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How Flowise is Changing the GenAI App Revolution

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Manage episode 435150753 series 3594143
内容由SingleStore提供。所有播客内容(包括剧集、图形和播客描述)均由 SingleStore 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

Join us on this intriguing journey where host Madhukar Kumar uncovers the story of FlowiseAI, an AI-powered chatbot tool that soared to fame in the open-source community. Henry Heng, the Founder of FlowiseAI, shares the inception of FlowiseAI was out of the need to streamline repetitive onboarding queries. Listen in as Henry shares the unexpected explosion of interest following its open-sourcing and how community engagement, spearheaded by creators like Leon, has been pivotal to its growth. The conversation takes a fascinating turn with the discussion of Flowise’s versatility, extending to AWS and single store's creative uses for product descriptions, painting a vivid picture of the tool's expansive potential.

Madhukar and Henry discuss the dynamic realm of data platforms, touching on the integration of large language models into developer workflows and the inevitable balance between commercial giants and open-source alternatives. Henry brings a personal perspective to the table, detailing his use of Fowise for managing property documentation and crafting an accompanying chatbot. Henry also addresses the critical issue of data privacy in enterprise environments, exploring how Flowwise approaches these challenges. The strategy behind monetizing Flowwise is also revealed, hinting at an upcoming cloud-hosted iteration and its future under the Y Combinator umbrella. Don't miss out on this insightful conversation on how FlowiseAI is revolutionizing GenAI!

Key Quotes:

  • “What I've experienced is that first you go through the architect. So the architect of companies and the senior teams as well will decide what architecture that we want to go with. And usually, I was part of the conversation as well. We tend to decide between, NoSQL or SQL depending on the use cases that we are using. For schema that are like fast changing schema or inconsistent, not like tabular structured data, we often use NoSQL or MongoDB. And for structured data, we use MySQL from my previous company. That's how we kind of like decide based on the use cases.”
  • “Judging from the interactions that I have with the community, I would say 80 percent of them are using OpenAI and OpenSource is definitely catching up but is still lagging behind OpenAI. But I do see the trend that is starting to pick up, like especially you have the MixedRoute, you have Lama2 as well. But the problem is that I think the cost is still the major factor. Like, people tend to go to which large language models has the lowest cost, right?”

Timestamps

  • (00:00) Building FlowiseAI to open source
  • (5:07) Innovative Use Cases of Flowwise
  • (10:15) Types of users of Flowise
  • (19:39) Database Architecture and Future Technology
  • (32:30) Quick hits with Henry

Links

Connect with Henry

Visit FlowiseAI

Connect with Madhukar

Visit SingleStore

  continue reading

12集单集

Artwork
icon分享
 
Manage episode 435150753 series 3594143
内容由SingleStore提供。所有播客内容(包括剧集、图形和播客描述)均由 SingleStore 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

Join us on this intriguing journey where host Madhukar Kumar uncovers the story of FlowiseAI, an AI-powered chatbot tool that soared to fame in the open-source community. Henry Heng, the Founder of FlowiseAI, shares the inception of FlowiseAI was out of the need to streamline repetitive onboarding queries. Listen in as Henry shares the unexpected explosion of interest following its open-sourcing and how community engagement, spearheaded by creators like Leon, has been pivotal to its growth. The conversation takes a fascinating turn with the discussion of Flowise’s versatility, extending to AWS and single store's creative uses for product descriptions, painting a vivid picture of the tool's expansive potential.

Madhukar and Henry discuss the dynamic realm of data platforms, touching on the integration of large language models into developer workflows and the inevitable balance between commercial giants and open-source alternatives. Henry brings a personal perspective to the table, detailing his use of Fowise for managing property documentation and crafting an accompanying chatbot. Henry also addresses the critical issue of data privacy in enterprise environments, exploring how Flowwise approaches these challenges. The strategy behind monetizing Flowwise is also revealed, hinting at an upcoming cloud-hosted iteration and its future under the Y Combinator umbrella. Don't miss out on this insightful conversation on how FlowiseAI is revolutionizing GenAI!

Key Quotes:

  • “What I've experienced is that first you go through the architect. So the architect of companies and the senior teams as well will decide what architecture that we want to go with. And usually, I was part of the conversation as well. We tend to decide between, NoSQL or SQL depending on the use cases that we are using. For schema that are like fast changing schema or inconsistent, not like tabular structured data, we often use NoSQL or MongoDB. And for structured data, we use MySQL from my previous company. That's how we kind of like decide based on the use cases.”
  • “Judging from the interactions that I have with the community, I would say 80 percent of them are using OpenAI and OpenSource is definitely catching up but is still lagging behind OpenAI. But I do see the trend that is starting to pick up, like especially you have the MixedRoute, you have Lama2 as well. But the problem is that I think the cost is still the major factor. Like, people tend to go to which large language models has the lowest cost, right?”

Timestamps

  • (00:00) Building FlowiseAI to open source
  • (5:07) Innovative Use Cases of Flowwise
  • (10:15) Types of users of Flowise
  • (19:39) Database Architecture and Future Technology
  • (32:30) Quick hits with Henry

Links

Connect with Henry

Visit FlowiseAI

Connect with Madhukar

Visit SingleStore

  continue reading

12集单集

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