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AI can mimic human language, but does that make it intelligent? We’re joined by Ozair Ali, Co-Founder of ekai, to unpack what it truly takes to turn cutting-edge AI into real-world solutions. Drawing on his global experience in startups, government and academia, Ozair brings unique insight into the limitations and possibilities of LLMs in the enterprise. He walks us through the practical UX challenges of working with LLMs, the statistical roots of modern AI and what makes an interface more than just a chat window.
Key Takeaways:
(02:56) AI terms often come from engineering, causing common confusion.
(05:57) Like the brain, LLMs show emergent behavior that’s hard to explain.
(09:00) LLMs mimic human speech but lack calibration.
(16:11) RAGs aren’t the first step — cheaper, simpler methods often get the same results.
(20:07) It’s mind-blowing that chat is still the default AI interface, as something better must exist.
(25:18) Non-technical users can build fast, blurring the line between data and software engineers.
(31:00) LLMs favor data-rich giants, but there’s hope for new disruptors to emerge.
(32:49) AI can unlock opportunities globally despite local infrastructure challenges.
Resources Mentioned:
Ozair Ali
https://www.linkedin.com/in/ozairali/
ekai | LinkedIn
https://www.linkedin.com/company/ekaiai/
ekai | Website
https://www.ekai.ai/
Conway’s Game of Life
https://playgameoflife.com/
Thanks for listening to the “Data Masters Podcast.” If you enjoyed this episode, be sure to subscribe so you never miss our latest discussions and insights into the ever-changing world of data.
#DataStrategy #DataManagement #DataMastersPodcast
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1111 ratings
AI can mimic human language, but does that make it intelligent? We’re joined by Ozair Ali, Co-Founder of ekai, to unpack what it truly takes to turn cutting-edge AI into real-world solutions. Drawing on his global experience in startups, government and academia, Ozair brings unique insight into the limitations and possibilities of LLMs in the enterprise. He walks us through the practical UX challenges of working with LLMs, the statistical roots of modern AI and what makes an interface more than just a chat window.
Key Takeaways:
(02:56) AI terms often come from engineering, causing common confusion.
(05:57) Like the brain, LLMs show emergent behavior that’s hard to explain.
(09:00) LLMs mimic human speech but lack calibration.
(16:11) RAGs aren’t the first step — cheaper, simpler methods often get the same results.
(20:07) It’s mind-blowing that chat is still the default AI interface, as something better must exist.
(25:18) Non-technical users can build fast, blurring the line between data and software engineers.
(31:00) LLMs favor data-rich giants, but there’s hope for new disruptors to emerge.
(32:49) AI can unlock opportunities globally despite local infrastructure challenges.
Resources Mentioned:
Ozair Ali
https://www.linkedin.com/in/ozairali/
ekai | LinkedIn
https://www.linkedin.com/company/ekaiai/
ekai | Website
https://www.ekai.ai/
Conway’s Game of Life
https://playgameoflife.com/
Thanks for listening to the “Data Masters Podcast.” If you enjoyed this episode, be sure to subscribe so you never miss our latest discussions and insights into the ever-changing world of data.
#DataStrategy #DataManagement #DataMastersPodcast