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cover of episode 879: Serverless, Parallel, and AI-Assisted: The Future of Data Science is Here, with Zerve’s Dr. Greg Michaelson

879: Serverless, Parallel, and AI-Assisted: The Future of Data Science is Here, with Zerve’s Dr. Greg Michaelson

2025/4/15
logo of podcast Super Data Science: ML & AI Podcast with Jon Krohn

Super Data Science: ML & AI Podcast with Jon Krohn
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Greg Michelson: Zerve平台在过去一年中取得了显著进展，推出了许多新功能，例如Fleet功能，它利用无服务器技术实现了代码执行的大规模并行化，极大地提高了处理速度，尤其是在处理大型语言模型调用时，无需编写额外的代码，也不会增加成本。此外，Zerve集成的AI助手可以帮助用户编写代码、构建模块，并简化了整个编码过程。Zerve的图架构允许同时运行多个代码块，支持多人协同工作，提高了团队协作效率。Zerve并非低代码/无代码工具，而是代码优先的数据科学环境，它通过协作式图环境和并行化等特性，帮助代码优先的数据团队将模型开发周期缩短多达9倍。每个节点都是一个代码窗口，用户可以全屏查看代码、输入和输出，方便代码预览和调试。Zerve支持与多种大型语言模型交互，包括OpenAI、AWS Bedrock和Hugging Face，用户可以根据自身需求和数据安全考虑选择合适的模型。Zerve的AI助手是一个可以操作画布的代理，可以根据自然语言指令创建整个项目工作流程，极大地提高了开发效率。 Jon Krohn: 作为主持人，Jon Krohn主要负责引导话题，提出问题，并对Greg Michelson的回答进行总结和补充。他从用户的角度出发，提出了许多实际问题，例如如何理解Zerve的DAG架构，如何集成LLM，以及如何解决SaaS公司面临的挑战等。

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Greg Michaelson speaks to Jon Krohn about the latest developments at Zerve, an operating system for developing and delivering data and AI products, including a revolutionary feature allowing users to run multiple parts of a program’s code at once and without extra costs. You’ll also hear why LLMs might spell trouble for SaaS companies, Greg’s ‘good-cop, bad-cop’ routine that improves LLM responses, and how RAG (retrieval-augmented generation) can be deployed to create even more powerful AI applications.

Additional materials: www.superdatascience.com/879)

This episode is brought to you by Trainium2, the latest AI chip from AWS) and by the Dell AI Factory with NVIDIA).

Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information.

In this episode you will learn:

  • (04:00) Zerve’s latest features

  • (35:26) How Zerve’s built-in API builder and GPU manager lowers barriers to entry

  • (40:54) How to get started with Zerve

  • (41:49) Will LLMs make SaaS companies redundant?

  • (52:29) How to create fairer and more transparent AI systems

  • (56:07) The future of software developer workflows