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Ep 41: Head of AI at Snowflake Baris Gultekin on Why They Built Their Own LLM, Governance as a Moat, and the Most Common Enterprise Use-Cases

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内容由Redpoint Ventures and By Redpoint Ventures提供。所有播客内容(包括剧集、图形和播客描述)均由 Redpoint Ventures and By Redpoint Ventures 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

Snowflake sits in a unique position in the AI landscape: They enable fast, secure, and scalable proprietary data access for thousands of customers, many of whom are building AI tools. They also maintain their own suite of AI products, increasing the utility of their platform and empowering customers who may not have the resources to build their own.

That’s why it was so fascinating to speak with Baris Gultekin, Snowflake’s Head of AI, on our latest Unsupervised Learning. Baris has helped Snowflake launch several key products, including Cortex, AI Data Cloud, and even Snowflake’s own LLM, called Arctic. Baris was a founder himself — he joined Snowflake through an acquisition of his blockchain API startup, nxyz. He has a unique window into the future of AI via his role building key infrastructure. It was really fun to dive deep into this side of the AI ecosystem with Baris.

[0:00] Intro

[0:33] Snowflake's AI Product Portfolio

[0:52] Building Arctic LLM: Challenges and Innovations

[2:57] Use Cases and Applications of Arctic LLM

[3:10] Cortex: Snowflake's Managed Service for LLMs

[4:26] Tackling BI Challenges with Cortex Analyst

[8:46] Data Extraction and Analysis with AI

[10:15] Snowflake's AI Strategy and Future Directions

[13:12] Governance and Security in AI Deployments

[22:25] Supporting and Integrating New AI Models

[24:02] Discussing the 405B AI Model

[25:02] Enterprise Use Cases and Cost Considerations

[26:09] Future of Arctic LM and Security Concerns

[26:59] Open Source Models and Guardrails

[30:21] Internal Use of LLMs at Snowflake

[31:32] Comparing Snowflake and Databricks AI Strategies

[33:24] Opportunities for AI Startups

[34:14] Exciting AI Developments and Future Prospects

[40:34] Over-hyped/Under-hyped

[45:58] Closing Thoughts and Resources

With your co-hosts:

@jacobeffron

- Partner at Redpoint, Former PM Flatiron Health

@patrickachase

- Partner at Redpoint, Former ML Engineer LinkedIn

@ericabrescia

- Former COO Github, Founder Bitnami (acq’d by VMWare)

@jordan_segall

- Partner at Redpoint

  continue reading

50集单集

Artwork
icon分享
 
Manage episode 436646263 series 3495253
内容由Redpoint Ventures and By Redpoint Ventures提供。所有播客内容(包括剧集、图形和播客描述)均由 Redpoint Ventures and By Redpoint Ventures 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

Snowflake sits in a unique position in the AI landscape: They enable fast, secure, and scalable proprietary data access for thousands of customers, many of whom are building AI tools. They also maintain their own suite of AI products, increasing the utility of their platform and empowering customers who may not have the resources to build their own.

That’s why it was so fascinating to speak with Baris Gultekin, Snowflake’s Head of AI, on our latest Unsupervised Learning. Baris has helped Snowflake launch several key products, including Cortex, AI Data Cloud, and even Snowflake’s own LLM, called Arctic. Baris was a founder himself — he joined Snowflake through an acquisition of his blockchain API startup, nxyz. He has a unique window into the future of AI via his role building key infrastructure. It was really fun to dive deep into this side of the AI ecosystem with Baris.

[0:00] Intro

[0:33] Snowflake's AI Product Portfolio

[0:52] Building Arctic LLM: Challenges and Innovations

[2:57] Use Cases and Applications of Arctic LLM

[3:10] Cortex: Snowflake's Managed Service for LLMs

[4:26] Tackling BI Challenges with Cortex Analyst

[8:46] Data Extraction and Analysis with AI

[10:15] Snowflake's AI Strategy and Future Directions

[13:12] Governance and Security in AI Deployments

[22:25] Supporting and Integrating New AI Models

[24:02] Discussing the 405B AI Model

[25:02] Enterprise Use Cases and Cost Considerations

[26:09] Future of Arctic LM and Security Concerns

[26:59] Open Source Models and Guardrails

[30:21] Internal Use of LLMs at Snowflake

[31:32] Comparing Snowflake and Databricks AI Strategies

[33:24] Opportunities for AI Startups

[34:14] Exciting AI Developments and Future Prospects

[40:34] Over-hyped/Under-hyped

[45:58] Closing Thoughts and Resources

With your co-hosts:

@jacobeffron

- Partner at Redpoint, Former PM Flatiron Health

@patrickachase

- Partner at Redpoint, Former ML Engineer LinkedIn

@ericabrescia

- Former COO Github, Founder Bitnami (acq’d by VMWare)

@jordan_segall

- Partner at Redpoint

  continue reading

50集单集

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