Rohan Rao

Large Language Models (LLMs) have overtaken the world over the last few years. In the future, LLMs will solve more and more use cases in every industry, domain, and business. It's time to level up or be left behind.

With rapid advancements in AI, we are at a phase where a new LLM is released almost every week. Amidst this plethora of options available, it's crucial to understand the similarities and differences between the various LLMs. How accurate are these LLMs for your business? How much computational resources are required to run these LLMs? How fast do these LLMs run? How expensive are these LLMs to deploy in production? Are open-source LLMs better than closed-source ones? Researching, understanding, and comparing these LLMs in a structured way can help you choose the right one for your business.

Gear up for an enlightening and comparative session at this year’s DataHack Summit! In this highly anticipated hack panel, we bring together leading AI practitioners to evaluate and compare various open-source & commercial Large Language Models (LLMs) across different tasks.

• Phi3 vs GPT 4o vs Llama 3
  
  This panel offers a unique opportunity to delve into the strengths, weaknesses, and performance of these models in real-world applications.