The Ledger
Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.
why aren't all 6,166 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 36 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable
Trojanowski: AI models will subsume agent harness engineering in 2-5 years
“I think that how long it will take to get swallowed up. I don't know exactly. You know, I think it's probably sub five years. I don't think it's sub two years. I think it's probably sub five years.”
Cerebras cloud achieves 10x inference speedup over fast GPUs on Gemma
“Say, if you run Gemma four, On your GP, you might get like a hundred tokens per second if you have a fast card. If you run it in their cloud, you get anywhere from 800 to 1500 tokens per second. So call it 10 X faster.”
Feldman: Cerebras sales were 10x higher than Groq's at acquisition
“And we were the fastest at it, and the largest, and, you know, our sales were more than 10 times the Grox, and they paid twenty billion dollars for the number two collector.”
Feldman: Cerebras signed an OpenAI compute deal worth over $20 billion
“Remember, we did a huge deal. This is probably the largest deals in Silicon Valley history north of twenty billion dollars.”
Feldman: Chinese open-source AI models trail GPT, Anthropic, and Gemini
“They are behind in chips. But their approach was at the next level is open source models where they're producing some extraordinary models. Not as good as GPT or Anthropic or Google's Gemini, but very good.”
Feldman: Agentic AI workflows are driving CPU demand through the roof
“And so, as we do more and more AI work, and more and more agentic work, we're making more and more calls to CPUs, and therefore the demand for CPUs is through the roof.”
Feldman: AI inference is bottlenecked by data movement, causing GPU slowness
“In inference in AI, it's the exact opposite. You move a huge amount of data, all the weights, from memory to compute, and you need one calculation to generate the next word. And then you have to do it again. So all the time is dominated by the movement of data…”
Feldman: Cerebras moves weights to compute ~2,500x faster than standard GPUs
“And so the speed of moving waits to compute is about two and a half thousand times faster here than on a Wilben GP.”
Feldman: Leading AI labs paused video generation development due to compute costs
“Obviously, what follows that Is video, because a video is just a collection of images. But that takes an enormous amount of compute right now. And that's one of the reasons it's been sort of set aside by the leading labs. So unbelievably computation intensive.”
Feldman: Cerebras signed a 760-megawatt multi-year compute deal with OpenAI
“The deal is 760 megawatts, 250 megawatts in 26 on a multi-year lease. An additional 250 megawatts in 27, on a multi-year lease, and an additional in 28, a multi-year lease.”
Katti: OpenAI must build its own compute infrastructure alongside partners
“I think what's becoming clear is to build the kind of compute we need and at this scale we have to not just rely on getting compute from our partners. We increasingly have to take a much more active role in building and getting that compute that we need.”
Katti: OpenAI commits to not taking existing power from local grids
“Whenever we build a data center anywhere, we make it a hard commitment that we are not taking power away from the grid. In fact, we are investing in the grid to generate new power so that we can consume it for data centers.”
Katti: Modern AI model training consists heavily of inference workloads
“We don't like to make a distinction between Training and infants, because a lot of training is now infants. So when we train a new model, we are generating synthetic data, for example. That's inference. When we train a new model, we are doing post-train, and t…”
Sachin Katti: OpenAI tripled compute and tripled revenue
“We tripled compute and we tripled revenue.”
Katti: Demand far outstrips OpenAI's compute supply, zero goes to waste
“Demand far outstrips. Compute supply today. So anything we can bring online, we consume immediately. So there's no compute that is going to waste for us.”
Katti: AI will soon design systems and chips for next-gen AI
“We do believe that the world of Likersh is not that far, where AI will design the systems it needs to train and run the next generation of AI.”
Sachin Katti: AI tokens will always command a premium due to compute shortages
“So in a world where computers are shortage, therefore, tokens are always going to be at a premium, and there's a shortage of tokens that we can produce, given the limited compute that we have”
Sands: AI agents and stablecoins will make microtransactions viable
“I think when we enter a world where like the human is not doing any work to execute the transaction, you're not typing in any credentials, you're not navigating to any web pages, the agent's doing it for you then microtransactions become viable, and you pair t…”
Deployment, not coding, is the new bottleneck for AI app development
“But now that like the app can be built in coded in 20 minutes, like Okay, the long pole is deploying the thing. And so, anyway, vibe coding was easy. Vibe deployment has become like more of the binding constraint.”
