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 23 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
Hoffman: Silicon Valley's major blind spot is focusing strictly on software
“We have our kind of blind spots, and a classic one for us tends to be well, everything should be done in See us. Everything should be done in software. Everything should be done in bits.”
Hoffman: Predictive AI for drug discovery only needs 1% accuracy
“Simply doing prediction and getting that prediction right, and by the way, it doesn't have to be right a hundred percent of time, it has to be right, like, one percent of the time, because you can validate the other 99% were it right, and then finding that one…”
Hoffman: Pure AI simulation will not solve drug discovery
“Silicon Valley will classically go, we'll put it all in simulation and that will solve it. Nope, that's not going to work.”
Hoffman: AI models are better diagnostic knowledge stores than humans
“And so the diagnostic capabilities, these are much better knowledge stores than any human being on the planet.”
Hoffman: In 10 to 20 years, doctors won't be human knowledge stores
“I actually think there will be a position for a doctor, 10 years from now, 20 years from now. It won't be as the knowledge store. It will be as a user of an, as an expert user of the knowledge store, but it's not gonna be, oh, because I went to med school for …”
Hoffman: AI agency and goal-setting capabilities are almost certain
“I think agency and goals is almost certain. There is a question. I think this is one of the areas where we want to have some clarity and control. That was a little bit like the kind of question of what kind of compute fabric holds it together because you can't…”
Hoffman: AI will be net super positive for climate change
“They obsess about the climate change stuff, because actually, in fact, if you apply intelligence at the scale and availability of electricity, you're going to help climate change. You're going to solve grids and appliances and a bunch of other stuff. And just …”
Hoffman: Silicon Valley Ethos Prioritizes Product Innovation Over Early Business Models
“This is actually one of the things that I think people don't realize about Silicon Valley. You start with, what's the amazing thing that you can suddenly create? Lots of these companies, you go, what's your business model? You go, I don't know. You're like, ye…”
Hoffman: Professionals not finding serious AI uses aren't trying hard enough
“If you haven't found a use of AI that helps you on something serious today, not just write a sonnet for your kid's birthday or, you know, I've got these ingredients in my fridge, what should I make? Do those too. But if you haven't for something like work, for…”
Hoffman: Using AI to generate startup due diligence plans saves a day
“When we get decks, we put them in and say, give me a due diligence plan, right? If not everybody here doing that, that's a mistake. Cause you, five minutes, you get one and you go, oh no, not two, not five. Oh, but three is good. And it would have taken me a d…”
Hoffman: AI does not need consciousness to reason or set goals
“I don't think you need consciousness for goal setting or reasoning.”
Hoffman: AI startups cannot sustain exponential costs without revenue
“You can't have an exponentiating cost curve without at least a following revenue curve.”
Hoffman: AI companions can be great companions, but not true friends
“And you're going to see all kinds of nutty people saying, oh, I have your AI friend right here. It's like, No, you don't. It's not a bi-directional relation. Maybe awesome companion, like just spectacular, but it's not a friend.”
Hoffman: 'Seven deadly sins' consumer framework still applies to AI
“The seven deadly stins still work because that's a question of what is infrastructure, psychological infrastructure across all eight billion plus human beings.”
Hoffman: Humans are better defined as Homo Techne than Homo Sapiens
“Cause of the classic classification of human beings is homo sapiens. I actually think we're homo techne because it's that iteration through technology.”
Hoffman: Microsoft's long-term AI agent experiments get trapped in polite loops
“So Microsoft has had running for years now, agents talking to each other long form, like, just like, let's go for a year and do that and see what happens. And so often they get into like, oh, thank you. No, thank you. No, thank you. One month later. Thank you.…”
Hoffman: Today's AI models are the worst you will ever use
“The worst AI you're ever going to use is the AI you're using today.”
Hoffman: Future AI will combine LLMs and diffusion models via unified fabric
“But the thing that people on track is it's going to be LMS and diffusion models. And I think other things with a fabric across them.”
Hoffman: Google achieved 40% data center energy savings using AI
“Google applied its algorithms to its own data centers, which are some of the best tuned grid systems in the world. 40% energy savings.”
Hoffman: LinkedIn remains hard to disrupt due to difficult network dynamics
“And so I think the reason why it's been difficult to create a disruptor to LinkedIn is it's a very hard network to build. It's actually not easy. And by staying really true to it, you end up getting a lot of people going, well, this is where I am for that. And…”
Hoffman: PayPal almost went bankrupt from exponential free volume costs
“At PayPal we had to change to, like, we, as you know, because you were close to us there, like, we had to change to a paid model because we're like, oh, look, we have exponentiating volume, which means exponentiating cost curve, which means despite having rais…”