About This Talk
As marketing and advertising teams adopt AI at scale, the challenge is no longer generating content: it is ensuring that content is trusted, precise, and contextually accurate. General-purpose models often fall short in high-stakes industries, where nuance, compliance, and credibility matter most. This keynote will showcase how Articul8 is advancing domain-specific models (DSMs) trained on industry-grade data and expertise, paired with specialized agents such as LLM-IQ for model evaluation and ModelMesh™, an agent-of-agents reasoning engine that dynamically selects the right models and agents for each task.
We will share evidence of how DSMs consistently outperform general models in reasoning and efficiency. We will demonstrate how grounding AI in domain expertise enables scalable systems built on transparency and trust. Attendees will leave with a clear understanding of why hyper-personalization with DSMs defines the next frontier in AI for marketing and how leaders can harness this shift to stay ahead.
Presenters
Arun Karthi Subramaniyan
Founder & CEO, Articul8 AI
Dr. Arun Karthi Subramaniyan is the Founder & CEO of Articul8. Previously, he led the Cloud & AI Strategy team at Intel where he was responsible for establishing and driving the overall AI strategy globally and was focused on democratizing AI in a sustainable fashion. Arun joined Intel from Amazon Web Services (AWS), where he led the Extreme-scale computing team spanning Machine Learning, Quantum Computing, High Performance Computing (HPC), Autonomous Vehicles, and Autonomous Computing. His team was responsible for developing solutions across all areas of HPC, quantum computing and large-scale machine learning applications, spanning a $1B+ portfolio, and he grew the businesses 2-3x over two years. Arun’s primary areas of research focus are Bayesian methods, global optimization, probabilistic deep learning for large scale applications, and distributed computing.
He enjoys working at the intersection of massively parallel computing and modeling large-scale systems. Before AWS, Arun founded and led the AI products team at GE’s Oil & Gas division, and grew the digital products business successfully. He and his team developed deep learning-augmented hybrid analytics for all segments of the oil & gas industry. Arun led the development of the Digital Twin platform for GE at GE’s Global Research Center. The platform continues to enable several thousand engineers to build advanced models efficiently. The asset specific cumulative damage modeling techniques he and his team pioneered define the standard for industrial damage modeling. As a Six Sigma Master Black Belt, he developed advanced techniques and tools for efficiently modeling large scale systems like jet engine fleets, gas turbines in powerplants and accelerated design times by 3-4X. Arun is a prolific researcher with a Ph.D. in Aerospace Engineering from Purdue University with 34 granted patents (54 filed), 50+ international publications that have been cited more than 1600 times with a h-index of 16. He is also a recipient of the Hull Award from GE, which honors technologists for their outstanding technical impact.