BrowserStack QA Meetup- Columbus (March 12)

Hello Columbus!
The community is buzzing and growing well.
We are thrilled to bring our third BrowserStack QA Meetup on March 12th!

We are creating a space for deeper insights, meaningful connections, and a vibe you won't want to miss.

What to expect:

• Connect: Network with Columbus' top engineering and QA minds.
• Learn: Real-world tactics and trends you can use immediately.
• Enjoy: Food, drinks, and great community spirit.

Agenda

• Sam Gomez is presenting "AI is more than LLMs: Choosing the right AI for your needs."

RSVP Essential: Space is limited, and we want to ensure a great experience for everyone. RSVP now to secure your spot!

📍 Venue: Leading EDJE, 6515 Longshore Loop, Suite 300, Dublin, OH 43017
📍 Free Parking: 6725 Longshore Street, Dublin, OH 43017
📅 Date & Time: March 12, 6:00 PM

Stay Connected!
Want to continue the conversation beyond the meetup?
Join our BrowserStack Discord Server to get updates, connect with fellow QA professionals, and be part of an ongoing discussion. Don’t miss out—click below to join!
🔗 [Join the BrowserStack Discord Server]

A Few Notes:
✅ This is an in-person event
✅ RSVP does not guarantee a seat – A confirmation email will be sent one day before the event.

TALK ABSTRACT:
AI is all the hype these days; however, despite (or maybe because of) the excitement around it, a high percentage of AI projects fail. Projects that are over budget, delayed, or that fail to scale past the POC phase are very common. In many of these scenarios, choosing the right approach can be as critical as the solution itself. Should you build a tailored machine learning model, leverage the power of large language models (LLMs), or integrate with AI copilots? Each option has unique strengths, trade-offs, and resource requirements, and the key to success lies in aligning your choice with your business goals and technical constraints.

In this talk, we will go beyond the basic concepts and definitions to provide a practical guide that allows attendees to navigate these decisions through real-world case studies. We will examine scenarios in which different AI paradigms were chosen, discuss the factors that influenced those decisions, and outline the process for evaluating needs, constraints, and outcomes. From assessing data availability and team expertise to balancing cost and scalability, you'll gain insights into the critical considerations that guide the selection process.

By the end of this session, you’ll have a clear process for determining whether machine learning, LLMs, or copilots are best suited to your AI challenges and understand the resources and strategies needed to bring your chosen solution to life. This talk is ideal for decision-makers, technical leads, and innovators seeking to demystify AI implementation and maximize the impact of their investments.