01:26 Journey to Snowflake02:32 Snowflake and AI06:43 Choosing your model07:44 Snowflake & OS09:43 Innovations to reduce training data size10:59 From large to small models13:14 Snowflake and agentic systems15:50 AI & data security17:17 Access control layer18:14 Embedded applications19:55 Data sharing21:37 Snowflake training & inference23:12 Data reshaping24:40 Structured versus unstructured model inputs25:24 Models providing the mean v. exceptions27:19 Vector databases30:33 Summary

<description>&lt;p&gt;01:26 Journey to Snowflake&lt;/p&gt;&lt;p&gt;02:32 Snowflake and AI&lt;/p&gt;&lt;p&gt;06:43 Choosing your model&lt;/p&gt;&lt;p&gt;07:44 Snowflake &amp; OS&lt;/p&gt;&lt;p&gt;09:43 Innovations to reduce training data size&lt;/p&gt;&lt;p&gt;10:59 From large to small models&lt;/p&gt;&lt;p&gt;13:14 Snowflake and agentic systems&lt;/p&gt;&lt;p&gt;15:50 AI &amp; data security&lt;/p&gt;&lt;p&gt;17:17 Access control layer&lt;/p&gt;&lt;p&gt;18:14 Embedded applications&lt;/p&gt;&lt;p&gt;19:55 Data sharing&lt;/p&gt;&lt;p&gt;21:37 Snowflake training &amp; inference&lt;/p&gt;&lt;p&gt;23:12 Data reshaping&lt;/p&gt;&lt;p&gt;24:40 Structured versus unstructured model inputs&lt;/p&gt;&lt;p&gt;25:24 Models providing the mean v. exceptions&lt;/p&gt;&lt;p&gt;27:19 Vector databases&lt;/p&gt;&lt;p&gt;30:33 Summary&lt;/p&gt;
</description>

Join us in discussion with Baris Gultekin, Head of AI at Snowflake, about the rapidly evolving AI stack.  

Office Hours with Baris Gultekin: The Era of Enterprise AI is Here

01:43 Tabular Acquisition by Databricks05:57 BI's Third Form09:12 Future of BI12:50 Data Quality in the World of LLMs18:48 Building Resilient Data Pipelines & ETL21:01 Evolving Role of BI Analysts23:18 Data and Decision-Making28:05 Conclusion

<description>&lt;p&gt;01:43 Tabular Acquisition by Databricks&lt;/p&gt;&lt;p&gt;05:57 BI's Third Form&lt;/p&gt;&lt;p&gt;09:12 Future of BI&lt;/p&gt;&lt;p&gt;12:50 Data Quality in the World of LLMs&lt;/p&gt;&lt;p&gt;18:48 Building Resilient Data Pipelines &amp; ETL&lt;/p&gt;&lt;p&gt;21:01 Evolving Role of BI Analysts&lt;/p&gt;&lt;p&gt;23:18 Data and Decision-Making&lt;/p&gt;&lt;p&gt;28:05 Conclusion&lt;/p&gt;
</description>

Tom Tunguz & Lauren DeMeuse from Theory Ventures join Benn Stancil, former Field CTO at Thoughtspot and co-founder of Mode. In this discussion, we cover the future of BI, ETL pipelines, and data analysts, and the potential for LLMs to transform the way to do business analysis.


Office Hours with Benn Stancil: BI's Third Form

01:55 Big Data is Dead06:41 Ease of Use08:54 Hybrid Architecture10:30 Audience Question: LLMs for Onboarding?12:55 Hybrid Architecture Enables New Software Design16:58 DuckDB & ETL19:24 Duck Puns22:07 Duck Community24:32 Summary

<description>&lt;p&gt;01:55 Big Data is Dead&lt;/p&gt;&lt;p&gt;06:41 Ease of Use&lt;/p&gt;&lt;p&gt;08:54 Hybrid Architecture&lt;/p&gt;&lt;p&gt;10:30 Audience Question: LLMs for Onboarding?&lt;/p&gt;&lt;p&gt;12:55 Hybrid Architecture Enables New Software Design&lt;/p&gt;&lt;p&gt;16:58 DuckDB &amp; ETL&lt;/p&gt;&lt;p&gt;19:24 Duck Puns&lt;/p&gt;&lt;p&gt;22:07 Duck Community&lt;/p&gt;&lt;p&gt;24:32 Summary&lt;/p&gt;
</description>

Tom Tunguz & Lauren DeMeuse from Theory Ventures join Jordan Tigani, CEO and Co-Founder of MotherDuck. In this discussion, we cover the evolution of enterprise data needs and database architectures, the importance of ease of use, and the value of levity and personality in your brand.




