Machine learning (ML) models contain numerous adjustable settings called hyperparameters that control how they learn from data. Machine learning (ML) models contain numerous adjustable settings called hyperparameters that control how they learn from data. Read More
[[{“value”:” We recently announced the general availability of cross-account sharing of Amazon SageMaker Model Registry using AWS Resource Access Manager (AWS RAM), making it easier to securely share and discover machine learning (ML) models across your AWS accounts. Customers find it challenging to share and access… Read More »Centralize model governance with SageMaker Model Registry Resource Access Manager sharing Ram Vittal AWS Machine Learning Blog
[[{“value”:” Have you ever stumbled upon a breathtaking travel photo and instantly wondered where it was and how to get there? With 1.3 billion international arrivals in 2023, international travel is poised to exceed pre-pandemic levels and break tourism records in the coming years. Each… Read More »Revolutionize trip planning with Amazon Bedrock and Amazon Location Service Yao Cong Yeo AWS Machine Learning Blog
[[{“value”:” In the automotive industry, the ability to efficiently assess and address vehicle damage is crucial for efficient operations, customer satisfaction, and cost management. However, manual inspection and damage detection can be a time-consuming and error-prone process, especially when dealing with large volumes of vehicle… Read More »Simplify automotive damage processing with Amazon Bedrock and vector databases Vinicius Pedroni AWS Machine Learning Blog
[[{“value”:” In the rapidly evolving world of generative AI image modeling, prompt engineering has become a crucial skill for developers, designers, and content creators. By crafting effective prompts, you can harness the full potential of advanced diffusion transformer text-to-image models, enabling you to produce high-quality… Read More »Understanding prompt engineering: Unlock the creative potential of Stability AI models on AWS Isha Dua AWS Machine Learning Blog
[[{“value”:” We are excited to announce the availability of Stability AI’s latest and most advanced text-to-image model, Stable Diffusion 3.5 Large, in Amazon SageMaker JumpStart. This new cutting-edge image generation model, which was trained on Amazon SageMaker HyperPod, empowers AWS customers to generate high-quality images… Read More »Introducing Stable Diffusion 3.5 Large in Amazon SageMaker JumpStart Tom Yemington AWS Machine Learning Blog
[[{“value”:” By processing complex data formats, deep learning has transformed various domains, including finance, healthcare, and e-commerce. However, applying deep learning models to tabular data, characterized by rows and columns, poses unique challenges. While deep learning has excelled in image and text analysis, classic machine… Read More »This AI Paper Introduces TabM: An Efficient Ensemble-Based Deep Learning Model for Robust Tabular Data Processing Nikhil Artificial Intelligence Category – MarkTechPost
[[{“value”:” A central challenge in advancing deep learning-based classification and retrieval tasks is achieving robust representations without the need for extensive retraining or labeled data. Numerous applications depend on extensive, pre-trained models functioning as feature extractors; however, these pre-trained embeddings often fail to encapsulate the… Read More »No Train, All Gain: Enhancing Deep Frozen Representations with Self-Supervised Gradients Aswin Ak Artificial Intelligence Category – MarkTechPost
[[{“value”:” Large-scale neural language models (LMs) excel at performing tasks similar to their training data and basic variations of those tasks. However, it needs to be clarified whether LMs can solve new problems involving non-trivial reasoning, planning, or string manipulation that differ from their pre-training… Read More »Effectiveness of Test-Time Training to Improve Language Model Performance on Abstraction and Reasoning Tasks Sajjad Ansari Artificial Intelligence Category – MarkTechPost
[[{“value”:” Image captioning has seen remarkable progress, but significant challenges remain, especially in creating captions that are both descriptive and factually accurate. Traditional image caption datasets, such as those relying purely on synthetic captions generated by vision-language models (VLMs) or web-scraped alt-text, often fall short… Read More »BLIP3-KALE: An Open-Source Dataset of 218 Million Image-Text Pairs Transforming Image Captioning with Knowledge-Augmented Dense Descriptions Aswin Ak Artificial Intelligence Category – MarkTechPost