Large Language Models

Scientific visualization has long been caught in a bind: the more complex the dataset, the more domain-specific the visualization, and the harder it is to automate. From MRI scans to hurricane simulations, modern scientific data is massive, high-dimensional, and notoriously messy. While dashboards and 2D plots have benefitted from LLM-driven automation, 3D volumetric visualization—especially in high-performance computing (HPC) settings—has remained stubbornly manual. VizGenie changes that. Developed at Los Alamos National Laboratory, VizGenie is a hybrid agentic system that doesn’t just automate visualization tasks—it refines itself through them. It blends traditional visualization tools (like VTK) with dynamically generated Python modules and augments this with vision-language models fine-tuned on domain-specific images. The result: a system that can answer questions like “highlight the tissue boundaries” and actually improve its answers over time. ...

In today’s threat landscape, cybersecurity is no longer a battle of scripts and firewalls. It’s a war of minds. And with the rise of intelligent agents powered by Large Language Models (LLMs), we are now entering a new era where cyber defense becomes not just technical but deeply strategic. The paper “Game Theory Meets LLM and Agentic AI” by Quanyan Zhu provides one of the most profound frameworks yet for understanding this shift. ...

When the DAO hack siphoned millions from Ethereum in 2016, the blockchain world learned a hard lesson: code is law, and bad law can be catastrophic. Fast forward to today, and smart contract security still walks a tightrope between complexity and automation. Enter Smart-LLaMA-DPO, a reinforced large language model designed not just to find vulnerabilities in smart contracts—but to explain them, clearly and reliably. 🧠 Beyond Detection: Why Explanations Matter Most smart contract vulnerability detectors work like smoke alarms—loud when something’s wrong, but not exactly helpful in telling you why. The core innovation of Smart-LLaMA-DPO is that it speaks the language of developers. It explains vulnerabilities with clarity and technical nuance, whether it’s a reentrancy flaw or an oracle manipulation scheme. And that clarity doesn’t come from magic—it comes from Direct Preference Optimization (DPO), a training method where the model learns not just from correct labels, but from expert-ranked explanations. ...

The Crossroads of Reason: When AI Hallucinates with Purpose On this day of reflection and sacrifice, we ask not what AI can do, but what it should become. Good Friday is not just a historical commemoration—it’s a paradox made holy: a moment when failure is reinterpreted as fulfillment, when death is the prelude to transformation. In today’s Cognaptus Insights, we draw inspiration from this theme to reimagine the way we evaluate, guide, and build large language models (LLMs). ...