Office Hours with Jordan Tigani: Modern Data Architectures

0:00 Office Hours - Evan Cheng01:28 From Meta to Mysten04:54 Why Develop a New Language, Move11:15 Developer Response to Move13:21 Zero Knowledge (ZK) Proof of Login19:00 Kiosk24:34 On Chain Storage Limitations29:01 DAGs & Web330:01 Mysten Labs Ecosystem & SUI34:03 SUI Token Launch38:30 Closing

<description>&lt;p&gt;0:00 Office Hours - Evan Cheng&lt;/p&gt;&lt;p&gt;01:28 From Meta to Mysten&lt;/p&gt;&lt;p&gt;04:54 Why Develop a New Language, Move&lt;/p&gt;&lt;p&gt;11:15 Developer Response to Move&lt;/p&gt;&lt;p&gt;13:21 Zero Knowledge (ZK) Proof of Login&lt;/p&gt;&lt;p&gt;19:00 Kiosk&lt;/p&gt;&lt;p&gt;24:34 On Chain Storage Limitations&lt;/p&gt;&lt;p&gt;29:01 DAGs &amp; Web3&lt;/p&gt;&lt;p&gt;30:01 Mysten Labs Ecosystem &amp; SUI&lt;/p&gt;&lt;p&gt;34:03 SUI Token Launch&lt;/p&gt;&lt;p&gt;38:30 Closing&lt;/p&gt;&lt;p&gt; &lt;/p&gt;
</description>

Please join us for a conversation between Tom Tunguz, GP of Theory Ventures, and Evan Cheng, Co-Founder & CEO of Mysten Labs. We cover his advances in Web3 (like a new language, ZK proof of logins, and kiosks) to the Mysten ecosystem and future  of the blockchain developer experience.


Office Hours with Evan Cheng, Building the Future of Blockchains

Takeaways from this discussion include:<ol><li>There is a pendulum between governance and self-serve, and that swing is narrowing with developments like Omni</li><li>There's a dynamic with centralization and decentralization hybrid execution at the edge which allows super-interactive user experiences. </li><li>As these experiences improve, the number of people who benefit and can access data in meaningful ways only increases.</li></ol>00:06 Introduction01:27 Being Chief Analytics Officer04:08 Evolution of BI08:23  Data Organization Structure10:53  Data Permissioning Philosophy14:12  Hybrid Execution17:36  BI Application Architecture19:36 Mitigating Buyer Fatigue21:20 BI & AI25:59 Semantic Layer27:12 Audience Question: Should AI Suggest Analyses?28:43 Embedded Analytics32:48 Will AI Automate BI Users Away?35:00 Summary

<description>&lt;p&gt;Takeaways from this discussion include:&lt;/p&gt;&lt;ol&gt;&lt;li&gt;There is a pendulum between governance and self-serve, and that swing is narrowing with developments like Omni&lt;/li&gt;&lt;li&gt;There's a dynamic with centralization and decentralization hybrid execution at the edge which allows super-interactive user experiences. &lt;/li&gt;&lt;li&gt;As these experiences improve, the number of people who benefit and can access data in meaningful ways only increases.&lt;/li&gt;&lt;/ol&gt;&lt;p&gt;00:06 Introduction&lt;/p&gt;&lt;p&gt;01:27 Being Chief Analytics Officer&lt;/p&gt;&lt;p&gt;04:08 Evolution of BI&lt;/p&gt;&lt;p&gt;08:23  Data Organization Structure&lt;/p&gt;&lt;p&gt;10:53  Data Permissioning Philosophy&lt;/p&gt;&lt;p&gt;14:12  Hybrid Execution&lt;/p&gt;&lt;p&gt;17:36  BI Application Architecture&lt;/p&gt;&lt;p&gt;19:36 Mitigating Buyer Fatigue&lt;/p&gt;&lt;p&gt;21:20 BI &amp; AI&lt;/p&gt;&lt;p&gt;25:59 Semantic Layer&lt;/p&gt;&lt;p&gt;27:12 Audience Question: Should AI Suggest Analyses?&lt;/p&gt;&lt;p&gt;28:43 Embedded Analytics&lt;/p&gt;&lt;p&gt;32:48 Will AI Automate BI Users Away?&lt;/p&gt;&lt;p&gt;35:00 Summary&lt;/p&gt;&lt;p&gt;&lt;br /&gt; &lt;/p&gt;
</description>

Colin Zima, Co-Founder and CEO of Omni Analytics and previously Chief Analytics Officer at Looker during its $2.6b acquisition by Google joins Tom Tunguz of Theory Ventures to discuss the evolving landscape of business intelligence including impacts of AI, self-service trends, and enhanced focus on data governance & security.

Office Hours with Tom Tunguz & Colin Zima

A show that invites luminaries from Startupland to talk about how to build great businesses. Questions are collected from the audience & interleaved into the conversation.

Office Hours with Tomasz Tunguz

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