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Impact of LLMs on the Tech Stack and Product Development // Anand Das // #188

Impact of LLMs on the Tech Stack and Product Development // Anand Das // #188

FromMLOps.community


Impact of LLMs on the Tech Stack and Product Development // Anand Das // #188

FromMLOps.community

ratings:
Length:
55 minutes
Released:
Nov 7, 2023
Format:
Podcast episode

Description

MLOps podcast #188 with Anand Das, Co-founder and CTO of Bito, Impact of LLMs on the Tech Stack and Product Development.

// Abstract
Anand and his team have developed a fascinating Chrome extension called "explain code" that has garnered significant attention in the tech community. They have expanded their extension to other platforms like Visual Studio code and Chat Brains, creating a personal assistant for code generation, explanation, and test case writing.

// Bio
Anand Das is the co-founder and CTO of Bito. Previously, he served as the CTO at Eyeota, which was acquired by Dun & Bradstreet for $165M in 2021. Anand also co-founded and served as the CTO of PubMatic in 2006, a company that went public on NASDAQ in 2020 (NASDAQ: PUBM).

Anand has also held various engineering roles at Panta Systems, a high-performance computing startup led by the CTO of Veritas, as well as at Veritas and Symantec, where he worked on a variety of storage and backup products.

Anand holds seven patents in systems software, storage software, advertising, and application software.

// MLOps Jobs board
https://mlops.pallet.xyz/jobs

// MLOps Swag/Merch
https://mlops-community.myshopify.com/

// Related Links
Website: https://bito.ai/

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Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/
Connect with Anand on LinkedIn: https://www.linkedin.com/in/ananddas/

Timestamps:
[00:00] Anand's preferred coffee
[00:15] Takeaways
[02:49] Please like, share, and subscribe to our MLOps channels!
[03:08] Anand's tech background
[10:06] Fun at Optimization Level
[12:59] Trying all APIs
[17:55] Models evaluation decision tree
[22:51] Weights and Biases Ad
[25:04] AI Stack that understands the code
[28:27] Tools for the Guard Rails
[33:23] Seeking solutions before presenting to LLM
[38:46] Prompt-Driven Development Insights
[40:16] Prompting best practices
[42:51] Unneeded complexities
[45:45] Cost-benefit analysis of buying GPUs
[49:13] ML Build vs Buy
[51:26] Best practices for debugging code assistant
[54:58] Wrap up
Released:
Nov 7, 2023
Format:
Podcast episode

Titles in the series (100)

Weekly talks and fireside chats about everything that has to do with the new space emerging around DevOps for Machine Learning aka MLOps aka Machine Learning Operations.