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Generative AI at the Edge with Vinesh Sukumar - #623

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Indhold leveret af TWIML and Sam Charrington. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af TWIML and Sam Charrington eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

Today we’re joined by Vinesh Sukumar, a senior director and head of AI/ML product management at Qualcomm Technologies. In our conversation with Vinesh, we explore how mobile and automotive devices have different requirements for AI models and how their AI stack helps developers create complex models on both platforms. We also discuss the growing interest in text-based input and the shift towards transformers, generative content, and recommendation engines. Additionally, we explore the challenges and opportunities for ML Ops investments on the edge, including the use of synthetic data and evolving models based on user data. Finally, we delve into the latest advancements in large language models, including Prometheus-style models and GPT-4.

The complete show notes for this episode can be found at twimlai.com/go/623.

  continue reading

699 episoder

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Manage episode 359742919 series 2355587
Indhold leveret af TWIML and Sam Charrington. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af TWIML and Sam Charrington eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

Today we’re joined by Vinesh Sukumar, a senior director and head of AI/ML product management at Qualcomm Technologies. In our conversation with Vinesh, we explore how mobile and automotive devices have different requirements for AI models and how their AI stack helps developers create complex models on both platforms. We also discuss the growing interest in text-based input and the shift towards transformers, generative content, and recommendation engines. Additionally, we explore the challenges and opportunities for ML Ops investments on the edge, including the use of synthetic data and evolving models based on user data. Finally, we delve into the latest advancements in large language models, including Prometheus-style models and GPT-4.

The complete show notes for this episode can be found at twimlai.com/go/623.

  continue reading

699 episoder

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