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 26 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
Shazeer: Character.ai Rejects Product Managers Who Push for Vertical Specialization
“And like, you know, we talked to like some you know, potential product managers early on and they all say the same thing. Oh yeah. Pick your verticals, narrow it down to me, to make it usable. And like, no, we're not going to hire these people. That's like the…”
Noam Shazeer: Compute and Model Size Constrain AI Progress More Than Data
“Yeah, probably the size of the model is the bigger challenge. We can get a lot of data, but actually the number one thing that's important is how much computation you do to train it.”
Shazeer: Users Prefer Video Game Characters Over AI Psychologists for Therapy
“We put up as an example, like a psychologist character, like maybe, maybe you want to, you know, talk to something and feel better, you know, and you know, that gets a little bit of use, but then what we hear a lot more from users is like, I'm talking to a vid…”
Shazeer: Total Computation Is the Single Most Critical Factor in AI Training
“We can get a lot of, we can get a lot of data, but like, really, actually the number one thing that's important is how much computation you do to train it.”
Shazeer: AI Hardware Advances Will Enable Garage Developers to Match Big Tech
“The hardware is progressing so fast that what you could do at a big company, you know, one year, a few years later, you're going to be able to do You know, at the university lab or in your garage.”
Shazeer: Character.ai Views AI Model Hallucinations as a Feature, Not a Bug
“We consider them a feature or at least, okay, basically, our goal, you know, our strategy is, like, launch something general, let people do what they want with it, and if these models are hallucinating, which we, which they certainly are, and we advertise that…”
Shazeer: AI Research Is Currently Like Alchemy With Unknown Outcomes
“And I think a lot of that has to do with the fact that, you know, this field is kind of alchemy. Right now, like no one knows exactly what is going to work.”
Character.ai Spent $2 Million in Compute to Train Its Serving Model
“The model we're serving now, we trained last summer and spent about two million dollars worth of compute cycles doing it.”
Shazeer: Large Tech Companies Withhold AI Launches Due to Brand Risk
“In the past things seem You know, potentially too much brand risk at larger companies to like actually launch and get it out there.”
Shazeer: Users Report Character.ai Helps Them Practice for Social Situations
“We've gotten testimonials of people who said that they were uncomfortable, you know, talking to other people, and, like, this is great practice. This is actually helped them build up practice in either social situations.”
Shazeer: Open and Closed AI Ecosystems Will Continue to Coexist
“As there has been, there will be a big ecosystem of open and closed of, you know, People who aren't sharing their secret sauce with, and people who are sharing all of their secret sauce and the ability to mess around with things at a small scale is going to le…”
Shazeer: Deep Learning Succeeds Because Hardware Is Optimized for Dense Matrix Multiplication
“The reason this whole field is working so well is because Now we have this magic hardware that's great at these dense matrix multiplications. And so you can do them like orders of magnitude faster than you can do anything that involves poking around in memory.”
Shazeer: Launch General-Purpose Technology Directly to Billions of Consumers
“If you have a technology that is, like, really, really general and has billions of use cases and, like, ordinary people can use, like, launch it to billions of people.”
Shazeer: B2C Products Proved Far Larger Than B2B Enterprise Search at Google
“I remember when I joined Google, there were, like, a lot of people working on this enterprise search appliance, which, you know, it was okay. Like, I think maybe somebody had this conventional wisdom that, like B to B is the only way to make money. But, like, …”
Shazeer: Full-Stack AI Co-Design Across Every Layer Is Hugely Powerful
“And then it also lets you do all this co-design of like, you get to affect every part of the stack, which is, you know, which is hugely powerful and fun.”
Shazeer: Developing AI Provides Greater Leverage Than Direct Medical Research
“So rather than directly working on say medical research or something I think I've got a lot more leverage, like let's push AI technology and then, you know, that can help with a lot of the rest of it.”
Shazeer: Character.ai's Mission Is a Billion Users Inventing a Billion Use Cases
“I like this, sort of motto of, you know, a billion users inventing a billion use cases, because that, that's sort of the superpower of this technology.”
Shazeer: Better Next-Word Prediction Directly Increases AI Model Intelligence
“And then if you can do it well, then This thing can just talk to you. It can be, you know, the better you do it, the smarter it gets. It's hugely, hugely general and useful, super simple to state.”
Shazeer: Impressive Language Models Existed Unreleased in Labs by 2020
“I'd say around 2020 was when sort of, like, really impressive stuff was sort of in the lab, but not launched.”
Shazeer: Character.ai Spent $2 Million in Compute to Train Its Model
“So you know, the model we're serving now, we train Last summer and spent about two million dollars worth of compute cycles doing it.”
Shazeer: Task-Specific Fine-Tuning Dramatically Improves Generally Pre-Trained AI Models
“The data that you get from users is great because It tells people like what, you know, what users like or like what users like in, in some particular application. It's kind of like a, you know, training a human. Like most of what's important is like you have y…”
Shazeer: Naively Training Models on Raw Chat Logs Risks Leaking User Privacy
“It's very important because, like, you know, if you just were to do the naive thing of take, like, every conversation you had with everyone and just train on it, then You could just be, like, spitting out, like, someone's private, you know, private life to, yo…”
Shazeer: Centralized AI Inference Batching Is Up to 100x More Efficient
“Obviously though, there's also like economics of scale of both training the best models And serving, like if you want to serve a product, you can do it maybe a hundred times more efficiently if you're serving many, many people at once and kind of batching thin…”
Shazeer: The Best AI Applications Have Not Been Invented Yet
“The best applications just haven't even been invented yet that You know, we, you know, we're still at, like invention of electricity kind of moment, or invention of the computer, where we don't really you know, we don't really know what the coolest things are …”
Shazeer: Neural Networks Were Rebranded as Deep Learning Due to Hardware Limits
“Neural networks had a bad name cause the hardware wasn't good enough.”
Shazeer: Parenthood Made Me More Religious and Shifted Focus to Meaningful Work
“A lot of things about parenthood are absolutely terrific and super fun, but I think it made me more, more religious. I decided to take a change of attitude from, like, what is fun right now to I should be Thankful for having the opportunity, you know, to do so…”