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December 21, 2017

Top Big Data, AI, and HPC Quotes of 2017

It’s been a fascinating year in advanced scale computing, much of that fascination focused on AI (broadly defined), now firmly established as the leitmotif of the high performance computing sector. Another big theme of 2017: expanding commercial adoption of HPC-class technologies. The editorial staffs of the three Tabor publications (EnterpriseTechHPCwireDatanami) have assembled what we think are some of the most interesting quotes of the year touching on the most compelling, forward-looking issues.

AI Combined with Quantum
“There are problems you cannot solve, (not) today, you can’t solve them with Exascale.… If you could take every grain of sand on the planet earth and turn it into a digital computer, and if you could write software to parallelize them across those trillions and trillions of cores, it would still take millions of years to solve some problems. (These are ) problems that don’t lend themselves well to the normal laws of physics and numerical analysis …, with, relative speaking, an infinite number of variables. But in some cases, machine learning combined with quantum computing may be a way to solve problems that otherwise would never be solved with normal digital computing techniques.”
– Karl Freund, consulting lead HPC and deep learning, Moor Insights & Strategy

Multi-disciplinary AI and the “Emergent Property”
“At the level of ‘general intelligence’ (i.e., superintelligent AI), this is where I got really interested in ‘emergent properties.’ The scientific world has generally has accepted this… For example, social sciences cannot be explained by psychology fully; psychology cannot be fully explained by neuroscience; neuroscience cannot be fully explained by biology; biology cannot be completely explained by chemistry; chemistry not by physics. Because at each level of complexity something emerges when you combine them. … My thinking is: Can you combine all the different aspects of task-specific artificial intelligence? A superhuman poker player bot, (combined with) one that plays chess, one that drives cars, combine a hundred of them, a thousand of them, and put them together in a system, and somehow fuse the neural nets, all the different AI methods, and see if something new emerges based on emergent properties? And if it does, will it be like human?”
– Dr. Eng Lim Goh, vice president, HPE

AI Combined with HPC
“We think exascale isn’t going to look like today’s systems in terms of usages. It’s not just going to be simulation and modeling any more. It’s going to be simulation and modeling sitting alongside machine learning and AI, sitting alongside high performance data analytics. And not just the workloads coexisting but also interacting through workflows.”
– Jerry Lotto, director HPC and technical computing, Mellanox

Technology and the Market’s Hidden Hand
“I think we are (headed over a cliff) in many areas of technology policy, because we have none. We did that with social media. We invented a system where totalitarian governments can impose their will on societies, and it was like an offshoot of showing people ads. Most of our technology policies have no foresight, no planning. There’s this near-libertarian myth that somehow the market will do the right thing, rather than the near-term profitable thing. That’s a fundamental misunderstanding of markets, I think.”
– Bruce Schneier, security guru and author

HPC Proliferation
“There is an entirely new class of users who do not know they are using HPC. We call it ‘implicit HPC.’”
– Raj Hasrah, corporate VP and GM, Intel Corporation

“When someone says HPC it means something really specific to traditional HPC folks; it’s tightly coupled, we’ve got some sort of low latency interconnect, parallel file systems, designed to run high performance, highly scalable custom applications. But today, this has changed. HPC has come to mean pretty much any form of scientific computing and as a result, its breadth has grown in terms of what kind of applications we need to support.”
– Gregory Kurtzer, founder, Singularity (HPC container software)

AI Dystopia vs. Utopia
“…what’s going to happen is that robots will be able to do everything better than us… I mean all of us. I’m not sure exactly what to do about this. It’s really about the scariest problem to me. So I really think we need government regulation here ensuring the public good. You’ve got companies that have to race to build AI because they’re going to be made uncompetitive. If your competitor is racing to build AI and you don’t, they will crush you. So they’re saying, ‘We need to build it too….’ Transport will be one of the first things to go fully autonomous. But when I say everything, the robots will do everything, bar nothing.”
– Elon Musk

“I think people who are naysayers and kind of try to drum up these doomsday scenarios, it’s really negative and in some ways I actually think it’s pretty irresponsible. If you’re arguing against AI then you’re arguing against safer cars that aren’t going to have accidents, and you’re arguing against being able to better diagnose people when they’re sick.”
– Mark Zuckerberg

Hacking Our National Security
“Speed, the tempo of decision and information, is the problem because our adversaries have figured out how to move inside our military decision loop.”
– Pamela Melroy, former space shuttle commander and deputy director of DARPA’s Tactical Technology Office, in testimony before the National Space Council.

Simulating the Brain
“I think it’s impressive what statistics is capable of, but it’s definitely not what we’re looking for when it comes to human intelligence. You can’t simulate hundreds of billions of brain cells. You need to look for the principles, and I think we’re lagging in good principles. We are lagging in basic understanding of how the brain works. If we crack the brain code, I think we can build an artificial brain.”
– Pascal Kauffman, neuroscientist

AI Proliferation
“There’s rapid improvement in (machine learning) tools and the techniques. This is going from something for specialists only to rapidly entering the toolkit of data teams and analytics teams and software development teams more broadly. Not next year, but the barriers to entry are dropping as the tools get better.”
– David Schatsky, managing director, Deloitte

Hadoop & Happiness
“I can’t find a happy Hadoop customer. It’s sort of as simple as that. The number of customers who have actually successfully tamed Hadoop is probably less than 20 and it might be less than 10…That’s just nuts given how long that product, that technology, has been in the market and how much general industry energy has gone into it.”
– Bob Muglia, CEO, Snowflake Computing

Data Ownership
“It’s a property rights thing. Do you own your data? Or does Facebook own it? We say you own it. We’re saying data is property, and we believe in property rights. And the big companies that have exploited users’ data have no respect for property rights, in this regard.”
– Algebraix Data CEO Charlie Silver

The Algorithmic Genie
“We all think that we’re doing something with our algorithms, but we don’t always get what we asked for. Just like the people in the stories from One Thousand and One Nights, we don’t quite understand how to talk to our genies, how to ask them the right wish.”
– Tim O’Reilly, founder, O’Reilly Media

JSON and the Imagination
“The more I learned and thought about it, the more it seemed to me that JSON looked a little bit like tables. (But) you sort of have to squint.”
– SQL co-creator Don Chamberlin