Towards AGI: Technologies, Challenges, and the Path Ahead

AI is evolving at lightning speed—but how close are we to reaching Artificial General Intelligence (AGI)? In this session, we’ll chart the path from early generative models to today’s cutting-edge systems and explore the breakthroughs, roadblocks, and ethical debates shaping AI’s future. From reasoning and multimodality to autonomy and alignment, we’ll dive into what’s working, what’s missing, and what’s next. Whether you're building AI applications or curious about where it’s all headed, this talk will connect today’s tools with tomorrow’s potential in the journey toward AGI.

Key Takeaways:

• How we got here: Understand the evolution of Generative AI — from early language models to the breakthroughs and beyond.
• Where we are now: Explore real-world applications, cutting-edge innovations, and how GenAI is reshaping industries today.
• What’s next: Discover what’s needed to move from today’s models toward AGI— reasoning, autonomy, multimodal learning, and open-source momentum.
• Why it matters: Learn the societal, ethical, and technical challenges that will define whether AGI is built responsibly — or recklessly.

Mayur Madnani is an engineer who transforms complex problems into impactful solutions across software, data, and AI. With a strong foundation in backend systems, scalable architectures, and machine learning, he brings deep technical insight and a forward-thinking mindset to every challenge. He holds a Master’s degree in Artificial Intelligence & Machine Learning from Liverpool John Moores University (UK), and is both a published researcher and a patent holder. Mayur is also passionate about mentorship and education, actively helping others navigate the evolving tech landscape. You can reach him on LinkedIn.