A Quote by Hilary Mason
It turns out it's important to build a product and not just a bunch of data models.
Related Quotes
Deep learning allows you to create predictive models at a level of quality and sophistication that was previously out of reach. And so deep learning also enhances the product function of data science because it can generate new product opportunities.
Simple models and a lot of data trump more elaborate models based on less data.
Data is the fabric of the modern world: just like we walk down pavements, so we trace routes through data, and build knowledge and products out of it.
Turns out, people's brains are not nearly as powerful a motivator as our hearts. Facts, data, and economic models don't move people to courageous action the way that powerful stories can.
The paradigm shift of the ImageNet thinking is that while a lot of people are paying attention to models, let's pay attention to data. Data will redefine how we think about models.
I was interested in data mining, which means analyzing large amounts of data, discovering patterns and trends. At the same time, Larry started downloading the Web, which turns out to be the most interesting data you can possibly mine.
Fashion data was used to build AI models to help Steve Bannon build his insurgency and build the alt-right. We used weaponized algorithms. We used weaponized cultural narratives to undermine people and undermine the perception of reality. And fashion played a big part in that.
While the creative works from the 16th century can still be accessed and used by others, the data in some software programs from the 1990s is already inaccessible. Once a company that produces a certain product goes out of business, it has no simple way to uncover how its product encoded data. The code is thus lost, and the software is inaccessible. Knowledge has been destroyed.
A lot of people seem to think that data science is just a process of adding up a bunch of data and looking at the results, but that's actually not at all what the process is.
My study is NOT as a climatologist, but from a completely different perspective in
which I am an expert … For decades, as a professional experimental test engineer, I have analyzed experimental data and watched others massage and present data. I became a cynic; My conclusion - 'if someone is aggressively selling a technical product who's merits are dependent on complex experimental data, he is likely lying'. That is true whether the product is an airplane or a Carbon Credit.
The bigger a data set that you have, the more polls, the more surveys that you have that people undertake, the more accurate your models are going to be. That's just a fact of data science.
The only basis for even talking about global warming is the predictions spewed out by computer models. The only quote/unquote "evidence" of global warming is what models are predicting the climate and the weather will be in the next 50 to 100 years. Now, what those models spit out is only as good as the data that's put in, and it's an absolute joke. In terms of science, it's a total joke. There is no warming, global or otherwise!
It turns out that is exactly what product strategy is all about—figuring out the right product is the innovator’s job, not the customer’s job.
My job is to analyze our data set to understand it and build products on it. I look at raw data, do the math to clean it up, and build systems to make it easy to understand.
Go out and collect data and, instead of having the answer, just look at the data and see if the data tells you anything. When we're allowed to do this with companies, it's almost magical.
Removed from 'Gmail' doesn't necessarily mean removed from all Google servers. In fact, your old emails are the data set from which Google models our behaviors - the real product it is offering its advertisers.
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