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Will synthetic data shape the future of AI training? | Ep. 229

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Content provided by Foundry. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Foundry or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

As the demand for high-quality training data continues to surge, synthetic data is emerging as a game-changing tool in the world of AI development. But is it the silver bullet enterprises need—or a potential minefield of risks? In this episode of Today in Tech, host Keith Shaw sits down with Alexius Wronka, CTO of Data and Growth at Invisible Technologies, to explore the advantages, limitations, and ethical challenges of using synthetic data to train large language models (LLMs) and enterprise AI systems. :mag: Topics Covered: What exactly is synthetic data? Key benefits vs. human-generated data Use cases in healthcare, autonomous vehicles, and enterprise AI Dangers of model overfitting and data hallucination Synthetic content, explainability, and detection tools The Matrix analogy: Are we training AI inside simulations? :point_right: Don't forget to like, comment, and subscribe for more episodes of Today in Tech! #SyntheticData #AITraining #InvisibleTechnologies #AlexiusWronka #TodayInTech #KeithShaw #EnterpriseAI #GenerativeAI #TechPodcast

  continue reading

497 episodes

Artwork
iconShare
 
Manage episode 483933372 series 3335763
Content provided by Foundry. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Foundry or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

As the demand for high-quality training data continues to surge, synthetic data is emerging as a game-changing tool in the world of AI development. But is it the silver bullet enterprises need—or a potential minefield of risks? In this episode of Today in Tech, host Keith Shaw sits down with Alexius Wronka, CTO of Data and Growth at Invisible Technologies, to explore the advantages, limitations, and ethical challenges of using synthetic data to train large language models (LLMs) and enterprise AI systems. :mag: Topics Covered: What exactly is synthetic data? Key benefits vs. human-generated data Use cases in healthcare, autonomous vehicles, and enterprise AI Dangers of model overfitting and data hallucination Synthetic content, explainability, and detection tools The Matrix analogy: Are we training AI inside simulations? :point_right: Don't forget to like, comment, and subscribe for more episodes of Today in Tech! #SyntheticData #AITraining #InvisibleTechnologies #AlexiusWronka #TodayInTech #KeithShaw #EnterpriseAI #GenerativeAI #TechPodcast

  continue reading

497 episodes

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