​[[{“value”:” Amazon SageMaker HyperPod is designed to support large-scale machine learning (ML) operations, providing a robust environment for training foundation models (FMs) over extended periods. Multiple users — such as ML researchers, software engineers, data scientists, and cluster administrators — can work concurrently on the… Read More »Implementing login node load balancing in SageMaker HyperPod for enhanced multi-user experience Janosch Woschitz AWS Machine Learning Blog

​[[{“value”:” This post was written with Darrel Cherry, Dan Siddall, and Rany ElHousieny of Clearwater Analytics. As global trading volumes rise rapidly each year, capital markets firms are facing the need to manage large and diverse datasets to stay ahead. These datasets aren’t just expansive… Read More »How Clearwater Analytics is revolutionizing investment management with generative AI and Amazon SageMaker JumpStart Darrel Cherry AWS Machine Learning Blog

​[[{“value”:” Twitch, the world’s leading live-streaming platform, has over 105 million average monthly visitors. As part of Amazon, Twitch advertising is handled by the ad sales organization at Amazon. New ad products across diverse markets involve a complex web of announcements, training, and documentation, making… Read More »How Twitch used agentic workflow with RAG on Amazon Bedrock to supercharge ad sales Bin Xu AWS Machine Learning Blog

​[[{“value”:” The rapid advancements in large language models (LLMs) have introduced significant opportunities for various industries. However, their deployment in real-world scenarios also presents challenges, such as generating harmful content, hallucinations, and potential ethical misuse. LLMs can produce socially biased, violent, or profane outputs, and… Read More »IBM Open-Sources Granite Guardian: A Suite of Safeguards for Risk Detection in LLMs Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Sampling from complex probability distributions is important in many fields, including statistical modeling, machine learning, and physics. This involves generating representative data points from a target distribution to solve problems such as Bayesian inference, molecular simulations, and optimization in high-dimensional spaces. Unlike generative modeling,… Read More »This AI Paper Sets a New Benchmark in Sampling with the Sequential Controlled Langevin Diffusion Algorithm Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” AI Video Generation has become increasingly popular in many industries due to its efficacy, cost-effectiveness, and ease of use. However, most state-of-the-art video generators rely on bidirectional models that consider both forward and backward temporal information to create each video part. This approach yields… Read More »Transforming Video Diffusion Models: The CausVid Approach Afeerah Naseem Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The advancement of AI model capabilities raises significant concerns about potential misuse and security risks. As artificial intelligence systems become more sophisticated and support diverse input modalities, the need for robust safeguards has become paramount. Researchers have identified critical threats, including the potential for… Read More »Best-of-N Jailbreaking: A Multi-Modal AI Approach to Identifying Vulnerabilities in Large Language Models Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​Podcasts are a fun and easy way to learn about machine learning. Podcasts are a fun and easy way to learn about machine learning.  Read More  

​[[{“value”:” Large language models (LLMs) trained on vast datasets of human language simulate logical and problem-solving abilities by following structured approaches. However, existing methods predominantly operate within a language space, where textual chains explicitly express reasoning processes. While effective for clarity, this reliance on language… Read More »Meta AI Introduces COCONUT: A New Paradigm Transforming Machine Reasoning with Continuous Latent Thoughts and Advanced Planning Capabilities Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Designing accurate all-atom protein structures is a critical challenge in bioengineering, as it involves generating both 3D structural data and 1D sequence information to define side-chain atom placements. Most approaches currently rely heavily on resolved experimentally determined structural datasets, which are scarce and biased,… Read More »PLAID: A New AI Approach for Co-Generating Sequence and All-Atom Protein Structures by Sampling from the Latent Space of ESMFold Aswin Ak Artificial Intelligence Category – MarkTechPost