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.

clear all ✕

why aren't all 11 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

Prediction Not checkable as stated
Hoffman: A data breach will put a data company out of business
“And of course, keeping that data secure is, is a huge issue, and you're going to build a security team, run penetration tests, you know, or of course you're going to be out of business if you have some sort of breach.”
Auren Hoffman Nov 20, 2017 ▶ 4:48 Where Should Machines Go to Learn? // Auren Hoffman, SafeGraph (FirstMark's Data Driven)
Assertion Not checkable as stated
Hoffman: Google has location data on 70% of US mobile phones
“Companies like Google have great access to this data because they have 70% of the phones in the U.S. That they have data on, and probably even a higher percentage of phones worldwide that they get to see all this great location data on.”
Auren Hoffman Nov 20, 2017 ▶ 12:51 Where Should Machines Go to Learn? // Auren Hoffman, SafeGraph (FirstMark's Data Driven)
Prediction Not checkable as stated
Hoffman: Nutrition tech will see little progress over the next 20 years
“On the flip side, if you think about nutrition, likely, 20 years from now, we'll still have fad diets. Just be, it's just incredibly difficult to collect all the data of, you know, everything that goes into your body, you know, your eventual outcome, which cou…”
Auren Hoffman Nov 20, 2017 ▶ 15:55 Where Should Machines Go to Learn? // Auren Hoffman, SafeGraph (FirstMark's Data Driven)
Prediction Not checkable as stated
Hoffman: China may lead in healthcare machine learning due to data regulations
“And so we could see, it's very possible we could see more machine learning innovations, or at least in certain areas, Like maybe in healthcare, for instance. We might see more machine learning innovations that happen in China than happen in, in other places.”
Auren Hoffman Nov 20, 2017 ▶ 21:25 Where Should Machines Go to Learn? // Auren Hoffman, SafeGraph (FirstMark's Data Driven)
Assertion Not checkable as stated
Hoffman: Machine learning engineers spend up to 99% of time organizing data
“So now, you know, you have these great machine learning engineers, and they thought they were going to be spending You know, all their time predicting the future, but it turns out they're spending 95 to 99% of their time organizing the past.”
Auren Hoffman Nov 20, 2017 ▶ 4:07 Where Should Machines Go to Learn? // Auren Hoffman, SafeGraph (FirstMark's Data Driven)
Assertion Not checkable as stated
Hoffman: Google ML engineers spend 95% of their time building models
“As a machine learning engineer, now you can spend 95% of your time predicting the future, which is what you want to do as a machine learning engineer.”
Auren Hoffman Nov 20, 2017 ▶ 5:24 Where Should Machines Go to Learn? // Auren Hoffman, SafeGraph (FirstMark's Data Driven)
Assertion Not checkable as stated
Hoffman: Compute power access prices have dropped every single month
“And the price, because of things like containers, et cetera, the price of access and compute power has gone down every single month.”
Auren Hoffman Nov 20, 2017 ▶ 9:57 Where Should Machines Go to Learn? // Auren Hoffman, SafeGraph (FirstMark's Data Driven)
Assertion Not checkable as stated
Hoffman: Internal data represents under 0.01% of global data for most companies
“Most companies out there, their own data represents, like, point oh one percent of the world. It's, unless you're Google, Facebook, Amazon, Tencent, a couple of others, you have a very small sliver of what's happening in the world.”
Auren Hoffman Nov 20, 2017 ▶ 11:57 Where Should Machines Go to Learn? // Auren Hoffman, SafeGraph (FirstMark's Data Driven)
Prediction Not checkable as stated
Hoffman: Oncology will see huge innovation in the next 20 years
“So the probably oncology is a place where we'll probably will see some innovation because there's a defined data set. There's, there are definitely some vendors today that have access to really good oncology data. So I expect that we'll see a lot of really gre…”
Auren Hoffman Nov 20, 2017 ▶ 15:31 Where Should Machines Go to Learn? // Auren Hoffman, SafeGraph (FirstMark's Data Driven)
Prediction Held up
Hoffman: Privacy-preserving data querying solutions will emerge by 2022
“But I expect within the next five years, we'll probably have answers to some of those problems.”
Auren Hoffman Nov 20, 2017 ▶ 18:44 Where Should Machines Go to Learn? // Auren Hoffman, SafeGraph (FirstMark's Data Driven)
Assertion Partly supported
Hoffman: SafeGraph has 120 investors
“We've got we have a 120 investors in our company.”
Auren Hoffman Nov 20, 2017 ▶ 19:35 Where Should Machines Go to Learn? // Auren Hoffman, SafeGraph (FirstMark's Data Driven)
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