The way we learn about AI is constantly evolving. Online courses, research papers, and technical blogs make it easier than ever to access new knowledge. But there’s one thing they can’t replicate - the experience of talking to someone who’s been where you are, faced the same challenges, and figured out what works (and what doesn’t).

That’s the unique value of in-person meetups. They’re not just about attending talks; they’re about real conversations, shared experiences, and the kind of insights you can’t always find in documentation. You could be deep into MLOps or just navigating your first deployment, but meetups will always offer something different - something valuable.

The Kind of Knowledge You Only Get from Meetups

Direct Access to Experts 

If you’re stuck on a problem, you can search for solutions online or dig into documentation. But sometimes, the best way to solve an issue is to ask someone who’s already done it.

Meetups make that possible. Instead of sending cold messages or hoping someone answers your forum post, you can ask a question in real-time and get an immediate, practical response. And it’s not just about technical challenges - whether it’s career advice, best practices, or just hearing how others handle similar problems, direct conversations cut through a lot of the noise.

Unfiltered Insights From People Who’ve Been There

AI case studies and tutorials are great, but they often present a polished version of reality - what worked in the end, after all the hurdles were overcome. Meetups, on the other hand, are where people talk about the full picture: the unexpected roadblocks, the experiments that failed, and the workarounds that actually made things work.

At an in-person event, you might hear an engineer casually mention a small config change that cut model deployment times in half - something that might never make it into a blog post but could save you days of troubleshooting. These are the kinds of lessons that get shared over coffee or in a hallway chat, and they can be the most useful takeaways from a meetup.

Exposure to New Ideas and Different Approaches

It’s easy to get stuck in the same patterns when working with AI - using familiar tools, following the same workflows, and tackling problems from a known perspective. But meetups introduce you to how other teams and industries are solving similar challenges, often in ways you wouldn’t have considered.

Maybe someone’s found a better way to monitor model drift, or a new technique for handling real-time inference at scale. These kinds of insights don’t always come from structured talks - they emerge from discussions, questions, and spontaneous problem-solving with others who share your interests.

Career Growth (Even If You’re Not Looking Yet)

Networking doesn’t have to mean handing out business cards or job hunting. Some of the best career opportunities come from simply being in the right place, having the right conversation, and meeting people who might remember you later.

Meetups are full of professionals who are hiring, looking for collaborators, or just open to sharing experiences. Whether you're actively seeking your next role or just want to get a better sense of where the field is headed, these connections can be invaluable down the road.

Bringing These Benefits to NYC: MLOps Days

We know how valuable in-person events can be, so we’ve teamed up with JFrog to create an event that captures the best parts of AI meetups: real conversations, hands-on insights, and a space to connect with others working in MLOps, AI, and GenAI.

That’s what MLOps Days NYC is about - bringing together engineers, researchers, and industry leaders to share their real-world experiences, challenges, and solutions.

This is more than a set of great presentations; it’s an opportunity to talk with the people who are shaping the field right now. We’ve lined up a series of practical talks from experts who have built, scaled, and secured AI systems at top companies.

The Talks & What You’ll Learn

We've handpicked speakers who aren't just talking about AI – they're building it, scaling it, and pushing its boundaries every day:

🎯 AIOps Without the Chaos by Ciro Greco

Here's the thing about AI in 2024 – everyone's talking about massive models and infinite compute, but what about the rest of us? Ciro's talk cuts through the hype to focus on what he calls "ML for the 99%" – practical, efficient approaches that actually work in the real world.

You'll learn why the fundamentals of ML in production haven't changed as much as you might think, even in the LLM era. If you're tired of hearing about billion-parameter models and looking for practical ways to make AI work with reasonable resources, this talk is for you.

Ciro is the Founder & CEO @ Bauplan With a Ph.D. in Linguistics and a track record of turning complex AI concepts into practical solutions, Ciro is reshaping how we think about AI infrastructure. Before founding Bauplan, he led AI initiatives that transformed recommendation systems and search capabilities for major tech companies. His research has been featured at SIGIR, and he's known for making the "impossible" possible with limited resources.

🛡️ Protecting ML Systems in the GenAI Era by Yuval Fernbach

Let's face it – GenAI has opened a Pandora's box of security challenges. Your models are processing more data than ever, deployment cycles are getting faster, and your MLOps pipelines are becoming increasingly complex. Each of these is a potential vulnerability.

Yuval dives into the security risks you might not even know about – from data poisoning to adversarial attacks. But more importantly, he'll share concrete strategies to protect your ML systems. This isn't just theory; it's battle-tested advice from someone who's built ML platforms used by companies worldwide.

Yuval Fernbach is the VP, CTO MLOps @ JFrog. As the co-founder of Qwak (now part of JFrog), Yuval brings a wealth of experience from his time at AWS and various high-stakes government projects. His decade of work in securing ML pipelines makes him the perfect guide for navigating the treacherous waters of AI security. Fun fact: He once prevented a major data breach by spotting a pattern that traditional security tools missed completely.

⚡ integrating Tech to Unlock Generative AI by Liron Freind Saadon,

Ever feel overwhelmed by the maze of tools and platforms needed to get GenAI into production? You're not alone. Liron's talk is all about making sense of the MLOps ecosystem in the age of generative AI.

She'll walk you through what a modern MLOps platform should look like – from initial data prep to model deployment and monitoring. Expect practical insights on choosing and integrating the right tools to build a workflow that actually works. Whether you're scaling existing systems or building new ones, you'll learn how to avoid common pitfalls and make smart architectural decisions.

Liron is the, Head of Dev Rel @ NVIDIA Leading NVIDIA's European developer ecosystem, Liron combines deep technical expertise with a gift for making complex concepts accessible. Her background in DevOps and telecommunications gives her a unique perspective on scaling AI systems. She's helped countless teams move from proof-of-concept to production, and she knows exactly where the pitfalls lie.

🤝 Human-in-the-Loop Feedback & Agentic Systems by Ari Kaplan

AI systems are getting more autonomous, but human insight is more crucial than ever. Ari will show you how to strike that perfect balance between AI automation and human guidance. But here's the really exciting part – he'll demonstrate how to build a governed chatbot on your company's data in just 60 seconds. Yes, you read that right – not 6 months, but 60 seconds.

This session is perfect if you're wrestling with questions about AI governance, ethical AI deployment, or just want to see a mind-blowingly fast way to build enterprise-ready chatbots.

Ari Kaplan, Head of Evangelism @ Databricks Known as the "Moneyball Pioneer," Ari revolutionized MLB analytics before turning his attention to enterprise AI. His work has influenced everything from baseball strategies to Fortune 500 decision-making. At Databricks, he's leading the charge in making AI systems more human-centric and ethically sound.

Join Us in NYC

📅 Tuesday, March 4th, 4:00 PM - 7:00 PM EST📍 45 Rockefeller Plaza, 27th Floor, NYC💰 Free (Registration Required)

This is an opportunity to experience the benefits of in-person learning firsthand - real conversations, practical insights, and connections that could make a difference in your work.

Register now and be part of the conversation.

Originally posted at: https://mlops.community/in-nyc-heres-why-in-person-ai-meetups-matter-more-than-ever/