Artwork

コンテンツは SingleStore によって提供されます。エピソード、グラフィック、ポッドキャストの説明を含むすべてのポッドキャスト コンテンツは、SingleStore またはそのポッドキャスト プラットフォーム パートナーによって直接アップロードされ、提供されます。誰かがあなたの著作物をあなたの許可なく使用していると思われる場合は、ここで概説されているプロセスに従うことができますhttps://ja.player.fm/legal
Player FM -ポッドキャストアプリ
Player FMアプリでオフラインにしPlayer FMう!

How Flowise is Changing the GenAI App Revolution

37:27
 
シェア
 

Manage episode 435150753 series 3594143
コンテンツは SingleStore によって提供されます。エピソード、グラフィック、ポッドキャストの説明を含むすべてのポッドキャスト コンテンツは、SingleStore またはそのポッドキャスト プラットフォーム パートナーによって直接アップロードされ、提供されます。誰かがあなたの著作物をあなたの許可なく使用していると思われる場合は、ここで概説されているプロセスに従うことができますhttps://ja.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 つのエピソード

Artwork
iconシェア
 
Manage episode 435150753 series 3594143
コンテンツは SingleStore によって提供されます。エピソード、グラフィック、ポッドキャストの説明を含むすべてのポッドキャスト コンテンツは、SingleStore またはそのポッドキャスト プラットフォーム パートナーによって直接アップロードされ、提供されます。誰かがあなたの著作物をあなたの許可なく使用していると思われる場合は、ここで概説されているプロセスに従うことができますhttps://ja.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 つのエピソード

Todos os episódios

×
 
Loading …

プレーヤーFMへようこそ!

Player FMは今からすぐに楽しめるために高品質のポッドキャストをウェブでスキャンしています。 これは最高のポッドキャストアプリで、Android、iPhone、そしてWebで動作します。 全ての端末で購読を同期するためにサインアップしてください。

 

クイックリファレンスガイド