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Reframing GenAI as Not AI - Generative Search, Auto-Complete and Pattern Matching

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Manage episode 480612829 series 3610932
Content provided by Pragmatic AI Labs and Noah Gift. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Pragmatic AI Labs and Noah Gift or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Episode Notes: The Wizard of AI: Unmasking the Smoke and Mirrors

Summary

I expose the reality behind today's "AI" hype. What we call AI is actually generative search and pattern matching - useful but not intelligent. Like the Wizard of Oz, tech companies use smoke and mirrors to market what are essentially statistical models as sentient beings.

Key Points

  • Current AI technologies are statistical pattern matching systems, not true intelligence
  • The term "artificial intelligence" is misleading - these are advanced search tools without consciousness
  • We should reframe generative AI as "generative search" or "generative pattern matching"
  • AI systems hallucinate, recommend non-existent libraries, and create security vulnerabilities
  • Similar technology hype cycles (dot-com, blockchain, big data) all followed the same pattern
  • Successful implementation requires treating these as IT tools, not magical solutions
  • Companies using misleading AI terminology (like "cognitive" and "intelligence") create unrealistic expectations

Quote

"At the heart of intelligence is consciousness... These statistical pattern matching systems are not aware of the situation they're in."

Resources

  • Framework: Apply DevOps and Toyota Way principles when implementing AI tools
  • Historical Example: Amazon "walkout technology" that actually relied on thousands of workers in India

Next Steps

  • Remove "AI" terminology from your organization's solutions
  • Build on existing quality control frameworks (deterministic techniques, human-in-the-loop)
  • Outcompete competitors by understanding the real limitations of these tools

#AIReality #GenerativeSearch #PatternMatching #TechHype #AIImplementation #DevOps #CriticalThinking

🔥 Hot Course Offers:

🚀 Level Up Your Career:

Learn end-to-end ML engineering from industry veterans at PAIML.COM

  continue reading

215 episodes

Artwork
iconShare
 
Manage episode 480612829 series 3610932
Content provided by Pragmatic AI Labs and Noah Gift. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Pragmatic AI Labs and Noah Gift or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Episode Notes: The Wizard of AI: Unmasking the Smoke and Mirrors

Summary

I expose the reality behind today's "AI" hype. What we call AI is actually generative search and pattern matching - useful but not intelligent. Like the Wizard of Oz, tech companies use smoke and mirrors to market what are essentially statistical models as sentient beings.

Key Points

  • Current AI technologies are statistical pattern matching systems, not true intelligence
  • The term "artificial intelligence" is misleading - these are advanced search tools without consciousness
  • We should reframe generative AI as "generative search" or "generative pattern matching"
  • AI systems hallucinate, recommend non-existent libraries, and create security vulnerabilities
  • Similar technology hype cycles (dot-com, blockchain, big data) all followed the same pattern
  • Successful implementation requires treating these as IT tools, not magical solutions
  • Companies using misleading AI terminology (like "cognitive" and "intelligence") create unrealistic expectations

Quote

"At the heart of intelligence is consciousness... These statistical pattern matching systems are not aware of the situation they're in."

Resources

  • Framework: Apply DevOps and Toyota Way principles when implementing AI tools
  • Historical Example: Amazon "walkout technology" that actually relied on thousands of workers in India

Next Steps

  • Remove "AI" terminology from your organization's solutions
  • Build on existing quality control frameworks (deterministic techniques, human-in-the-loop)
  • Outcompete competitors by understanding the real limitations of these tools

#AIReality #GenerativeSearch #PatternMatching #TechHype #AIImplementation #DevOps #CriticalThinking

🔥 Hot Course Offers:

🚀 Level Up Your Career:

Learn end-to-end ML engineering from industry veterans at PAIML.COM

  continue reading

215 episodes

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