Hilary Mason
16 statements across 2 episodes · 4 bullish · 3 bearish · 1 people on the record · first statement Dec 5, 2013 by Hilary Mason · said 9 times in 7 episodes since 2013 · across every show →
On the record as a speaker too: Hilary Mason's record, appearances and statements → this page counts the times other people say the name.
Mentions by year
brought up most by Matt Turck (4), John Foreman (2), Gilad Lotan (1), Chris Moody (1), Adam Laiacano (1)
tap a year for its mentions
2013 9 mentions in 7 episodes 1 per episode
- John Foreman, Mailchimp // Data Driven NYC 19 // October 2013
- Matt Turck, Bloomberg Ventures // Data Driven NYC# 3 // Feb 2012
- Joe Lonsdale, Formation 8 // Fireside Chat at Data Driven NYC #20 (Hosted by FirstMark Capital)
- Adam Laiacano, Tumblr // Data Driven NYC 20 // Nov 2013 (Hosted by FirstMark Capital)
- Gilad Lotan, Betaworks // Data Driven NYC 20 // Nov 2013
- Mike Dauber, Battery Ventures // Data Driven NYC 19 // October 2013 (interviewed by Matt Turck)
- Chris Moody, Gnip // Data Driven NYC #3 // Feb 2012
- every mention in 2013, scene by scene →
Everything said about Hilary Mason, oldest first
Dec 5, 2013
Mason: Forcing teams to admit informal error metrics motivates analytical rigor
“And if there are no error metrics that we are planning to use initially you know, we might be working on something like a recommendation algorithm. And the error metric for the first version is, it looks good to me. You at least have to admit that in public, i…”
Dec 5, 2013 positive
Mason balances data teams with one predictable and one speculative project
“And in terms of the day-to-day management, I'd like to make sure everyone who I work with has both, you know, one sort of longer-term, more well-understood problem, and then one problem they can work on when they're really excited, ah, that's a little bit, as …”
Dec 5, 2013
Dec 5, 2013
Hilary Mason: Data analysts should investigate areas where intuition fails
“Generally, look for places where intuition fails. That is, ah, your company, your product, your data, you should have a good sense of what you would expect. And yet, when you see something in it that doesn't meet your expectations, ah, that's probably an indic…”
Dec 5, 2013 negative
Hilary Mason: Separating R&D from product rarely works for tech companies
“I have seen companies that successfully separate, ah, research and development as long as everyone still eats lunch together but generally that doesn't seem to be a great approach in that you eventually end up with a research department off in the corner publi…”
Dec 5, 2013
Mason: Asking how an evil dictator would use product sparks creative ideas
“So if you ask this question, like, if we put this thing in the hands of an evil dictator, ah, what would they do with it? Ah, it's a way to get people to sort of brainstorm and come up with crazy ideas for it, some of which might actually be good.”
Dec 5, 2013
Mason: Data projects must prove immediate relevance to business goals
“Assuming we can solve this perfectly, what is the first thing we'll do with it that makes sure it has immediate relevance to the product, or the business, or the system you're building? Because there are a lot of super cool ideas that do not tie directly to th…”
Dec 5, 2013 positive
Mason: Relying on peers for data hurts efficiency; build self-serve dashboards
“Whenever somebody has to ask someone else for a piece of information to get their job done, it really makes everybody much less effective. So if you see people asking for the same kinds of information, there should be dashboards or a way that they can access i…”
Dec 5, 2013
Dec 5, 2013 negative
Hilary Mason: Startups must understand how their machine learning models work
“Won't speak for the large companies or people who are working on very specific problems, but when you're generally building systems that in a startup environment, it's really important to understand why your system is doing the thing it's doing, or else it's g…”
Dec 8, 2016
Mason: Building generic ML products is harder than solving single enterprise problems
“When somebody, when a vendor or a startup is going to build a product that solves your problem, They must solve a generic formulation of the problem. They have to solve everybody's version of your same problem. When you want to solve your problem, you just nee…”
Dec 8, 2016
Mason: Publications reflect past research, while informal chats reveal future ideas
“And so I really believe if you want to know what someone did a year ago, you read their publication, and if you want to know what they're doing now, you watch them give a talk like this, and if you want to know the sort of wacky ideas they're thinking about, y…”
Dec 8, 2016 bullish
Dec 8, 2016 positive
Dec 8, 2016 negative
Mason: Sentiment analysis remains fundamentally unsolved due to lacking ground truth
“I think there are a couple of things that everyone thinks are solved problems that are absolutely not, and so something like sentiment analysis is something where we sort of take for granted that you can just plug into an API and get a number back, but this is…”