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Podcast
Open-Source vs Closed-Source LLMs
Part of the AI360 video and podcast series
Is it better to use ‘open-source’ or ‘closed-source’ when it comes to creating Generative AI models? Deloitte’s Baris Sarer weighs these options, and shares a 5-point test to identify that 'open-source' is the optimal choice.
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Learn when to utilize 'open-source' or 'closed-source' models to create Generative AI models
In this episode, Baris Sarer – a Principal in Deloitte’s Technology, Media & Telecommunications practice, explores the differences in ‘open-source’ and ‘closed-source’ for Generative AI models. He discusses how organizations can make informed decisions about when to use each model to shape an enterprise's strategy, and the features and trade-offs to consider.
Within the next 12 months, we will see successful examples of open-source monetization, the wild card would be the AI regulations and how it would impact the open-source space.
Baris Sarer, a technology strategist with over 20 years of experience in Telecom, Media & Entertainment, and Technology, excels in driving business transformation through data-driven strategies and strategic technology investments. Currently, as Deloitte's AI Strategic Growth Opportunity (SGO) lead, he spearheads AI innovation in the TMT industry and expands the Generative AI business through bold initiatives and strategic partnerships.
Watch the video interview here:
The AI360 podcast series is a succinct, insightful series, delivering cutting-edge perspectives from Deloitte leaders on AI topics in just 360 seconds.
Artificial intelligence continues to change the world around us at a dizzying pace.
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