The Ledger, every show
Every statement that passed quotation and attribution checks, across all 44 shows. Pick shows below, then mix any filter with any other.
shows 
every show 44 of 44
Siddharth: All digital knowledge work will be automated within 10 years
“The glimpse of the future that I see is that all knowledge work is going to be automated. If a human's job involves looking at a computer, analyzing what's on the screen, using different tools, using a keyboard and a mouse, it's going to be automated. It's onl…”
Siddharth: AI will allow individuals to run 7 to 8 companies simultaneously
“Now, I think in the limit over the next decade, every human might run seven to eight companies as these, as the loop from idea to, I mean, as you can go from prompt to company in hopefully like a single step over the next decade.”
Siddharth: AGI development will follow a slow, steady takeoff timeline
“It's innings one, and I believe in slow takeoff. I'm sorry to pour cold water on all the AI doomers that might be listening to this, but we are not in a rapid takeoff scenario. I believe in slow, steady takeoff for AGI and eventually super intelligence.”
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.”
Siddharth: Frontier AI models can autonomously build software systems for weeks
“You're seeing what the coding models today are capable of building end-to-end systems, like coding for days. Sometimes a week.”
AI coding improvements boost model performance across unrelated non-coding tasks
“When the models improve in coding, they have out of domain performance. They also improve in other tasks that have nothing to do with coding for reasons we don't fully understand.”
Siddharth: AGI Will Make Humans 100x More Productive
“AGI is going to just make humans a hundred X more productive.”
Siddharth: AGI will allow non-technical founders to launch startups cheaply
“In a future where AGI exists, this person will recruit a marketing GPT, a software engineer GPT, a PM GPT, and get off the ground for a lot less capital. A million flowers will bloom. Lots and lots of non-technical founders will start companies.”
Siddharth: There will be more software engineers in ten years than today
“I think it'll, I think there'll be more software engineers because if you define a software engineer as somebody who's capable of building a software product to solve a real problem, that pool of builders is going to expand way beyond people who've graduated w…”
Siddharth: Chinese open-source AI models like DeepSeek and Qwen are state-of-the-art
“I think it's very impressive, like the progress that they've made in open source with DeepSeek Kimi Ketu, Kuen. These models are state of the art.”
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…”
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.”
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.”
Siddharth: Turing bridges frontier AI lab data and enterprise deployment
“Most data companies don't see deployment, and most deployment companies don't see data. So Turing is the one company that works with the Frontier AI Labs and Fortune 500 enterprises, and we are a trusted bridge between research and deployment.”
Siddharth: 10-trillion-parameter frontier AI models are now beginning to emerge
“The current series of frontier models are largely in the trillion parameter realm. Yeah. Now we are starting to see 10 trillion parameter models.”
Siddharth: AI scaling laws continue to hold across compute and data
“The scaling laws are continuing to hold, meaning bigger model with more data, with more compute, means that the models smoothly keep getting better. It's like the, when the pre-training loss keeps coming down, it's like the model's performance on also all thes…”
Enterprises are abandoning fine-tuning for frontier models with context management
“What I'm seeing more and more is there's a lot more people going into the no fine tuning camp than a couple of years ago for very high value enterprise use cases.”
Turing works with seven of the eight frontier AI labs
“We work with seven out of the eight frontier labs.”
Siddharth: Enterprise custom AI models are a permanent requirement
“I think it's a permanent requirement.”
Siddharth: Enterprise AI adoption will be slow in back-office, fast in front-office
“In back office automation, it'll probably be very slow, and it'll, it'll probably be the upstarts that'll do things well. I think the change management will be too slow. But I'm optimistic about front office, especially in financial services, life sciences, ph…”
Siddharth: Governments will build sovereign internal AI models
“I think it would make sense for governments to build their own internal versions of some of these models, which would require proprietary data again to be collected.”
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.”
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?”
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.”
OpenAI partnered with Turing to teach GPT-3 coding and tool use
“OpenAI came to us when they were training GPT-III and they wanted to teach GPT-III to code. So we collaborated with them on teaching the models to code and to do tool use, function calling”
Siddharth: AI compute is shifting significantly toward post-training reinforcement learning
“In the past, it was a lot of the compute went into pre-training. Now a lot of compute goes into reinforcement learning in post-training as well. Especially after O-one came out and DeepSeek came out.”
Siddharth: Reinforcement learning is the dominant paradigm for training AI agents
“Today, the dominant paradigm is reinforcement learning.”
Siddharth: Budget transition to AI is highest in marketing and support
“I think the transfer is pretty high in areas like customer support copywriting SEO, like some of these marketing related areas.”
Siddharth: Future hardware will be always-on devices processing multimodal tokens
“We'll have some type of a device that is, that we'll carry that's always on and processing multimodal tokens.”
Siddharth: AI data market will consolidate into a few main winners
“I think there'll be a few winners. I think there'll be a few winners. A few because I do think for the labs, it helps them to have a few partners for resiliency. And I imagine also for price competitiveness. I think there'll be a few winners.”
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.”
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.”
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.”
Siddharth's EA built custom task-management software instead of buying SaaS
“The bottoms up pincer is every human can now write software. My EA wrote software because I have a crazy schedule. Like I work a lot. I travel a lot. Like I'm always on. So it creates a lot of work. So my EA wrote Software to manage her EA team, and that softw…”