Welcome to AI Masters Voice, the podcast where we connect minds to dive into the future of AI. 

As AI Enthusiast, you might already know that are the main challenges with LLMs. For me it was a question, I couldn't answer right away.

What are the top problems/challenges we are facing with Large Language Models (LLMs)?

To answer this question, I invited AI visionary David Mataciunas demystifying the "Top 10 Challenges of LLMs."

In the ever-evolving world of Artificial Intelligence, staying ahead means understanding the complexities that shape our digital future. This week, we've launched new AI Masters Voice Podcast episode Part 1 of a captivating two-part series of this conversation.

Why David? With a rich background spanning from ML engineering to spearheading AI research initiatives in Lithuania, David brings unparalleled insights into the AI landscape and firsthand experiences. His journey from analyzing and creating vast datasets to pioneering solutions in AI makes him the perfect guide to navigate these complex waters.

In this episode, we delve into the intricate challenges of LLMs – from hallucinations and reasoning to multilingual capabilities, and everything in between. Deividas not only identifies these obstacles but also shares his profound experiences and practical solutions, providing invaluable insights for AI Masters and enthusiasts.

Whether you're an AI professional, student, or enthusiast, this episode is packed with insights that will broaden your understanding and spark curiosity for what's to come in Part 2 (next Friday).

Do not hesitate to leave a comment, like and share the episode with your AI community.

Key Highlights

• From Financial Analyst to AI Innovator
  David shares his transition from financial analysis to leading AI projects, illustrating the importance of continuous learning in AI.
  
• Understanding LLMs
  A deep dive into Large Language Models, their potential and limitations, with a special focus on hallucinations and reasoning challenges.
• AI's Impact on Language and Communication
  Discussion on multilingual capabilities in AI and David's involvement in projects enhancing Lithuanian language processing.
• The Road to AGI
  Exploration of Artificial General Intelligence and how solving reasoning in AI could lead to groundbreaking advancements across various domains.
• The Future of AI Development
  Insights into the evolution of AI, including the importance of quality data and the potential of AI to understand human-like reasoning.
  

This episode provides a comprehensive overview of the current state and future directions of AI through the lens of an expert actively shaping the field.

00:00 Episode highlights
01:23 Intro: AI Masters Voice
01:54 Top10 Challenges/Problems of Large Language Models
02:02 Welcoming Deividas Matačiūnas
03:00 David's introduction
04:05 Explaining AI in Simple Terms
04:40 Data Analyst
06:08 Data Scientist
08:02 Machine Learning (ML) engineer
09:59 LLMs
12:10 Difference between LLMs and GenAI
14:10 Model training
15:56 The Journey from Financial Analyst to AI Advocate
19:05 IBM and AI mentors
20:12 AI Association of Lithuania
22:22 LT AI Research Group and Lithuanian language in AI
25:22 Lithuanian Wisper model
27:06 Support for David's finetuning project
28:20 Main topic: TOP 10 LLMs challenges
28:45 Challenge no 1.: Hallucinations in LLMs
34:28 RAG - Retrieval-Augmented Generation
35:30 Price comparison for Training, Finetuning and RAG
36:51  Challenge no 2.: Reasoning
39:58 Reasoning example 1
42:47 Reasoning example 2
44:09 Practical solution: "Let's do this Step by Step"
46:36 FOMO of AI train. Focus on building a process.
48:31 Quality of the data
51:17 Finishing the PART 1
51:46 End titles