​[[{“value”:” Multimodal Attributed Graphs (MMAGs) have received little attention despite their versatility in image generation. MMAGs represent relationships between entities with combinatorial complexity in a graph-structured manner. Nodes in the graph contain both image and text information. Compared to text or image conditioning models, graphs… Read More »InstructG2I : A Graph Context Aware Stable Diffusion Model to Synthesize Images from Multimodal Attributed Graphs Adeeba Alam Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The problem that this research seeks to address lies in the inherent limitations of existing large language models (LLMs) when applied to formal theorem proving. Current models are often trained or fine-tuned on specific datasets, such as those focused on undergraduate-level mathematics, but struggle… Read More »LeanAgent: The First Life-Long Learning Agent for Formal Theorem Proving in Lean, Proving 162 Theorems Previously Unproved by Humans Across 23 Diverse Lean Mathematics Repositories Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Modern organizations increasingly depend on robust cloud infrastructure to provide business continuity and operational efficiency. Operational health events – including operational issues, software lifecycle notifications, and more – serve as critical inputs to cloud operations management. Inefficiencies in handling these events can lead to… Read More »Boost productivity by using AI in cloud operational health management Sean Xiaohai Wang AWS Machine Learning Blog

​[[{“value”:” Multimodal Situational Safety is a critical aspect that focuses on the model’s ability to interpret and respond safely to complex real-world scenarios involving visual and textual information. It ensures that Multimodal Large Language Models (MLLMs) can recognize and address potential risks inherent in their… Read More »Multimodal Situational Safety Benchmark (MSSBench): A Comprehensive Benchmark to Analyze How AI Models Evaluate Safety and Contextual Awareness Across Varied Real-World Situations Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” This post is cowritten with Ethan Handel and Zhiyuan He from Indeed.com. Indeed is the world’s #1 job site¹ and a leading global job matching and hiring marketplace. Our mission is to help people get jobs. At Indeed, we serve over 350 million global… Read More »How Indeed builds and deploys fine-tuned LLMs on Amazon SageMaker Ethan Handel AWS Machine Learning Blog

​[[{“value”:” Agentic workflows are a fresh new perspective in building dynamic and complex business use case-based workflows with the help of large language models (LLMs) as their reasoning engine. These agentic workflows decompose the natural language query-based tasks into multiple actionable steps with iterative feedback… Read More »Improve LLM application robustness with Amazon Bedrock Guardrails and Amazon Bedrock Agents Shayan Ray AWS Machine Learning Blog

​[[{“value”:” Customers across all industries are experimenting with generative AI to accelerate and improve business outcomes. Generative AI is used in various use cases, such as content creation, personalization, intelligent assistants, questions and answers, summarization, automation, cost-efficiencies, productivity improvement assistants, customization, innovation, and more. Generative… Read More »Dive deep into vector data stores using Amazon Bedrock Knowledge Bases Vishwa Gupta AWS Machine Learning Blog

​[[{“value”:” Generating accurate and aesthetically appealing visual texts in text-to-image generation models presents a significant challenge. While diffusion-based models have achieved success in creating diverse and high-quality images, they often struggle to produce legible and well-placed visual text. Common issues include misspellings, omitted words, and… Read More »Empowering Backbone Models for Visual Text Generation with Input Granularity Control and Glyph-Aware Training Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Information Retrieval (IR) systems for search and recommendations often utilize Learning-to-Rank (LTR) solutions to prioritize relevant items for user queries. These models heavily depend on user interaction features, such as clicks and engagement data, which are highly effective for ranking. However, this reliance presents… Read More »Apple Researchers Propose BayesCNS: A Unified Bayesian Approach Tackling Cold Start and Non-Stationarity in Large-Scale Search Systems Sajjad Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” While writing the code for any program or algorithm, developers can struggle to fill gaps in incomplete code and often make mistakes while trying to fit new pieces into existing code snippets or structures. These challenges arise from the difficulty of fitting the latest… Read More »Are LLMs Failing to Match with Suffix in Fill-in-the-Middle (FIM) Code Completion? Horizon-Length Prediction: A New AI Training Task to Advance FIM by Teaching LLMs to Plan Ahead over Arbitrarily Long Horizons Divyesh Vitthal Jawkhede Artificial Intelligence Category – MarkTechPost