Training large language models (LLMs) is an involved process that requires planning, computational resources, and domain expertise. Training large language models (LLMs) is an involved process that requires planning, computational resources, and domain expertise. Read More
[[{“value”:” The pre-training of language models (LMs) plays a crucial role in enabling their ability to understand and generate text. However, a significant challenge lies in effectively leveraging the diversity of training corpora, which often include data from varied sources such as Wikipedia, blogs, and… Read More »Researchers from Princeton University Introduce Metadata Conditioning then Cooldown (MeCo) to Simplify and Optimize Language Model Pre-training Nikhil Artificial Intelligence Category – MarkTechPost
[[{“value”:” Complex domains like social media, molecular biology, and recommendation systems have graph-structured data that consists of nodes, edges, and their respective features. These nodes and edges do not have a structured relationship, so addressing them using graph neural networks (GNNs) is essential. However, GNNs… Read More »PyG-SSL: An Open-Source Library for Graph Self-Supervised Learning and Compatible with Various Deep Learning and Scientific Computing Backends Afeerah Naseem Artificial Intelligence Category – MarkTechPost
[[{“value”:” Large language models (LLMs) have revolutionized natural language processing, enabling applications that range from automated writing to complex decision-making aids. However, ensuring these models produce factually accurate responses remains a significant challenge. At times, LLMs generate outputs that appear credible but are factually incorrect,… Read More »DeepMind Research Introduces The FACTS Grounding Leaderboard: Benchmarking LLMs’ Ability to Ground Responses to Long-Form Input Aswin Ak Artificial Intelligence Category – MarkTechPost
[[{“value”:” Advancements in neural networks have brought significant changes across domains like natural language processing, computer vision, and scientific computing. Despite these successes, the computational cost of training such models remains a key challenge. Neural networks often employ higher-order tensor weights to capture complex relationships,… Read More »Researchers from Caltech, Meta FAIR, and NVIDIA AI Introduce Tensor-GaLore: A Novel Method for Efficient Training of Neural Networks with Higher-Order Tensor Weights Asif Razzaq Artificial Intelligence Category – MarkTechPost
[[{“value”:” Video-Language Representation Learning is a crucial subfield of multi-modal representation learning that focuses on the relationship between videos and their associated textual descriptions. Its applications are explored in numerous areas, from question answering and text retrieval to summarization. In this regard ,contrastive learning has… Read More »HBI V2: A Flexible AI Framework that Elevates Video-Language Learning with a Multivariate Co-Operative Game Adeeba Alam Ansari Artificial Intelligence Category – MarkTechPost
[[{“value”:” Multimodal foundation models are becoming increasingly relevant in artificial intelligence, enabling systems to process and integrate multiple forms of data—such as images, text, and audio—to address diverse tasks. However, these systems face significant challenges. Existing models often struggle to generalize across a wide variety… Read More »EPFL Researchers Releases 4M: An Open-Source Training Framework to Advance Multimodal AI Asif Razzaq Artificial Intelligence Category – MarkTechPost
[[{“value”:” Ovarian lesions are frequently detected, often by chance, and managing them is crucial to avoid delayed diagnoses or unnecessary interventions. While transvaginal ultrasound is the primary diagnostic tool for distinguishing benign from malignant lesions, its accuracy heavily relies on the examiner’s expertise. A shortage… Read More »Transformer-Based AI Models for Ovarian Lesion Diagnosis: Enhancing Accuracy and Reducing Expert Referral Dependence Across International Centers Sana Hassan Artificial Intelligence Category – MarkTechPost
[[{“value”:” Generative AI applications are gaining widespread adoption across various industries, including regulated industries such as financial services and healthcare. As these advanced systems accelerate in playing a critical role in decision-making processes and customer interactions, customers should work towards ensuring the reliability, fairness, and… Read More »Align and monitor your Amazon Bedrock powered insurance assistance chatbot to responsible AI principles with AWS Audit Manager Bharathi Srinivasan AWS Machine Learning Blog
[[{“value”:” This post was co-written with Ben Doughton, Head of Product Operations – LCH, Iulia Midus, Site Reliability Engineer – LCH, and Maurizio Morabito, Software and AI specialist – LCH (part of London Stock Exchange Group, LSEG). In the financial industry, quick and reliable access… Read More »London Stock Exchange Group uses Amazon Q Business to enhance post-trade client services Ben Doughton AWS Machine Learning Blog