Prediction Not checkable as stated
Siddharth: Agentic AI will replace services firms like McKinsey, BCG, and Accenture
“So I think like Turing will probably replace companies like McKinsey, Bain, BCG, and every services company like Accenture, TCS, Wipro, Infosys, like all of these companies doing vanilla services that's going to be automated with these agentic systems.”
Prediction Not checkable as stated
Siddharth: Solving multimodality, reasoning, tool use, and coding yields ASI
“Turing's the world's leading research accelerator, working with all of these frontier labs to advance them along I would say the four pillars of superintelligence which is multimodality, reasoning, tool use, and coding. If you solve these four things, you will…”
Insight
Siddharth: ASI means automating 90% of computer tasks for 90% of humans
“And I think of ASI as us having automated 90% of the tasks that 90% of humans do today in front of a computer, right?”
Prediction Not checkable as stated
Siddharth: AI will automate $30 trillion of global knowledge work
“This is like, if you look at those four dimensional, if you look at that four dimensional matrix, that's 30 trillion dollars of knowledge work that is going to be automated.”
Insight
Siddharth: Reasoning models ended demand for simple AI data factories
“This industry had a huge shift after the reasoning models came out late last year, O-one being the first. The shift is, before the reasoning models, this industry needed simple data. Gobs and gobs of simple data. You needed a data factory. Or, ah, this industr…”
Insight
Siddharth: Enterprise AI performs best on 0.5B-to-10B parameter custom models
“It'll probably probably be a smaller model. Oftentimes we see a half a billion to a ten billion parameter model. That's the regime, not a trillion parameter model. And this will be faster, more accurate.”
Prediction Not checkable as stated
Siddharth: Custom LLMs will allow investment firms to employ fewer analysts
“I think, like, the best firms are already doing this, ah, to help an investment analyst make better decisions faster, and eventually with significantly fewer people.”
Assertion Not checkable as stated
Siddharth: Turing works with seven of the eight frontier AI labs
“We work with seven out of the eight Frontier Labs. We work with OpenAI, Anthropic, Meta, Google, Microsoft, Nvidia, Amazon, anybody that's building a Frontier Foundation model, we are probably working with them already.”
Assertion Not checkable as stated
Siddharth: Public internet data for pre-training AI ran out three years ago
“These models ate the internet when they were pre-trained, but the internet data is used up. It was used up like three years ago, right?”
Insight
Siddharth: Verifiable domains allow self-play reinforcement learning to replace RLHF
“Now, for these verifiable domains like coding and math, instead of doing reinforcement learning with human feedback, you can do reinforcement learning. Because you can automatically check when you got the correct answer or not in these verifiable domains. And …”
Prediction Not checkable as stated
Siddharth: AI will progress steadily rather than via rapid takeoff
“I don't think rapid takeoff is how things will unfold. I think it's going to be steady, continuous progress. Every step of the way, we're going to keep moving forward and it's going to be great, and it's great for a few reasons.”
Insight
Siddharth: Frontier AI Training Demands Complex Reasoning and STEM Data
“The race to HGI is on, and the data needs of these models have shifted. These models need incredibly complex data for training them to get better at coding, advanced reasoning, STEM, etc.”
Assertion Not checkable as stated
Siddharth: Turing's Agentic Coding Data Stumps All Current AI Models
“We are creating data for coding now, for agentic coding, that would stump all of today's models and agents built on top of those models.”
Prediction Not checkable as stated
Siddharth: AI models will solve agentic coding benchmarks in six months
“I would give, give that maybe six months before the models climb that hill, and then we'll generate data that's even harder for the models.”
Insight
Siddharth: Enterprise AI does not require 100% accuracy with human oversight
“I feel like the self-driving car industry did a lot of damage to AI in one particular way, which is it because with self-driving cars, 99% accuracy is not enough. That, that last one percent really matters. But with a lot of AI systems, if you're automating th…”
Assertion Not checkable as stated
Siddharth: Enterprise workflow data does not exist on the internet
“To solve real world enterprise workflows, you need, ah, real world enterprise data, and that data doesn't exist on the internet.”
Opinion
Siddharth: Enterprise AI automation is at 0.25 on a 10-point scale
“If I think of a zero to 10 point scale on the consumer side, we are maybe at a three.
On the enterprise side, we are maybe at a .25 at best, right?”
Disclosure
Siddharth: Turing Built Thousands of RL Gyms for Agent Training
“We built thousands of these reinforcement learning gyms to train agents.”
