​ As technology continues to advance at an astonishing pace, Cerebras Systems and G42 have just taken a giant leap forward in the world of artificial intelligence. In a groundbreaking partnership, they have successfully completed a 4-Exaflop AI supercomputer, marking a significant milestone in the… Read More »Cerebras and G42 Break New Ground with 4-Exaflop AI Supercomputer: Paving the Way for 8-Exaflops Asif Razzaq Artificial Intelligence Category – MarkTechPost

​ Modern self-driving systems frequently use Large-scale manually annotated datasets to train object detectors to recognize the traffic participants in the picture. Auto-labeling methods that automatically produce sensor data labels have recently gained more attention. Auto-labeling may provide far bigger datasets at a fraction of… Read More »Researchers from Waabi and the University of Toronto Introduce LabelFormer: An Efficient Transformer-Based AI Model to Refine Object Trajectories for Auto-Labelling Aneesh Tickoo Artificial Intelligence Category – MarkTechPost

​ Amid the growing complexities of academic dishonesty in online education, Rosalyn has introduced StableSight, an advanced AI system crafted to counter cheating methods, encompassing generative AI and organized cheating rings during online exams. The surge in demand for professional certifications, driven by a significant… Read More »Rosalyn Unveils StableSight AI to Combat Rising Online Exam Cheating Niharika Singh Artificial Intelligence Category – MarkTechPost

​ At a basic level, Machine Learning (ML) technology learns from data to make predictions. Businesses use their data with an ML-powered personalization service to elevate their customer experience. This approach allows businesses to use data to derive actionable insights and help grow their revenue… Read More »Implement real-time personalized recommendations using Amazon Personalize Cristian Marquez AWS Machine Learning Blog

​ One of the most common applications of generative AI and large language models (LLMs) is answering questions based on a specific external knowledge corpus. Retrieval-Augmented Generation (RAG) is a popular technique for building question answering systems that use an external knowledge base. To learn… Read More »Improve LLM responses in RAG use cases by interacting with the user Antonia Schulze AWS Machine Learning Blog

​ A widely acclaimed large language model for genomic data has demonstrated its ability to generate gene sequences that closely resemble real-world variants of SARS-CoV-2, the virus behind COVID-19. Called GenSLMs, the model, which last year won the Gordon Bell special prize for high performance… Read More »Gen AI for the Genome: LLM Predicts Characteristics of COVID Variants Isha Salian – Archives Page 1 | NVIDIA Blog

​ Home Table of Contents Faster R-CNNs Object Detection and Deep Learning Measuring Object Detector Performance From Where Do the Ground-Truth Examples Come? Why Do We Use Intersection over Union (IoU)? Mean Average Precision (mAP) The (Faster) R-CNN Architecture A Brief History of R-CNN R-CNN… Read More »Faster R-CNNs Hector Martinez PyImageSearch

​ Optimizing machine learning models with dynamic shapes can be crucial for achieving better performance and flexibility. Dynamic shapes refer to the ability of a model to handle input data with varying dimensions during runtime. Users utilize frameworks that support dynamic computation graphs, such as… Read More »This AI Paper Introduces Relax: A Compiler Abstraction for Optimizing End-to-End Dynamic Machine Learning Workloads Mohammad Arshad Artificial Intelligence Category – MarkTechPost

​ Understanding the intricate networks in animal brains has been a big challenge for scientists, especially when studying diseases like Alzheimer’s. Traditional methods could have been faster and cheaper.  Before SmartEM, scientists used regular microscopes, but it took a long time to capture the details… Read More »MIT Researchers Developed SmartEM: An AI Technology that Takes Electron Microscopy to the Next Level by Seamlessly Integrating Real-Time Machine Learning into the Imaging Process Niharika Singh Artificial Intelligence Category – MarkTechPost

​ Researchers from Google DeepMind explore the in-context learning (ICL) capabilities of large language models, specifically transformers, trained on diverse task families. However, their study needs to work on out-of-domain tasks, revealing limitations in generalization for functions beyond the pretraining distribution. The findings suggest that… Read More »This AI Paper from Google DeepMind Studies the Gap Between Pretraining Data Composition and In-Context Learning in Pretrained Transformers Sana Hassan Artificial Intelligence Category – MarkTechPost