassan Artificial Intelligence Category – MarkTechPost