[RCAC Workshop] AI Ecosystem 2026: What’s New and What Matters
📅 Date: January 23, 2026 ⏰ Time: 1PM EST 💻 Location: Virtual 🏫 Instructor: Ashish
The AI landscape is evolving at an unprecedented pace, with rapid shifts in model architectures, tooling, deployment paradigms, and governance. This session provides a structured, practitioner-focused overview of the AI ecosystem as it stands in 2026, cutting through hype to focus on what is technically and strategically relevant. Rather than deep-diving into a single framework, the training maps the broader ecosystem—models, infrastructure, agent systems, multimodal AI, open vs. closed platforms, and emerging standards—to help participants make informed design and investment decisions.
Who Should Attend
AI/ML engineers, data scientists, research software engineers, platform engineers, technical leads, and advanced students who want a clear, up-to-date understanding of the modern AI stack. This session is ideal for practitioners responsible for architectural decisions, tooling selection, or long-term AI strategy, as well as researchers transitioning from experimental LLM usage to production-grade systems.
What You’ll Learn
Participants will gain a high-level but technically grounded understanding of the current AI ecosystem, including:
How the AI stack has evolved from single-model usage to full AI systems (models, agents, tools, orchestration, and infrastructure)
Key trends shaping 2026, including agentic workflows, multimodal models, open-source vs. commercial trade-offs, and on-prem vs. cloud deployment
The role of orchestration frameworks, vector databases, evaluation tooling, and governance layers
Practical guidance on which developments matter for real-world research, enterprise, and academic use cases—and which are largely noise
How to reason about future-proofing AI systems amid rapid ecosystem churn
Level
Intermediate. Familiarity with basic machine learning concepts and prior exposure to large language models (e.g., APIs, notebooks, or simple applications) is recommended, but deep expertise in any single framework is not required. 🔗 Register now: LINK