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 485 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 0 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
Traynor: There is no line of sight to a trillion-dollar European company
“Like I don't see a line of sight to a trillion dollar company in Europe full stop.”
dbt CEO Tristan Handy: The modern data stack concept is dead
“I don't think the modern data stack is a useful idea anymore.”
Srinivas: Google is making a mistake chasing OpenAI with Gemini
“Hence why, like, you know, I actually think Google is making a big mistake by trying to do whatever OpenAI is doing, right, like, going after them with the large, oh, I'm not, they're having GPT-IV, I'm going to turn Gemini.”
Srinivas: Building a web search index is harder than competing with GPT-4
“We believe that building your own index is even harder than trying to compete with GPT-IV because it's not a problem that's just solved with money.”
Srinivas: Citing web sources in AI search constitutes legal fair use
“And it's actually fair use. The fact that you're attributing credit is fair use.”
Mathew Lodge argues prompt engineering is a fallacy and merely trial-and-error
“And so the idea that there's something called prompt engineering, engineering in the sense of you're applying an approach because it's going to give you the output that you desire. Is a complete fallacy. At best it's trial and error. It's prompt trial and erro…”
Wiggins: Data science, not physics, won World War II
“I grew up as a physicist thinking that, you know, physics really won World War II, but now that I'm a data scientist, I realize that it was actually data science that won World War II, but that story was classified for about 75 years, which is the story of how…”
Liberty: Prompt engineering is a fad, not a long-term profession
“A lot of people believe that prompt engineering is incredibly crucial. I don't necessarily buy into that. I don't know if you remember, but people, like, thought that, like you know query building for Google would be a profession too, right? And that didn't qu…”
Stancil: dbt's SQL-based semantic layer is not a real semantic model
“They're moving in, like, the semantic layer tool, so basically they're saying, give us raw data, and we will tell you, like, apply semantics to it. The way that they do that now is through SQL. So, like, semantics are kind of, like, air quote semantics. It's b…”
MongoDB CEO Dev Ittycheria calls Oracle the most hated tech vendor
“Oracle is the most hated vendor in our tech industry. In the tech industry today”
Lowin: Managed hosting for open-source tools is a bad business model
“I think that that is a bad business model. And I sort of, I'm on the record of that. And for a very simple reason, which is that A company that is solving a problem needs to find the correct way to express its knowledge and its solution to that problem.”
Cancel: Traditional CRMs reliant on manual human data entry are insane
“Again, like this idea that we have today of a CRM or centralized place for, to keep all this information is a pretty insane system, right? This idea that humans enter things into one big ledger and they have to enter it in a certain format and all those humans…”
Microsoft Azure 'cheats a little bit' when reporting total cloud revenue
“No, and Azure claims they do as well. Yeah, yeah, if you lump everything in, they claim. Right. But, yeah, they cheat a little bit. They do, and how they break out the numbers.”
Anthony: Autonomous driving cannot be solved with sensors and LiDAR alone
“You can't solve it with sensors. You can't solve it with compute power. You can't solve it with, ah, ah, LiDAR. You can't solve it by knowing exactly where everything, everything is.”
Domingos: Mandating total model explainability literally makes deep learning illegal
“And at the end of the day, you know, you can't, like the European Union, mandate that every model has to be explainable, right? Because then, if you read that law literally, it makes deep learning illegal, right?”
Neuralink's clinical-first strategy leads to grindingly slow progress, says Thomas Reardon
“Whereas if you go just to the clinical population first, which is sort of where Neuralink is going with their work, it's just grindingly slow progress.”
Marcus challenges Andrew Ng: AI cannot automate every one-second mental task
“I don't think it's true at all, so there are some things that people can do in a second that AI can automate, and there are other things that it can't”
Marcus: Drivers should not trust Tesla Autopilot because AI remains unready
“So you should not be trusting a Tesla. Elon might get on 60 minutes and take his hands off the wheel, but you should not be doing the same because the technology is not really there yet.”
Marcus: Current AI techniques are too brittle to earn public trust
“Most of why I don't think we should trust AI right now is that the current techniques that people are using are simply too brittle to earn the trust that we're giving them.”
Open-source software distribution is being superseded by SaaS models
“I almost feel like open source is just being superseded by any software as a service, and what I mean by that is the following. It's like, as soon as you host something as a service, people don't seem to ask so much about open source, right?”
Kulkarni: The big data era is over and the time series era has begun
“The big data era is over, and in fact, we're now entering the time series era for analyzing the past, understanding the present, and predicting the future.”
