GMI Cloud at NVIDIA GTC: Pushing AI to the Next Level

The AI race isn’t slowing down—miss a beat, and you’re playing catch-up. That’s why NVIDIA GTC (March 17-21) is the place to be for anyone serious about shaping the future of AI and machine learning.

At GMI Cloud, we’re not just spectators in this revolution—we’re building it. GTC is our opportunity to go beyond the hype, dive into cutting-edge breakthroughs, and connect with the innovators who are redefining what AI can do. And we’re bringing our own expertise to the table—because winning in AI isn’t just about keeping up; it’s about leading the way.

GMI Cloud Takes the Stage: Two Talks You Can’t Miss

We’re not just attending GTC—we’re driving the conversation on how AI companies can go from prototype to powerhouse and outpace the competition. AI moves fast, and the difference between success and irrelevance is execution. That’s why GMI Cloud is hosting two must-attend talks tailored for AI builders, product leaders, and decision-makers looking to turn ambitious ideas into market dominance.

🔥 Pawn to Queen: How to Elevate AI Projects to Winning the Market

Most AI projects start as promising experiments, but only a few evolve into industry-defining solutions. Why? Because execution, strategy, and infrastructure make all the difference. This session unpacks the playbook for turning small AI initiatives into scalable, high-impact products—from navigating compute constraints and optimizing model performance to aligning AI capabilities with real business value. 

Whether you're a startup aiming to disrupt or an enterprise looking to refine your AI strategy, this session will provide practical frameworks to accelerate your path to market leadership.

⚡ The Importance of Developing Faster Now: Why Speed is Everything in AI

In AI, speed isn’t just an advantage—it’s survival. If you’re not iterating fast, you’re already behind. Compute bottlenecks, slow retraining, and inefficient deployment kill momentum, while AI leaders build for agility without sacrificing reliability.

Join us as we break down the five key technical foundations that separate winners from the rest—from scalable infrastructure and automated data pipelines to optimized deployment and MLOps. If you’re building AI and want to move faster, this is the talk you can’t afford to miss.

Keynotes & Trends: Where AI is Headed Next

We’ll be all ears for Jensen Huang’s keynote and the latest insights from industry leaders. Expect major discussions on AI hardware, LLM advancements, and the next wave of generative AI—the kind of updates that redefine what's possible.

What are we interested in? Check out the following short-list below:

• Accelerate Inference on NVIDIA GPUs [S72330] — Deploying large language models for inference at scale is inherently complex, often requiring intricate optimizations across compute-bound and memory-bound regimes. We examine automatic vertical fusion, epilogue optimization, and adaptive kernel generation across batch sizes for GEMV and GEMM workloads, addressing key efficiency concerns, from NVIDIA CUDA® graph captures and optimized all-reduce strategies to custom kernel registrations. We'll highlight Together AI's journey in optimizing inference performance across the stack.
• Unlocking High-Performance AI Applications at Airbnb [S73265] — Discover how NVIDIA Triton and TensorRT-LLM transformed AI at Airbnb, enabling high-performance ML serving and unlocking new product use cases previously unattainable. We'll discuss infrastructural challenges faced when integrating rapidly evolving, sophisticated technologies into a complex ML stack, and how NVIDIA solutions were pivotal in enhancing our inference capabilities, thereby pioneering a new generation of AI at Airbnb. Then we'll discuss our rigorous technical evaluations and explorations of NVIDIA technologies, from hardware accelerations to engine optimizations, and highlight transformative Airbnb AI products enabled by these capabilities. Join us as we share our journey of surmounting challenges and reaching new frontiers, showcasing NVIDIA's role in powering real-world AI use cases.
• Scalable AI Infrastructure in the Gaming Industry [S73667] — Discover how Electronic Arts is advancing its AI/ML infrastructure to scale teams who can run AI, scale applications of AI, and scale the impact of AI across player experiences. We'll highlight EA’s streamlined GPU provisioning across multi-cloud and on-premises environments, centralized model management for compliance and accessibility, and rapid deployment capabilities, enabling seamless workflows that accelerate development and bring AI innovations into production with robust service level agreements.
• AI in Action: Optimize Your AI Infrastructure [S74315] — Explore strategies for building and managing an efficient AI infrastructure that streamlines both training and inference. In this panel discussion, industry leaders will discuss how they leverage NVIDIA and Google Cloud's AI solutions to optimize resource utilization, reduce costs, and improve the overall performance of their AI applications.

Deep Dives & Workshops: AI at Full Throttle

GTC is packed with must-attend technical sessions, and we’ll be diving headfirst into:

🔥 Scaling Generative AI & LLMs – From fine-tuning to deployment, how can we push LLMs to be faster, cheaper, and more effective?

🤖 Reinforcement Learning & Autonomous AI – Training AI that adapts and makes decisions in real time—critical for robotics, trading, and self-learning systems.

⚙️ AI Infrastructure Optimization – The battle for compute is real. Learn how to optimize GPUs, storage, and MLOps to handle massive AI workloads at scale.

🌍 Edge AI & Real-Time Decision Making – AI isn’t just cloud-based—edge computing is bringing intelligence directly to devices.

✅ Ethical AI & Trustworthy Models – AI can’t just be powerful; it has to be responsible. We’ll join the conversation on bias mitigation, transparency, and AI governance.

Here are some workshops we're eager to attend:

• Efficient Large Language Model (LLM) Customization — Learn how to improve LLM application capabilities and reduce the size of required LLMs using parameter efficient fine-tuning (PEFT).
• Building LLM Applications With Prompt Engineering — Learn how to build a variety of LLM-based applications through the use of modern prompt engineering techniques.
• Building AI Agents with Multimodal Models — In this course, attendees will learn about neural network agents that can reason using many different data types by exploring different fusion techniques.
• Deploying RAG Pipelines for Production at Scale — Participants will gain hands-on experience deploying, monitoring, and scaling RAG pipelines with the NVIDIA NIM Operator and learn best practices for infrastructure optimization, performance monitoring, and handling high traffic volumes.

Each of these is fundamental to building tangible real-world applications. 

Let’s Talk—And Build

The real power of GTC? The people. We’re excited to connect with researchers, engineers, and AI leaders who are pushing the boundaries of what’s possible. Whether you’re looking for insights, partnerships, or solutions to scale your AI, let’s make it happen.

📍 Visit us at Booth #239 – We’ll be showcasing our latest AI solutions, running live demos, and answering your toughest AI challenges.

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