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.
Newsletter: Sign up for our free daily newsletter)**More on this Episode: **Episode Page)**Join the discussion: **Thoughts on this? Join the convo.)Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup)Website: YourEverydayAI.com)Email The Show: [email protected])**Connect with Jordan on **LinkedIn)Topics Covered in This Episode:
- Choosing AI: Algorithms vs. Agents
- Understanding AI Models and Agents
- Using Conditional Statements in AI
- Importance of Data in AI Training
- Risk Factors in Agentic AI Projects
- Innovation through AI Experimentation
- 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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