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Contenido proporcionado por Forbes Books and Gregory Shepard. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Forbes Books and Gregory Shepard o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
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The Philosophy of AI: Examining the Ethical Implications with David Danks (Part Two)

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Manage episode 423087429 series 2902835
Contenido proporcionado por Forbes Books and Gregory Shepard. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Forbes Books and Gregory Shepard o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
In the second half of the episode, the conversation dives deeper into the practical applications of AI that entrepreneurs can leverage. David explains time series models for forecasting how situations evolve over time and how founders can use causal discovery techniques to identify the true drivers of outcomes rather than just correlations. They discuss the potential for AI to aid investors in evaluating startup trajectories and finding whitespace opportunities. David stresses the importance of having high-quality data to feed AI models. He advises entrepreneurs to look for repetitive tasks where desired outcomes are clear as areas ripe for applying AI capabilities. The talk also covers AI's limitations around subjective aspects requiring human context and judgment. David recommends having AI handle the routine, mundane elements while reserving higher-level decision-making for humans to get the best combination. Overall, David provides insightful guidance on practical ways founders can utilize AI technologies like time series modeling, causal analysis, and task augmentation while being intentional about which aspects to keep under human control. His advice can help entrepreneurs navigate the hype to determine the right AI applications for their businesses.
  continue reading

82 episodios

Artwork
iconCompartir
 
Manage episode 423087429 series 2902835
Contenido proporcionado por Forbes Books and Gregory Shepard. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Forbes Books and Gregory Shepard o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.
In the second half of the episode, the conversation dives deeper into the practical applications of AI that entrepreneurs can leverage. David explains time series models for forecasting how situations evolve over time and how founders can use causal discovery techniques to identify the true drivers of outcomes rather than just correlations. They discuss the potential for AI to aid investors in evaluating startup trajectories and finding whitespace opportunities. David stresses the importance of having high-quality data to feed AI models. He advises entrepreneurs to look for repetitive tasks where desired outcomes are clear as areas ripe for applying AI capabilities. The talk also covers AI's limitations around subjective aspects requiring human context and judgment. David recommends having AI handle the routine, mundane elements while reserving higher-level decision-making for humans to get the best combination. Overall, David provides insightful guidance on practical ways founders can utilize AI technologies like time series modeling, causal analysis, and task augmentation while being intentional about which aspects to keep under human control. His advice can help entrepreneurs navigate the hype to determine the right AI applications for their businesses.
  continue reading

82 episodios

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