Sands: AI agents will drive adoption of real-time metering and billing
“I think in the world of agents, what we're gonna see more and more of is real-time metering, like, what have you consumed And real-time billing”
Sands: AI agents will operate as multifaceted economic actors within 12 months
“I think the most interesting thing in the next 12 months is, I mean, I think we'll move up and I don't know if it's going to be to four or to five, But I think the more interesting thing is actually that, like, we talked about agents as economic actors, mostly…”
Catanzaro: Moore's Law has been economically dead for five to ten years
“The original statement of Moore's law was economic, right? It was about, we can afford to put twice as many transistors on the same chip in every, whatever, 24 months, whatever the time period is. And these days that is, Absolutely not the case. It hasn't been…”
Catanzaro: At AI compute limits, intelligence gains require higher efficiency
“If you accept as the truth that we're going to be running at the limit, then what that means is that the way to get more intelligence is to be more efficient. We can't get more intelligence by applying more force if we're already at the limit. We have to be mo…”
Catanzaro: Multi-token prediction lowers inference costs as model accuracy improves
“With multi-token prediction, the speed that you get is a function of the accuracy of your model. The more accurate your model is, the faster the inference is, the cheaper the inference is, the more accurate it is. That's not usually how it works, but in this c…”
Prince predicts bot traffic will be 1,000x human traffic within five years
“I think that if you extrapolate this out, you know, in five years, I think you'll see a thousand times more bot traffic than human traffic. And if I had to take kind of an over under bet on that, I'd take the over bet that it's just going to, it's growing at s…”
Prince: There will never be a 14th DNS root server
“There will never be a 14th root server, and the organizations that run them will probably never change as well”
Prince: The same individual currently directs all Iranian state cyber attacks
“And the same guy to this day is running all of Iranian cyber attacks.”
Prince: Co-founders asking how to divide responsibilities likely have wrong partners
“If you're asking that question, it probably means you have the wrong co-founders.”
Prince: Log4j-level software vulnerabilities will be found weekly for two years
“You know, I think for the next you know, a 104 days, a 104 weeks. So two years you're going to see a log for J like vulnerability every single week.”
Prince: AI resistance among mid-career workers risks creating a lost generation in tech
“I really do worry that we're going to have this sort of lost generation of sort of either, you know, young millennials or older Gen Z folks that just, they, they're, they were sort of, they're going to have incentives to say we shouldn't use these tools becaus…”
Prince: AI will boost engineering and sales hiring while replacing corporate measurement roles
“If I have a developer and I can now give them AI tools and they're 10 times as productive, I'm gonna hire as many developers as I can. If I, you know, have a salesperson and I can give them tools that eliminate the parts of their job that they don't like, whic…”
Prince: A 12-to-1 manager ratio is optimal for flat organizations
“I think 12 to one is right. And the benefit of expanding the number of the average number of direct reports Is it inherently flattens the organization?”
Prince: Local newspaper to earn more from AI licensing than display ads
“My wife and I bought the local newspaper in our hometown, Park City, Utah. I think we will make more this year off AI licensing deals than we do off display ads.”
Balaban: AI cloud compute is not a commodity service
“The big thing is that cloud compute is not a commodity service. It is a very complicated, highly vertically integrated type of service that spans everything from land, land entitlement, Construction, HPC, high performance computing design, software, virtualiza…”
Balaban predicts the neocloud market will support multiple large players
“I think it's absolutely room for multiple very large players, just like the traditional cloud business has shown that there's room for multiple large winners and multiple large players.”
Balaban: The AI industry continues to underbuild compute infrastructure
“Well, I think that we continue to be generally under building.”
Balaban: NVIDIA's real software moat is cuDNN, not just CUDA
“One of the big moats they've got is just The QDNN stack. It's not just CUDA. It's, you know, CUDA is sure. That's like the water we all swim, but like CUDNN has got so many, you know, matrix multiplication, routine optimizations baked into it.”
Balaban: Modern AI applications are far less latency-sensitive than legacy cloud apps
“The old school traditional legacy cloud business was so latency focused because of some of the applications, but this new fleet of AI applications are far less latency sensitive.”
Balaban: Lambda is leasing 2023-deployed H100 GPUs at higher rates today
“You actually look at the chips that we deployed in twenty-twenty-three, H-one hundreds. We're now leasing those out at a higher rate. Now than we were originally in 20, 23.”
Balaban: Multimodal AI will eventually render every pixel of software directly
“I think that for a lot of the pieces of software on your computer, you might see that taking over where, you know, you can get the glimpse of the future with this ASCII art, and then eventually it'll also have a multimodal network that's generating every pixel…”
Balaban: Everyone in the US will eventually require at least one GPU
“I believe that in the future, everybody in the United States will need the computational power of one GPU or more to just do their daily work You know, enjoy life, whether it's getting access, whether it's getting entertained, whether it's being productive, wh…”
Pre-training models on language before reinforcement learning is the correct architecture
“Having the model have a prior of language and being able to like, think in language and then train on top of that, that seems like clearly the right. The right thing to do.”
Combining reinforcement learning with pre-training outperforms scaling pre-training alone
“If you were just trying to scale pre-training, you wouldn't get anywhere near as far as also trying to scale RL on top of pre-training, which is what we do now.”
Levie: CIO sentiment on AI remains optimistic, avoiding trough of disillusionment
“I think the tone is actually remarkably optimistic and excited and positive as opposed to, you know, there's a sort of, You know, typical trough of disillusionment, you know, from Gartner and the hype cycle or whatnot.”
Levie: A single coding agent task can consume $1,000 in compute
“One, you know, coding agent could be consuming, you know, a thousand dollars of compute on a single task. So clearly like you can't lump that all into a 20 dollar per user per month fee.”
Levie: AI compute cost reductions will take 5 to 10 years
“The data center providers, the labs, et cetera, have pricing power. They don't need to lower their prices on anything. So you're not seeing the typical things that drive down the cost of compute. I'm highly optimistic that that happens over the next five to 10…”