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​[[{“value”:” AI institutions develop heterogeneous models for specific tasks but face data scarcity challenges during training. Traditional Federated Learning (FL) supports only homogeneous model collaboration, which needs identical architectures across all clients. However, clients develop model architectures for their unique requirements. Moreover, sharing effort-intensive locally… Read More »HtFLlib: A Unified Benchmarking Library for Evaluating Heterogeneous Federated Learning Methods Across Modalities Sajjad Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” May 8 AI Codecon was a huge success. We had amazing speakers and content. We also had over 9,000 live attendees and another 12,000 who signed up to be able to view the content later on the O’Reilly learning platform. (Here’s a post with… Read More »Coding for the Future Agentic World Tim O’Reilly AI & ML – Radar

​[[{“value”:” The Shift in Agentic AI System Needs LLMs are widely admired for their human-like capabilities and conversational skills. However, with the rapid growth of agentic AI systems, LLMs are increasingly being utilized for repetitive, specialized tasks. This shift is gaining momentum—over half of major… Read More »Why Small Language Models (SLMs) Are Poised to Redefine Agentic AI: Efficiency, Cost, and Practical Deployment Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Meetings play a crucial role in decision-making, project coordination, and collaboration, and remote meetings are common across many organizations. However, capturing and structuring key takeaways from these conversations is often inefficient and inconsistent. Manually summarizing meetings or extracting action items requires significant effort and… Read More »Meeting summarization and action item extraction with Amazon Nova Baishali Chaudhury Artificial Intelligence and Machine Learning

​[[{“value”:” Developing robust text-to-SQL capabilities is a critical challenge in the field of natural language processing (NLP) and database management. The complexity of NLP and database management increases in this field, particularly while dealing with complex queries and database structures. In this post, we introduce… Read More »Building a custom text-to-SQL agent using Amazon Bedrock and Converse API Pavan Kumar Vadupu Lakshman Manikya Artificial Intelligence and Machine Learning

​[[{“value”:” In this post, we explore how generative AI can revolutionize threat modeling practices by automating vulnerability identification, generating comprehensive attack scenarios, and providing contextual mitigation strategies. Unlike previous automation attempts that struggled with the creative and contextual aspects of threat analysis, generative AI overcomes… Read More »Accelerate threat modeling with generative AI Edvin Hallvaxhiu Artificial Intelligence and Machine Learning

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​[[{“value”:” It feels like every other AI announcement lately mentions “agents.” And already, the AI community has 2025 pegged as “the year of AI agents,” sometimes without much more detail than “They’ll be amazing!” Often forgotten in this hype are the fundamentals. Everybody is dreaming… Read More »Designing Collaborative Multi-Agent Systems with the A2A Protocol Heiko Hotz and Sokratis Kartakis AI & ML – Radar

​[[{“value”:” Autoencoders and the Latent Space Neural networks are designed to learn compressed representations of high-dimensional data, and autoencoders (AEs) are a widely-used example of such models. These systems employ an encoder-decoder structure to project data into a low-dimensional latent space and then reconstruct it… Read More »How Latent Vector Fields Reveal the Inner Workings of Neural Autoencoders Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Introduction: The Need for Efficient RL in LRMs Reinforcement Learning RL is increasingly used to enhance LLMs, especially for reasoning tasks. These models, known as Large Reasoning Models (LRMs), generate intermediate “thinking” steps before providing final answers, thereby improving performance on complex problems such… Read More »AREAL: Accelerating Large Reasoning Model Training with Fully Asynchronous Reinforcement Learning Sana Hassan Artificial Intelligence Category – MarkTechPost