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Navigating Build vs. Buy Decisions in Emerging AI Technologies - ML 180
Manage episode 458214147 series 2977446
Contenuto fornito da Charles M Wood. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Charles M Wood o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.
In today's episode, we dive into the critical decision-making process of building versus buying technology solutions, especially when it comes to agentic logic-based frameworks. With the industry still in its early stages, I recommend waiting for managed solutions to mature, while Ben suggests the educational value of simple project builds. They discuss the importance of understanding the technology thoroughly before diving into business-focused decisions, using tools like customer user journeys (CUJs) to evaluate scalability, cost-efficiency, and maintainability. They also highlight some initial challenges and missteps in project management and the necessity for pre-evaluation by tech teams.
For non-technical teams engaged in technical projects, they provide structured guidance on navigating these unknowns efficiently. Additionally, they emphasize the value of research spikes and incremental development to manage risk and learn from user behavior. Finally, they explore the promising yet evolving landscape of generative AI and its potential high ROI with Retrieval-Augmented Generation (RAG).
Socials
Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
…
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For non-technical teams engaged in technical projects, they provide structured guidance on navigating these unknowns efficiently. Additionally, they emphasize the value of research spikes and incremental development to manage risk and learn from user behavior. Finally, they explore the promising yet evolving landscape of generative AI and its potential high ROI with Retrieval-Augmented Generation (RAG).
Socials
Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
209 episodi
Manage episode 458214147 series 2977446
Contenuto fornito da Charles M Wood. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Charles M Wood o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.
In today's episode, we dive into the critical decision-making process of building versus buying technology solutions, especially when it comes to agentic logic-based frameworks. With the industry still in its early stages, I recommend waiting for managed solutions to mature, while Ben suggests the educational value of simple project builds. They discuss the importance of understanding the technology thoroughly before diving into business-focused decisions, using tools like customer user journeys (CUJs) to evaluate scalability, cost-efficiency, and maintainability. They also highlight some initial challenges and missteps in project management and the necessity for pre-evaluation by tech teams.
For non-technical teams engaged in technical projects, they provide structured guidance on navigating these unknowns efficiently. Additionally, they emphasize the value of research spikes and incremental development to manage risk and learn from user behavior. Finally, they explore the promising yet evolving landscape of generative AI and its potential high ROI with Retrieval-Augmented Generation (RAG).
Socials
Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
…
continue reading
For non-technical teams engaged in technical projects, they provide structured guidance on navigating these unknowns efficiently. Additionally, they emphasize the value of research spikes and incremental development to manage risk and learn from user behavior. Finally, they explore the promising yet evolving landscape of generative AI and its potential high ROI with Retrieval-Augmented Generation (RAG).
Socials
Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
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