Big Data

“I think that Those are the buzzwords today that, like, blockchain was a year ago, and that big data was a year ago.”

“We are the opposite. We talk about little data. We want to go find that one thing that's going to drive success or failure and bring a lot to bear on that one thing, and that is where we spend all of our time.”

“Most companies do not in fact have like big data. Perhaps there are a few companies like in genomics or like astrophysics that like actually have, you know, Petabytes of data, but like most data sets are not that big.”

“Now, some people will say, well, big data will solve this. We use artificial intelligence and we'll crunch and we'll see patterns and trends. And to a degree that will be of help. But I don't think it will be the panacea. I think there will still be too much n…”

“Ultimately it's all the same thing. It's all the same trend, which is basically turning companies from sort of like analog companies that run on, you know, sending Excel spreadsheets around with a lot of manual processes into companies that are intelligent and…”

“There we think just the increasing use of big data and data analytics to predict consumer demand and actually reduce the amount of inventory will be a more powerful force than the fact that there were shortages in certain areas.”

“I think that people have sort of rushed ahead, and maybe not always thought very carefully about what happens when you build an algorithm, or when you build something based on data, and just expect humans to fit in around it. And I think that that actually has…”

“This is a seven hundred and fifty billion dollar market where there's 125 different managers where there's about a thousand deals with 3000 different underlines. So this has gone from something that you can do yourself to big data.”

“Everybody's so crazy about big data and that people are ignoring the details associated with the human psychology and how people react. And that small data usually is the pathway to some huge market opportunities.”

“So the convergence of, I'd say mathematical foundations and statistical machine learning tools, the big data and the hardware is created this historical moment of AI.”

“I think the really interesting thing about insurance is it's the first big data problem.”

“I sort of define big data as it's a mindset. It's about being really fast about using data to make decisions. So it's not just about petabytes of data. It's about, you know, how fast can you leverage data to create business outcomes and so that mindset is what…”

“In big data, to me, the fundamental breakthrough is providing information from multiple places and producing insights where the data finds the data.”

“If you look at big data is not a siloed application. It gets infused through the organization. So it's usually part of some operational business process. And it's really hard to lift and shift it into the cloud.”

“I believe that Application aware big data is sort of the next driver in this space, and we'll get, we will get an application layer that will become very intelligent as a result of this underlying big data.”

“So my favorite example of this is the phrase big data. So a year and a half ago, if you use the phrase big data in a tech job listing, it was positive. You know, it was seen as compelling and cutting edge. In June of 2015, it's not negative, but it's totally n…”

“You can answer questions, right? Answer those what if questions? What happens if, you know, a disease is released in this crowd? What happens if we shut down this tube station? Questions which governments and companies want to answer, but which, you know, you …”

“So it turns out the reason for big data is machine learning.”

“So I like something that Peter Norvig, the director of research at Google said when he referred to big data, he says, big data is not just quantitatively different, but it's qualitatively different. In other words, there's something that happens when you have …”

“And the way I think about big data is when machines learn from big data is very much like human beings learn from life experiences.”

“You can think of business intelligence going forward as the ability to apply machine learning algorithms to big data, and not just look at past questions, but also future questions, or asking to predict the unknowns from the knowns.”

“Venture capital has not been affected at all by this approach, you know, big data approach.”

“Those guardrails were overly restrictive relative to where we felt we could really both source and invest intelligently and to achieve the returns that we were shooting for.”

“But I think it's just now it's so ingrained in pretty much every single thing that you look at or I look at, it's kind of doesn't mean anything anymore.”

“Most of the things that are sort of big data are actually not that big. You know, you would like to, you'd like to think of these petabytes and exabytes floating around there and coming up with really amazing insights that could never have been seen. But a lot…”

“AI today is a little bit like that kind of big data trend everyone talked about in 2005 and six, where it's changing the world in a bunch of different ways that I'll detail in a moment. But it's not really living up to, I think, all the hype, and that's probab…”

“We're building lots of software, hoping it works, and we're not really thinking about the harder intellectual issues at play.”

“As every company is becoming a technology company there's an ever increasing amount of data that's available to them that can be analyzed. So there's an opportunity to develop a very powerful data-driven culture and be much smarter about one's business. And Th…”

“I think that we actually just entering truly interesting part of big data. I think everything so far, and it's been years in the making, has been about the early stage of creation of tools, of creation of companies, startups, of experimentation, and we're just…”

“So eventually the industry will presumably consolidate. Every industry at some point consolidates. But my sense is that it's not happening anytime soon. It's certainly not at scale.”

“AI from my perspective is very much a child of big data.”

“Deep learning for the most part was really developed by some, you know, particularly forward-thinking researchers like, you know, you have a con, Jeff Hinton, that, that, that group, and it's really only up until recently when those algorithms intersected with…”

“The, you know, the quote-unquote big data thing Turns out to have produced a number of very valuable technologies, not that many valuable businesses and part of it is because the data on its own, as everybody knows, is, you know, it's just information.”

“And to me it feels like, Big data. Maybe six or seven years ago where companies were real waking up and realizing we have all these data assets. We need to do something with them. And that led to the rise of Hadoop and the Hadoop vendors and then, you know, a …”

“And I have a three-part diagnosis, which is that it's fallen in love with statistics, it's fallen in love with big data, and it's forgotten its roots.”

“It's also a huge maintenance problem. So, a lot of customers we talk to don't want to, you know, forget about the network performance or the CPU computation, right? It's just a management overhead of now there are two copies of something as logically the same.”

“When I think of sharing, I think of the GitHub model, right, where it's not, here's your final published product, but here is, clone it, fork it, and this is how I derive at those insights, so other people can learn from those insights, and that's really impor…”

“I think big data is a big buzzword from big company to make big money.”

“Unlike the data sets arising in physics, the data sets that typically fall under the big data umbrella are about people, Their attributes, their actions, and their interactions. That is to say these are social data sets that document people's lives, behaviors …”

“The issue is granularity. In other words, not only do these data sets document social phenomena, they do so at the granularity of individual people and their second-to-second activities.”

“When it comes to addressing issues like bias, fairness, and inclusion, perhaps we should instead be focusing our attention on the granular nature of big data.”

“Ultimately, the big data game will be won by those who know how to ask and answer interesting questions.”

“And honestly, to me, this whole hype will all be real and make sense if, in five, 10 years from now, There is, like, C-level execs, more like me, who are, who actually own the data function, own the science function, and if that actually happens, then this who…”

“Aster was one of the first companies that you, that we used it as our major positioning statement, and I do believe we had the first big data event. Although I may be wrong, but nobody has, ah, nobody has, ah, told me otherwise so far.”

“We use Big Data a lot less because Big Data has lost a lot of the benefit it had for us back in 2009.”

“I actually do not believe in big data. I believe in small data.”

“What in big data what's happening is, the machine is automating the cognitive functions that people perform, right?”

“Big data is a twenty-year secular trend.”

“And three, I think that big data is a very interesting opportunity for us, for the, ah, New York tech community to really build an engineering culture in this city, ah, which hasn't been the case so far, but for reasons I'll discuss.”

“I think that the, I think the advantage that big data is going to give to companies is going to be temporary. I think it's going to be evolving towards being, ah, something like, ah, like what zero stock was to manufacturing a few years ago where, you know, at…”

“Well, I think that big data is our opportunity as a community to catch up quite a bit and becoming a very strong engineering place, and there's essentially, you know, several reasons for that.”