​[[{“value”:” Large language models (LLMs) have transformed the landscape of natural language processing, becoming indispensable tools across industries such as healthcare, education, and technology. These models perform complex tasks, including language translation, sentiment analysis, and code generation. However, their exponential growth in scale and adoption… Read More »Chameleon: An AI System for Efficient Large Language Model Inference Using Adaptive Caching and Multi-Level Scheduling Techniques Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Founded in 2022, Perplexity AI has quickly emerged as a significant player in artificial intelligence, particularly in AI-driven search technologies. With a strong focus on innovation and user-centric features, the company has introduced groundbreaking advancements while securing notable investments to expand its operations. Recent… Read More »How Perplexity AI is Transforming Search: Recent Innovations, Strategic Partnerships, and Market Advancements in 2024 Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Trailing the advances made by AI in drug discovery, one can say there is a vast amount of untapped potential. Therapeutic nanobodies, particularly, have had relatively limited breakthroughs as they require complex interdisciplinary knowledge. The COVID-19 pandemic urged the development of therapeutic nanobodies that… Read More »The Virtual Lab: AI Agents Design New SARS-CoV-2 Nanobodies with Experimental Validation Afeerah Naseem Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Parallel computing continues to advance, addressing the demands of high-performance tasks such as deep learning, scientific simulations, and data-intensive computations. A fundamental operation within this domain is matrix multiplication, which underpins many computational workflows. Recent hardware innovations, like Tensor Core Units (TCUs), offer efficient… Read More »Huawei Research Developed MatMulScan: A Parallel Scan Algorithm Transforming Parallel Computing with Tensor Core Units, Enhancing Efficiency and Scalability for Large-Scale Matrix Operations Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Geometry representations play a crucial role in solving complex 3D vision problems. The rapid evolution of deep learning has sparked significant interest in developing neural network-compatible geometric data representations. Recent technological advances, particularly those centered on coordinate networks, have demonstrated promising capabilities in modeling… Read More »Geometry Distributions: Advancing Neural 3D Surface Modeling with Diffusion Models Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In recent years, the evolution of artificial intelligence has brought forth increasingly sophisticated large language models (LLMs). However, training these models remains a complex challenge due to their immense computational requirements. Traditionally, training such models has been possible only in centralized environments with high-bandwidth… Read More »PRIME Intellect Releases INTELLECT-1 (Instruct + Base): The First 10B Parameter Language Model Collaboratively Trained Across the Globe Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Deep learning techniques are increasingly applied to neuroimaging analysis, with 3D CNNs offering superior performance for volumetric imaging. However, their reliance on large datasets is challenging due to the high cost and effort required for medical data collection and annotation. As an alternative, 2D… Read More »Enhancing Deep Learning-Based Neuroimaging Classification with 3D-to-2D Knowledge Distillation Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The rapid development of artificial intelligence (AI) has produced models with powerful capabilities, such as language understanding and vision processing. However, deploying these models on edge devices remains challenging due to limitations in computational power, memory, and energy efficiency. The need for lightweight models… Read More »Tsinghua University Researchers Released the GLM-Edge Series: A Family of AI Models Ranging from 1.5B to 5B Parameters Designed Specifically for Edge Devices Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The new efficient multi-adapter inference feature of Amazon SageMaker unlocks exciting possibilities for customers using fine-tuned models. This capability integrates with SageMaker inference components to allow you to deploy and manage hundreds of fine-tuned Low-Rank Adaptation (LoRA) adapters through SageMaker APIs. Multi-adapter inference handles… Read More »Easily deploy and manage hundreds of LoRA adapters with SageMaker efficient multi-adapter inference Dmitry Soldatkin AWS Machine Learning Blog

​[[{“value”:” Machine learning is advancing rapidly, particularly in areas requiring extensive data processing, such as natural language understanding and generative AI. Researchers are constantly striving to design algorithms that maximize computational efficiency while improving the accuracy and performance of large-scale models. These efforts are critical… Read More »Microsoft Researchers Present a Novel Implementation of MH-MoE: Achieving FLOPs and Parameter Parity with Sparse Mixture-of-Experts Models Nikhil Artificial Intelligence Category – MarkTechPost