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

Harry Stebbings interviews Jonathan Siddharth, the Founder and CEO of Turing, about the evolving landscape of data labeling, the shift towards AI-driven research acceleration, and the automation of knowledge work. Jonathan discusses how Turing is training superintelligence by creating RL environments for various industries, functions, and roles, enabling AI agents to perform complex tasks. He also touches on the importance of custom models for enterprises, the potential for AI to automate knowledge work, and the future of SaaS in an AI-dominated world. The conversation explores the challenges and opportunities in AI, including data acquisition, revenue concentration, and the role of governments in AI development, as well as the potential for AI to drive productivity and innovation across industries.

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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

The Evolution of Data Labeling and Turing's Role in Superintelligence Training

From Chatbots to Agents: The Changing Data Landscape and Reinforcement Learning Environments

Data Acquisition and Turing's Differentiation in the AI Landscape

The Necessity of Custom Models and the Automation of Knowledge Work

Adoption Challenges and the Pace of AI Progression in Large Companies

The Transfer of Budget from Human Labor to AI Technology

The Future of Work in an AI-Automated World

Moats in an AI-Driven World and the Importance of Data-Driven Feedback Loops

Revenue Metrics and Competition in the AI Data Provisioning Market

Respect for Competitors and the Potential for Government Involvement

The Absence of an AI Bubble and the Power of Current Models

Growing Pains in AI Deployment and the Grand Prize of AGI

The Future of SaaS in an AGI World

The Evolution of Software Engineering and the Discovery Problem

The Future of Data Provisioning and the Importance of Research Depth

Widely Held Beliefs About AI and Underestimating China

Closed vs. Open Models and Elon Musk's Approach to AI Safety

Changing Beliefs and Unpopular Decisions at Turing

Excitement for the Future and the Potential of AI

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

00:00The Evolution of Data Labeling and Turing's Role in Superintelligence Training

The Evolution of Data Labeling and Turing's Role in Superintelligence Training

06:32From Chatbots to Agents: The Changing Data Landscape and Reinforcement Learning Environments

From Chatbots to Agents: The Changing Data Landscape and Reinforcement Learning Environments

11:02Data Acquisition and Turing's Differentiation in the AI Landscape

Data Acquisition and Turing's Differentiation in the AI Landscape

14:19The Necessity of Custom Models and the Automation of Knowledge Work

The Necessity of Custom Models and the Automation of Knowledge Work

18:10Adoption Challenges and the Pace of AI Progression in Large Companies

Adoption Challenges and the Pace of AI Progression in Large Companies

21:35The Transfer of Budget from Human Labor to AI Technology

The Transfer of Budget from Human Labor to AI Technology

24:50The Future of Work in an AI-Automated World

The Future of Work in an AI-Automated World

28:02Moats in an AI-Driven World and the Importance of Data-Driven Feedback Loops

Moats in an AI-Driven World and the Importance of Data-Driven Feedback Loops

31:54Revenue Metrics and Competition in the AI Data Provisioning Market

Revenue Metrics and Competition in the AI Data Provisioning Market

35:24Respect for Competitors and the Potential for Government Involvement

Respect for Competitors and the Potential for Government Involvement

39:32The Absence of an AI Bubble and the Power of Current Models

The Absence of an AI Bubble and the Power of Current Models

41:52Growing Pains in AI Deployment and the Grand Prize of AGI

Growing Pains in AI Deployment and the Grand Prize of AGI

45:51The Future of SaaS in an AGI World

The Future of SaaS in an AGI World

50:51The Evolution of Software Engineering and the Discovery Problem

The Evolution of Software Engineering and the Discovery Problem

55:12The Future of Data Provisioning and the Importance of Research Depth

The Future of Data Provisioning and the Importance of Research Depth

58:31Widely Held Beliefs About AI and Underestimating China

Widely Held Beliefs About AI and Underestimating China

1:00:02Closed vs. Open Models and Elon Musk's Approach to AI Safety

Closed vs. Open Models and Elon Musk's Approach to AI Safety

1:02:07Changing Beliefs and Unpopular Decisions at Turing

Changing Beliefs and Unpopular Decisions at Turing

1:03:36Excitement for the Future and the Potential of AI

Excitement for the Future and the Potential of AI