Everyone wants the latest and greatest AI buzzword. But at what cost? 

And what the heck is the difference between algos, LLMs, and agents anyway? 

Tune in to find out.

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Topics Covered in This Episode:

1. Choosing AI: Algorithms vs. Agents
2. Understanding AI Models and Agents
3. Using Conditional Statements in AI
4. Importance of Data in AI Training
5. Risk Factors in Agentic AI Projects
6. Innovation through AI Experimentation
7. Evaluating AI for Business Solutions
   
   

Timestamps:
00:00 AWS AI Leader Departs Amid Talent War

03:43 Meta Wins Copyright Lawsuit

07:47 Choosing AI: Short or Long Term?

12:58 Agentic AI: Dynamic Decision Models

16:12 "Demanding Data-Driven Precision in Business"

20:08 "Agentic AI: Adoption and Risks"

22:05 Startup Challenges Amidst Tech Giants

24:36 Balancing Innovation and Routine

27:25 AGI: Future of Work and Survival

Keywords:
AI algorithms, Large Language Models, LLMs, Agents, Agentic AI, Multi agentic AI, Amazon Web Services, AWS, Vazhi Philemon, Gen AI efforts, Amazon Bedrock, talent wars in tech, OpenAI, Google, Meta, Copyright lawsuit, AI training, Sarah Silverman, Llama, Fair use in AI, Anthropic, AI deep research model, API, Webhooks, MCP, Code interpreter, Keymaker, Data labeling, Training datasets, Computer vision models, Block out time to experiment, Decision-making, If else conditional statements, Data-driven approach, AGI, Teleporting, Innovation in AI, Experiment with AI, Business leaders, Performance improvements, Sustainable business models, Corporate blade.

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