The Tesoro AI Podcast

Enterprise AI Infrastructure: Effectively Deploying AI Models Across Varied Environments | Adam Gibson, Konduit


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Today, I sat with Adam Gibson, the founder of Konduit, who is building the tooling for AI development and model deployment. Konduit is on a mission to help run AI models where developers want them to run - whether that be in the cloud on premise, the edge, or mobile. Adam explains the new projects they are working on and the importance of the acceleration of AI adoption.

Founder Bio:

Adam Gibson is the creator of Deeplearning4j and Konduit serving. He has been focused on building open source AI infrastructure complimenting production deployments since 2013. Adam is a multi book author publishing for O'Reilly Media and Impress Japan. He is based in Japan and focuses on helping companies to strengthen their production deployments.

If your company is looking to scale its AI initiatives, head over to Tesoro AI (www.tesoroai.com). We are experts in AI strategy, staff augmentation, and AI product development.

Timestamps:

2:03 - How Adam got started

6:46 - In what ways are people deploying models for use cases

10:20 - The process of customizing a pre-built model

15:30 - Why the volume and quality of data impact the model

19:45 - What they are working on today Konduit Survey and Eclipse Deeplearning4j

23:37 - The challenges of deploying a model in various environments

27:58 - How is the adoption of AI being used globally to create a competitive advantage

33:09 - The importance of creating a talent pool that can accelerate the adoption of AI

37:30 - If you give people the ability to automatically generate models they will have tools without the discipline and instructions on how to use them and that is a problem

40:29 - How to find Adam Gibson

Resources:

Company website: https://www.konduit.ai/ LinkedIn: https://www.linkedin.com/company/konduitkk Facebook: https://www.facebook.com/konduitai/ Twitter: https://mobile.twitter.com/KonduitAi

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The Tesoro AI PodcastBy Darius Gant

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