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The Unbearable Lightness of Data // Rohit Krishnan // #295

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

The Unbearable Lightness of Data // MLOps Podcast #295 with Rohit Krishnan, Chief Product Officer at bodo.ai.

Join the Community: https://go.mlops.community/YTJoinIn

Get the newsletter: https://go.mlops.community/YTNewsletter

// Abstract

Rohit Krishnan, Chief Product Officer at Bodo.AI, joins Demetrios to discuss AI's evolving landscape. They explore interactive reasoning models, AI's impact on jobs, scalability challenges, and the path to AGI. Rohit also shares insights on Bodo.AI’s open-source move and its impact on data science.

// Bio

Building products, writing, messing around with AI pretty much everywhere

// Related Links

Website: www.strangeloopcanon.com

In life, my kids. Professionally, https://github.com/bodo-ai/Bodo ... Otherwise, personally, it's writing every single day at strangeloopcanon.com!

~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~

Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExplore

Join our Slack community [https://go.mlops.community/slack]

Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)]

Sign up for the next meetup: [https://go.mlops.community/register]

MLOps Swag/Merch: [https://shop.mlops.community/]

Connect with Demetrios on LinkedIn: /dpbrinkm

Connect with Rohit on LinkedIn: /rkris

Timestamps:

[00:00] Rohit's preferred coffee

[00:12] Takeaways

[00:46] DeepSeek UI Insight

[07:07] Signal vs. Noise Feedback

[09:24] Report refinement process

[11:54] Cognitive load and model control

[15:27] Future AI possibilities

[18:47] AI data labeling jobs

[21:27] AI noise and overhead

[26:12] Information Overload & Attention

[29:52] AGI Progress Vectors Explained

[37:28] GPU Memory Bottlenecks in AI

[46:23] AI vs ML Engineering

[50:22] Parsing PDFs with Metadata

[53:24] Wrap up

  continue reading

490集单集

Artwork
icon分享
 
Manage episode 470815309 series 3241972
内容由Demetrios提供。所有播客内容(包括剧集、图形和播客描述)均由 Demetrios 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

The Unbearable Lightness of Data // MLOps Podcast #295 with Rohit Krishnan, Chief Product Officer at bodo.ai.

Join the Community: https://go.mlops.community/YTJoinIn

Get the newsletter: https://go.mlops.community/YTNewsletter

// Abstract

Rohit Krishnan, Chief Product Officer at Bodo.AI, joins Demetrios to discuss AI's evolving landscape. They explore interactive reasoning models, AI's impact on jobs, scalability challenges, and the path to AGI. Rohit also shares insights on Bodo.AI’s open-source move and its impact on data science.

// Bio

Building products, writing, messing around with AI pretty much everywhere

// Related Links

Website: www.strangeloopcanon.com

In life, my kids. Professionally, https://github.com/bodo-ai/Bodo ... Otherwise, personally, it's writing every single day at strangeloopcanon.com!

~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~

Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExplore

Join our Slack community [https://go.mlops.community/slack]

Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)]

Sign up for the next meetup: [https://go.mlops.community/register]

MLOps Swag/Merch: [https://shop.mlops.community/]

Connect with Demetrios on LinkedIn: /dpbrinkm

Connect with Rohit on LinkedIn: /rkris

Timestamps:

[00:00] Rohit's preferred coffee

[00:12] Takeaways

[00:46] DeepSeek UI Insight

[07:07] Signal vs. Noise Feedback

[09:24] Report refinement process

[11:54] Cognitive load and model control

[15:27] Future AI possibilities

[18:47] AI data labeling jobs

[21:27] AI noise and overhead

[26:12] Information Overload & Attention

[29:52] AGI Progress Vectors Explained

[37:28] GPU Memory Bottlenecks in AI

[46:23] AI vs ML Engineering

[50:22] Parsing PDFs with Metadata

[53:24] Wrap up

  continue reading

490集单集

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