The Ledger
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Big tech companies, not startups, will drive machine learning innovations
“I think we're gonna probably be seeing innovations from those types of companies, ah, before startups.”
Data analytics startups will eventually dislodge incumbents like SAS
“I do think that the incumbent players like SAS I mean, I think over time will hopefully be dislodged by, you know, some number of startups.”
Kleiner Perkins' largest investment check ever was into Twitter
“The largest check that the KP's ever written was in the Twitter.”
Cheap storage causes enterprise and consumer companies to suffer from data obesity
“The cost and ability to store tons of data is, is so prevalent both in consumer and enterprise companies that I think oftentimes you end up in this kind of data obesity state where you start storing data for reasons you don't even know why you're storing it.”
Large enterprise companies will eventually move production workloads onto Hadoop
“I think it will happen.”
Kaggle competition winners rely primarily on feature engineering and algorithm ensembles
“If you look at, you know, who wins most of the Kaggle competitions, it tends to be, you know, combinations of ensembles of different algorithms, but it's really the feature engineering.”
US government intelligence agencies were using big data software in 2004
“We had three-letter agencies using our software 10 years ago, like, plus, and they certainly had more than big data, so it's not new.”
Differentiating big data startups purely on data visualization is getting difficult
“It just feels like between D three and other tools, that that area, it's getting more difficult to differentiate just on visualization. You have to have other pieces.”
Data science will always require specialized professionals with strong statistics backgrounds
“I think there's always going to be a need for someone who has a background in statistics and can understand how to use tools to understand what are the questions that should be asked, how to do the feature engineering, to understand your business, whether it b…”
Big data startups greatly underestimate the requirements for enterprise readiness
“I think that in general, I try to determine does this team have a strong enough understanding of what it's like to sell to the Fortune 2000 or 5000 to know what it means to be enterprise ready? I think that oftentimes, ah, companies greatly underestimate that.”
Kleiner Perkins passes on founders who cannot justify their tech stack choices
“And I'm not saying that the decisions that that company made were wrong, necessarily, but I think that at the end of the day, technology is here to solve a problem, and if you don't know why you selected a particular, For particular, particular technology, I t…”
Most data growth to 40 zettabytes by 2020 will originate from sensors
“If you look at the, you know, the forecasts that are going from the 2.8 zettabytes to 40 zettabytes in 2020 that's, most of that data is gonna be coming from sensors, right?”
Companies mine consumer property data to identify B2B lead generation opportunities
“Insurance, you know, homes, there's all this, like, if you look at the statistics of, okay, marriage is oftentimes nine months past that, like, you know, different regions of the country, you could also predict maybe when they go buy a home, and so actually, l…”