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DTSTAMP:20260413T112605
DTSTART;TZID=Europe/Berlin:20260417T130000
DTEND;TZID=Europe/Berlin:20260417T140000
SUMMARY:How AI Succeeds — Insights from Manufacturing Applications with Nik
 ita Golovko
DESCRIPTION:Most AI discussions confuse Large Language Models (LLMs) with A
 I as a whole. In this episode Eberhard sits down with Nikita Golovko — indu
 strial AI architect and practitioner at Siemens — to challenge that view an
 d explores what happens when probabilistic systems meet deterministic envir
 onments like industrial automation.\n\nWe clarify the differences between L
 LMs\, Generative AI\, and other AI methods — and where each actually create
 s value. From there\, the focus shifts to architecture: how to safely integ
 rate probabilistic AI into systems that require reliability\, precision\, a
 nd control.\n\nFinally\, we generalize these lessons beyond industry\, show
 ing how choosing the right tool for the right problem leads to better outco
 mes in any domain.
LOCATION:https://www.youtube.com/watch?v=1FmdktJVHhE https://www.linkedin.c
 om/events/7449385628313690112/ Most AI discussions confuse Large Language M
 odels (LLMs) with AI as a whole. In this episode Eberhard sits down with Ni
 kita Golovko — industrial AI architect and practitioner at Siemens — to cha
 llenge that view and explores what happens when probabilistic systems meet 
 deterministic environments like industrial automation.  We clarify the diff
 erences between LLMs\, Generative AI\, and other AI methods — and where eac
 h actually creates value. From there\, the focus shifts to architecture: ho
 w to safely integrate probabilistic AI into systems that require reliabilit
 y\, precision\, and control.  Finally\, we generalize these lessons beyond 
 industry\, showing how choosing the right tool for the right problem leads 
 to better outcomes in any domain.
STATUS:CONFIRMED
TRANSP:OPAQUE
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