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
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, Jonathan previously helped pioneer natural language search at Powerset, which was acquired by Microsoft.
AGENDA:
03:35 Data, Compute, Algorithms: What is Most Abundant? What is Lacking Most?
09:18 What Does No One Know About AI's Data Requirements That Everyone Should?
17:05 The Biggest Challenges Enterprises Have with AI Adoption
20:38 Why Will 99% of Knowledge Work Will be Gone in 10 Years
27:12 How Will Data-Driven Feedback Loops Replace Technology as the Moat
36:08 Who Wins the Data Labelling Market? Who Loses?
38:23 Is Revenue BS in Data Labelling? Are Players Calling GMV Revenue?
45:20 Why is SaaS Dead in a World of AI?
51:23 Will the Phone be the Primary User Interface to an AI World?
57:07 Quickfire Round
TWiST 500 interviews with Cortical Labs, Turing, AND Mercor | E2159
Today’s show:
Alex is back with three more awesome interviews with founders on the bleeding edge of innovative tech.
Dr. Hon Weng Chong walks us through the basics of biological computing and Cortical Labs’ first-ever commercial computer running on living human cells.
Turing founder Jonathan Siddarth unpacks the secrets of LLM benchmarking, and explains why even our most advanced tests need to get much much harder right away.
Finally, Mercor founder Brendan Foody on how AI is about to reinvent the hiring process, and marrying the effectiveness of recruiters with the ease of online job boards.
It’s three — count ’em, three — can’t miss TWiST interviews guaranteed to make you smarter
Timestamps:
(0:00) OpenAI’s GPT-5: When is it coming out? Is it going to be TOO smart?
(08:06) Cortical Labs’ Hon Weng Chong on the electric connection between neuroscience and machine learning
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(11:27) Show Continues…
(15:17) The extreme difficulty of going from the lab to a shippable product
(20:00) .TECH: Say it without saying it. Head to www.get.tech/twist or your favorite registrar to get a clean, sharp .tech domain today.
(21:05) Show Continues…
(28:15) Why data is a factor of time
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(31:16) Show Continues…
(42:44) Turing CEO Jonathan Siddarth explains why it’s so important to keep benchmarking our LLMs
(47:24) What it means when a model “saturates” a test, and why benchmarks need to get HARDER
(50:22) What happens with the LLMs can answer all of our smartest questions?
(53:44) AI Agents train in gyms? Wait, really?
(01:01:33) Coding teaches models how to think, and more training mysteries don’t understand
(01:03:11) Brendan Foody from Mercor explains the “matching problem” that makes hiring such a pain
(01:07:02) How Mercor combines a job board’s distribution with the value of a recruitment agency
(01:10:49) Brendan recalls building his first AI interviewer in his college dorm
(01:20:16) Mercor has the opposite of a retention problem and crazy growth
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What’s the path to AGI? A conversation with Turing Co-founder and CEO Jonathan Siddharth
In this episode of Gradient Dissent, Jonathan Siddharth, CEO & Co-Founder of Turing, joins host Lukas Biewald to discuss the path to AGI.
They explore how Turing built a "developer cloud" of 3.7 million engineers to power AGI training, providing high-quality code and reasoning data to leading AI labs. Jonathan shares insights on Turing’s journey, from building coding datasets to solving enterprise AI challenges and enabling human-in-the-loop solutions. This episode offers a unique perspective on the intersection of human intelligence and AGI, with an eye on the expansion of new domains beyond coding.
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