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Java Brains에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Java Brains 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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Ep 11: Exploring AI for application developers (with Sinan Ozdemir)

1:29:14
 
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Manage episode 427311717 series 3323603
Java Brains에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Java Brains 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Link to GitHub for Sinan's book https://github.com/sinanuozdemir/quick-start-guide-to-llms

Sinan on LinkedIn: https://www.linkedin.com/in/sinan-ozdemir/

In this episode, I engage in a compelling conversation with Sinan Ozdemir, a seasoned expert in AI and LLMs who shares over a decade of experience. We navigate the fascinating progression of large language models (LLMs), discussing their deterministic and non-deterministic characteristics, the art of prompting, and the significance of model architecture and training data.

Our discussion also covers the latest strides in AI, including the creation of smaller and more efficient models capable of running on everyday devices. We delve into the intriguing world of AI benchmarks, the surprising performance of specialized models compared to industry giants like GPT-4, and the innovative approaches required for continued advancement.

Additionally, we highlight the ongoing tension between major corporations with extensive resources and smaller companies using open-source models to stay competitive. Join us to explore how the demand for personalized AI is influencing both research and corporate strategies.

SWE-bench: Can Language Models Resolve Real-World GitHub Issues? https://arxiv.org/abs/2310.06770

--- Support this podcast: https://podcasters.spotify.com/pod/show/javabrains/support

  continue reading

11 에피소드

Artwork
icon공유
 
Manage episode 427311717 series 3323603
Java Brains에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Java Brains 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Link to GitHub for Sinan's book https://github.com/sinanuozdemir/quick-start-guide-to-llms

Sinan on LinkedIn: https://www.linkedin.com/in/sinan-ozdemir/

In this episode, I engage in a compelling conversation with Sinan Ozdemir, a seasoned expert in AI and LLMs who shares over a decade of experience. We navigate the fascinating progression of large language models (LLMs), discussing their deterministic and non-deterministic characteristics, the art of prompting, and the significance of model architecture and training data.

Our discussion also covers the latest strides in AI, including the creation of smaller and more efficient models capable of running on everyday devices. We delve into the intriguing world of AI benchmarks, the surprising performance of specialized models compared to industry giants like GPT-4, and the innovative approaches required for continued advancement.

Additionally, we highlight the ongoing tension between major corporations with extensive resources and smaller companies using open-source models to stay competitive. Join us to explore how the demand for personalized AI is influencing both research and corporate strategies.

SWE-bench: Can Language Models Resolve Real-World GitHub Issues? https://arxiv.org/abs/2310.06770

--- Support this podcast: https://podcasters.spotify.com/pod/show/javabrains/support

  continue reading

11 에피소드

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