Horizontal AI Suites Like Salesforce Einstein Are Just Marketing Fluff
“When we hear marketing terms like Einstein, or Sensei, or pick your other dead male inventor, That, that approach applied to a horizontal set of software problems simply doesn't make sense because the interesting stuff recruiting data or hiring data or our dat…”
Ehrenberg: Y Combinator's adversarial founder-investor ethos is 'really shitty'
“It's against, like, the YC ethos. Like, I don't think in many ways that that attitude of it, you know, founder, it's founders versus investors, keep investors at arm's length is really healthy. I actually think that's really shitty. And does founders agree to …”
'Product market fit' is an overused tautology
“Product market fit. Which, I mean, if I hear that again, that's where, big data, whatever big data went to, or Synergy I mean, it's such a tautology, you know, it's like, yeah, ok, people want what you've built a product that people want to buy, it's so insigh…”
Marcus: Siri's technology is not fundamentally different from ELIZA
“But the technology for Siri is not really that different from the technology for ELISA, and Siri is still very far from artificial general intelligence.”
Marcus: Deep learning alone won't solve common-sense AI without symbolic systems
“Deep learning doesn't seem to be getting us there. The old systems, in some ways, we're better at that. We do need a marriage between the two.”
Srivas: Cloudera and Hortonworks are disingenuous about their open source control
“I think that's a bit disingenuous on Hortonworks and Cloudrass part to say that Because they would like to, so the, here's the dirty little truth about open source software, open source vendors, right? I love open source as long as it's my open source and not …”
Falkowitz: Training employees to spot phishing attacks does not work
“So I'm gonna train all of you to spot phishing. That's not gonna work, right”
LeCun: Simulating biological brain neurons to achieve AI is 'completely nuts'
“There are people out there in Europe that, that have argued for the fact to kind of study neurons and neurons and neural networks natural neural networks in all the details, and then build giant supercomputers to simulate this very accurately, and somehow they…”
LeCun: Building chips for spiking neural networks is misguided
“The problem is, from the engineering point of view, nobody has actually demonstrated that spiking neurons actually work. Like there is no image recognition systems that are based on spiking neural networks. Why build chips for something we don't know works? So…”
Sumo Logic is 'taking down Splunk hard'
“So, you know, we have one competitor out there. I'll name them. They're called Splunk. So if you're familiar with Splunk, we're taking them down, and we're taking them down hard, and they know it.”
O'Neil: Data science is a war of moneyed interests against vulnerable people
“I think of data science as And the general modelization of everything in sight, including education, including getting a job insurance, health, it's a war. And we're losing. Like we are, this is a war of the people who have money and can go hire data scientist…”
Ping Li: Incumbent enterprise tech vendors haven't innovated in a decade
“It's such a great time to be a startup right now because the incumbents are so far behind. They have not innovated, ah, in the last decade. And any of the big data dimensions are the applications, storage, the data layers.”
Socher: Physical constraints will prevent an AI hard takeoff
“And as bullish and excited as I am about AI, I'm not a believer in this crazy hard takeoff. I think, yes, things will accelerate, but there are certain things that will just require time because of physics and constraints in the real world, such as like long-t…”
Greenblatt: Government pressure to cloister AI models internally is counterproductive
“I think that a bunch of likely government action at least seems to push in favor of AI companies keeping their models internal and not deploying them, which I think for the risks that I'm most worried about doesn't help and in fact is anti-helpful”
Greenblatt: Internal AI deployment within labs and government carries major risk
“There's a lot of risk from just internal deployment, especially if you're deploying within AI companies and government, right, which are two of the most high stakes Applications”
Wolf: Bostrom's Paperclip Maximizer Scenario Describes Real AI Incidents
“But definitely it seems like when Ballstrom worked about it in 2003, it seems a little bit like, you know, futuristic, definitely, and maybe something that was like a little bit crazy and just would not happen. But today, I mean, it's pretty clearly something …”
Wolf: Post-Training Mitigates Backdoor Risks in Open-Source AI Models
“Right now, if you pre-train and post-train a model for longer, you very likely change quite a lot of the weights and that it has. So I think there's a lot of way to circumvent that which means that at the moment I'm a bit less worried about that than maybe jus…”
Trojanowski: Enterprise agents need process reliability, not 'Move 37' breakthroughs
“And so the thing that you know, someone is buying from us is not, this will be the best ever tax return. They're buying that, you know, the confidence... They're buying that it's going to be consistent and reliable and something that they can trust that actual…”
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.”
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: 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.”
Kolter: Robotics AI is not yet ready for pure compute scaling
“Certain fields. I think things like robotics is still one. I don't think we're quite at the, let's just scale it up level with robotics yet. Some companies might argue we are. I don't think we are. I think we're still in the let's explore methods to find the r…”
Kolter: AI agent benefits outweigh security risks if deployed with proper guardrails
“Yes, I think so, actually. I think if you run with proper guardrails, you know, we release guardrails for coding agents, for example. If you're on proper guardrails with proper sandboxing, and right now, yes, you probably also take some care to be a little bit…”
Text model scaling is one of humanity's top scientific discoveries
“The discovery That when you train big enough models on lots of text, and then turn, and then a little bit of additional sort of, you know, fine-tuning text, and then turn them loose to generate, that this generates long-form coherent thought. That was probably…”
Evans: Anthropic momentum is fleeting as AI model leadership shifts weekly
“Not really. I mean, this week they've got all the fire, they've got all the juice, whatever the word is. I don't know. This week, next week, it'll be something else.”