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Scott Hanselman: Semantic Kernel - Episode 280
Manage episode 395499254 series 3541978
Scott Hanselman is a teacher at heart. He speaks all over to whoever will listen. He's written code that you, dear listener, has used. Scott has been blogging, coding, and podcasting a LONG time. He codes, writes, speaks, empowers, promotes, braids, learns and listens - usually not in that order. And he's a Vice President at Microsoft in his day job. You can find him on YouTube, TikTok, Instagram, and Mastodon! His Hanselminutes podcast has surpassed 900 episodes, and his Azure Friday show, over 750 episodes.
Topics of Discussion:
[4:33] What should developers be focusing on?
[625] Understanding the complexity of AI development.
[8:09] Without understanding context, we can’t make good prompts.
[8:42] What are the levels of the pyramid that every developer should understand?
[9:16] Developers should start by learning the basics of AI.
[9:22] The question of who is responsible when a website or model goes down.
[14:15] Grounding your AI in reality.
[15:19] Edge deployed AI model.
[17:00] A foundational model is a machine learning model that has been pre-trained on a data set.
[20:40] The limitations of large language models.
[21:00] AI transformer models and their growth in size and complexity.
[21:46] Conversation with John Maeda at the .NET Conf on Semantic Kernel.
[22:02] Integrating these large language models into conventional programming languages.
[23:08] A few exciting and actionable features of semantic kernel.
[28:18] Concerns about data privacy in smart homes.
[29:07] Advice for developers looking to jump into semantic kernel.
Mentioned in this Episode:
Programming with Palermo — New Video Podcast! Email us at programming@palermo.net.
Clear Measure, Inc. (Sponsor)
.NET DevOps for Azure: A Developer’s Guide to DevOps Architecture the Right Way, by Jeffrey Palermo — Available on Amazon!
Jeffrey Palermo’s Twitter — Follow to stay informed about future events!
Want to Learn More?
Visit AzureDevOps.Show for show notes and additional episodes.
100集单集
Manage episode 395499254 series 3541978
Scott Hanselman is a teacher at heart. He speaks all over to whoever will listen. He's written code that you, dear listener, has used. Scott has been blogging, coding, and podcasting a LONG time. He codes, writes, speaks, empowers, promotes, braids, learns and listens - usually not in that order. And he's a Vice President at Microsoft in his day job. You can find him on YouTube, TikTok, Instagram, and Mastodon! His Hanselminutes podcast has surpassed 900 episodes, and his Azure Friday show, over 750 episodes.
Topics of Discussion:
[4:33] What should developers be focusing on?
[625] Understanding the complexity of AI development.
[8:09] Without understanding context, we can’t make good prompts.
[8:42] What are the levels of the pyramid that every developer should understand?
[9:16] Developers should start by learning the basics of AI.
[9:22] The question of who is responsible when a website or model goes down.
[14:15] Grounding your AI in reality.
[15:19] Edge deployed AI model.
[17:00] A foundational model is a machine learning model that has been pre-trained on a data set.
[20:40] The limitations of large language models.
[21:00] AI transformer models and their growth in size and complexity.
[21:46] Conversation with John Maeda at the .NET Conf on Semantic Kernel.
[22:02] Integrating these large language models into conventional programming languages.
[23:08] A few exciting and actionable features of semantic kernel.
[28:18] Concerns about data privacy in smart homes.
[29:07] Advice for developers looking to jump into semantic kernel.
Mentioned in this Episode:
Programming with Palermo — New Video Podcast! Email us at programming@palermo.net.
Clear Measure, Inc. (Sponsor)
.NET DevOps for Azure: A Developer’s Guide to DevOps Architecture the Right Way, by Jeffrey Palermo — Available on Amazon!
Jeffrey Palermo’s Twitter — Follow to stay informed about future events!
Want to Learn More?
Visit AzureDevOps.Show for show notes and additional episodes.
100集单集
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