​[[{“value”:” Generative AI models have become highly prominent in recent years for their ability to generate new content based on existing data, such as text, images, audio, or video. A specific sub-type, diffusion models, produces high-quality outputs by transforming noisy data into a structured format.… Read More »Discrete Diffusion with Planned Denoising (DDPD): A Novel Machine Learning Framework that Decomposes the Discrete Generation Process into Planning and Denoising Afeerah Naseem Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Despite recent advances in multimodal large language models (MLLMs), the development of these models has largely centered around English and Western-centric datasets. This emphasis has resulted in a significant gap in linguistic and cultural representation, with many languages and cultural contexts around the world… Read More »CMU Researchers Release Pangea-7B: A Fully Open Multimodal Large Language Models MLLMs for 39 Languages Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In recent years, large language models (LLMs) have demonstrated significant progress in various applications, from text generation to question answering. However, one critical area of improvement is ensuring these models accurately follow specific instructions during tasks, such as adjusting format, tone, or content length.… Read More »Microsoft AI Introduces Activation Steering: A Novel AI Approach to Improving Instruction-Following in Large Language Models Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” To stay competitive, businesses across industries use foundation models (FMs) to transform their applications. Although FMs offer impressive out-of-the-box capabilities, achieving a true competitive edge often requires deep model customization through pre-training or fine-tuning. However, these approaches demand advanced AI expertise, high performance compute,… Read More »Generative AI foundation model training on Amazon SageMaker Trevor Harvey AWS Machine Learning Blog

​[[{“value”:” You can now create an end-to-end workflow to train, fine tune, evaluate, register, and deploy generative AI models with the visual designer for Amazon SageMaker Pipelines. SageMaker Pipelines is a serverless workflow orchestration service purpose-built for foundation model operations (FMOps). It accelerates your generative… Read More »Automate fine-tuning of Llama 3.x models with the new visual designer for Amazon SageMaker Pipelines Lauren Mullennex AWS Machine Learning Blog

​[[{“value”:” Amazon SageMaker is a cloud-based machine learning (ML) platform within the AWS ecosystem that offers developers a seamless and convenient way to build, train, and deploy ML models. Extensively used by data scientists and ML engineers across various industries, this robust tool provides high… Read More »Implement Amazon SageMaker domain cross-Region disaster recovery using custom Amazon EFS instances Jinzhao Feng AWS Machine Learning Blog

​[[{“value”:” The generative AI market has expanded exponentially, yet many existing models still face limitations in adaptability, quality, and computational demands. Users often struggle to achieve high-quality output with limited resources, especially on consumer-grade hardware. Addressing these challenges requires solutions that are both powerful and… Read More »Stability AI Releases Stable Diffusion 3.5: Stable Diffusion 3.5 Large and Stable Diffusion 3.5 Large Turbo Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Retrieval-Augmented Generation (RAG) is a growing area of research focused on improving the capabilities of large language models (LLMs) by incorporating external knowledge sources. This approach involves two primary components: a retrieval module that finds relevant external information and a generation module that uses… Read More »FunnelRAG: A Novel AI Approach to Improving Retrieval Efficiency for Retrieval-Augmented Generation Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Alignment with human preferences has led to significant progress in producing honest, safe, and useful responses from Large Language Models (LLMs). Through this alignment process, the models are better equipped to comprehend and represent what humans think is suitable or important in their interactions.… Read More »Meet SynPO: A Self-Boosting Paradigm that Uses Synthetic Preference Data for Model Alignment Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​[[{“value”:” I’m worried about AI. I’m not worried about it taking my job. I believe AI is a genuine productivity tool. By which I mean it can make developers produce more. The question is whether those developers are producing something good or not. The difference… Read More »Rift Between Junior and Senior Developers Trisha Gee AI & ML – Radar