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20VC: Scale, Surge, Turing, Mercor: Who Wins & Who Loses in Data Labelling | Is Revenue in Data Labelling Real or GMV? | Why 99% of Knowledge Work Will Go and What Happens Then? | Why SaaS is Dead in a World of AI with Jonathan Siddharth @ Turing

Overview

Shownote

Highlights

Transcript

Chapters

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20VC: Scale, Surge, Turing, Mercor: Who Wins & Who Loses in Data Labelling | Is Revenue in Data Labelling Real or GMV? | Why 99% of Knowledge Work Will Go and What Happens Then? | Why SaaS is Dead in a World of AI with Jonathan Siddharth @ Turing

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch

Dec 01

20VC: Scale, Surge, Turing, Mercor: Who Wins & Who Loses in Data Labelling | Is Revenue in Data Labelling Real or GMV? | Why 99% of Knowledge Work Will Go and What Happens Then? | Why SaaS is Dead in a World of AI with Jonathan Siddharth @ Turing

20VC: Scale, Surge, Turing, Mercor: Who Wins & Who Loses in Data Labelling | Is Revenue in Data Labelling Real or GMV? | Why 99% of Knowledge Work Will Go and What Happens Then? | Why SaaS is Dead in a World of AI with Jonathan Siddharth @ Turing

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch

Dec 01

Overview Shownote Highlights Transcript Chapters Pins

Shownote

Jonathan Siddharth is Founder and CEO of Turing, one of the fastest-growing AI companies advancing frontier models. Jonathan has led the company to an astonishing $300M ARR with just $225M raised and a profitable company. A Stanford-trained AI scientist, J...

Highlights

In this forward-looking discussion, Jonathan Siddharth of Turing explores the transformative impact of AI on knowledge work, enterprise adoption, and the future of software. Moving beyond conventional narratives, he unpacks how reinforcement learning, data loops, and agentic systems are redefining what’s possible in AI development and deployment.

06:17

Agents require teaching the model tool use

15:03

A smaller, fine-tuned model can be faster and more accurate than a giant world model for specific enterprise workflows.

20:16

Convincing financial firms to adopt AI is easier when tied to profit rather than cost-saving.

24:01

Top AI models can produce work indistinguishable from human experts in simple tasks

35:30

Alex Wang from Scale AI is respected for his early insight into data's role in AI.

43:32

Achieving AGI could unlock unprecedented intellectual and economic value

45:20

If you believe in AGI, investing in SaaS apps is unwise because SaaS is over.

54:23

AI devices will become an extension of the brain

57:07

AI will improve incrementally, not through rapid takeoff

Chapters

SaaS and data labeling face automation

00:00

Data, Compute, Algorithms: What is Most Abundant? What is Lacking Most?

03:35

What Does No One Know About AI's Data Requirements That Everyone Should?

09:18

The Biggest Challenges Enterprises Have with AI Adoption

17:05

Why Will 99% of Knowledge Work Will be Gone in 10 Years

20:38

How Will Data-Driven Feedback Loops Replace Technology as the Moat

27:12

Who Wins the Data Labelling Market? Who Loses?

36:08

Is Revenue BS in Data Labelling? Are Players Calling GMV Revenue?

38:23

Why is SaaS Dead in a World of AI?

45:20

Will the Phone be the Primary User Interface to an AI World?

51:23

Quickfire Round

57:07

Transcript

Jonathan Siddharth: I think the era of data labeling companies is over, and it's now the era of research accelerators. All knowledge work is going to be automated. It's only a matter of time. I don't see an AI bubble. These models are incredibly powerful. ...