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 15 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 1 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
Maples: High-Priced Seed Deals Like Character.ai Won't Return 100x
“Expensive, high-priced investment, and hopefully it works, but you're not going to make a thousand times your money on that deal. You're probably not going to make a hundred times your money, even in the best of circumstances.”
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…”
a16z paid growth prices for early-stage Character.AI to back Noam Shazeer
“My partner, Sarah led around a character AI and, you know, it was extremely early stage and, You know, we invested at a, you know, what you would call a gross stage price. But we knew that the likelihood of some degree of success in backing Nome was extremely …”
Lazarte: Character AI is merely the Friendster of AI companions
“In a few years, we're going to look back, and we're going to say that Character AI was Friendster. And what I mean by that is there's going to be a company that is going to be very important, and we'll look back and we'll say Character AI was the precursor of …”
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: 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…”
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: 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.”
Mostaque: Character.AI Sees Two Hours of Engagement Per Session
“Character AI has something like two hours a day of engagement per session”
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: 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: 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: 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: 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…”