The Rise of the Thinking Machine

By Michael Feldman

August 25, 2011

This year has seen some notable advancements in computer-based brain mimicry, not just on the artificial intelligence (AI) front, but also related to in silico brain simulations.

Watson’s vanquishing of Jeopardy champions Brad Rutter and Ken Jennings in February set the stage for the year.  The now world-famous IBM super exhibited a sophisticated understanding of language semantics along with the ability to integrate that understanding into a complex analytics engine.  Since the Jeopardy match, IBM has been looking to take the technology into the commercial realm, most notably in the health care arena. 

Meanwhile projects like FACETS (Fast Analog Computing with Emergent Transient States) and SpiNNaker are working to uncover the nature of the brain at the level of the neuron.  The goal here is not to create any kind of artificial intelligence system a la Watson, but rather to simulate the neuronal network of the brain for basic science research.

SpiNNaker, a multi-year project run out of the UK at the University of Manchester, also is attempting to map the brain’s low-level biological structure and function. In June, the project received its first batch of custom-built ARM processors that will eventually power a 50 thousand-node neural network supercomputer.

The FACETS project, managed by the University of Heidelberg, actually wrapped up last year. It’s sequel, BrainScaleS project booted up in January 2011, with the idea of developing of a “brain-inspired computer architecture” based on a custom-designed neural network hardware.  BrainScaleS has links to Henry Markram’s famous Blue Brain work.

Blue Brain, based at the École Polytechnique Fédérale in Lausanne (EPFL), is perhaps the best-known of the brain mimicry projects. The idea is to perform detailed simulations of the brain at the scale of the neuronal network.  In this case though, the work was done with conventional supercomputing hardware (if you can call Blue Gene conventional). The project has successfully simulated a rat cortical column.

The follow-on to Blue Brain, also headed by Markram, is the Human Brain Project. The goal here is to move from rats to human and simulate the entire brain.

The other bookend to the Watson AI story is also from IBM. Last week, the company unveiled their cognitive computing chips.  This is basic research as well, but IBM is aiming the technology at developing thinking machines, rather than just using it to elucidate the workings of the brain.

I queried Markram about the significance to IBM’s latest chippery, who responded thusly: “This is a very important technology step. There are still many challenges ahead, but neuromorphic chips like IBM’s are bound to become key processing units in hybrid architectures of future computers.”  He also recognized the work at FACETS/BrainScaleS and SpiNNaker as contributing to this growing body of knowledge.

So what does it all mean?  For those of you who read about such development in the popular press, there has been plenty of speculation about the future of artificial brains.  A lot of this is centered around how such technology will impact the human condition, particular how intelligent computers will displace human labor.

The big question is if such technology will ultimately benefit people or merely make them superfluous.  Edward Tenner,  a historian of technology and culture with a Ph.d in European history, believes it will be the former.  From a piece he penned in The Atlantic:

 
Will people be obsolete? I doubt it. The economic theory of comparative advantage explains why. Assuming there will still be people, even if the computers are running everything, it will pay for them to let people do what they are relatively better at. There’s likely to be a higher opportunity cost for computers to do more intuitive analysis for which human brain-body system has evolved and concentrate on tasks at which their abilities are an even high-multiple than people’s. In the case of computers and people, as I suggested about IBM’s Watson and Jeopardy! there will always be elements of tacit knowledge and common sense that will be extremely expensive to achieve electronically.

His premise is that it will always be cheaper and more effective to have a real live human provide answers that involve intuition.  “So even if, for example, computers surpass physicians on diagnostic reasoning,” he writes, “it will be cheaper, more effective, and safer to have their judgment double-checked by a real doctor.

Maybe.  But I think one of the article’s commenters nailed it pretty well when he suggests that the real question is not whether computers will replace all labor, but how many jobs will be displaced by intelligent machines and how that impacts our traditional economic model.  He writes:

In classical economics, employers furnish the capital, and workers produce raw materials and finished goods or services.  There is tension between worker and management: both need each other, but both want a bigger piece of the profits from work; each has a strong bargaining position, and the compromise they reach determines wages and benefits.  But what’s playing out on the world stage isn’t classical economics at all.  With every passing year, owners of capital are relying less on workers and more on machines.  The balance has shifted in favor of owners of capital.

We don’t have to wait for the future to see this play out.  It’s been happening for decades, as businesses large and small have adopted IT.  The commenter notes that multinational tech manufacture Foxconn will be shedding a million of its million and half workers manufacturing circuit boards over the next two years, thanks to assembly line robotics.

We’ve certainly seen similar downsizing across the manufacturing sector in general. A century ago, the same process happened in agriculture, a sector whose labor base continues to decline.  It’s not that the industries are shrinking, just their labor force.

With the introduction of more sophisticated computing,  machines are moving higher up the food chain. For example, over the last three decades at JP Morgan, profitability has risen by a factor of 30, but employee head count has only doubled. That’s directly attributable to computer technology raising productivity.

The advent of really intelligent machines like Watson and its neuromorphic brethren will accelerate all this, in ways we can only imagine.  Even industries that are enjoying relatively rapid job growth today, like professional services, education, and health care, will eventually be impacted.

From my perspective, the key problem is that our social and economic systems are not ready for this.  While everyone is fixated on globalization, I think that’s a side show compared to what will happen — and is happening — as intelligent technology displaces human labor worldwide.

It’s not just that people who have invested years of specialized training will find their jobs threatened.  As the commenter noted above, the balance between capital and labor is shifting rapidly in favor of capital as the labor force is squeezed into fewer and fewer jobs that resist automation.  The hope is that other industries will emerge to engage the masses again, as happened after the agricultural and industrial revolutions.  But this time may be different.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

New Exascale System for Earth Simulation Introduced

April 23, 2018

After four years of development, the Energy Exascale Earth System Model (E3SM) will be unveiled today and released to the broader scientific community this month. The E3SM project is supported by the Department of Energy Read more…

By Staff

RSC Reports 500Tflops, Hot Water Cooled System Deployed at JINR

April 18, 2018

RSC, developer of supercomputers and advanced HPC systems based in Russia, today reported deployment of “the world's first 100% ‘hot water’ liquid cooled supercomputer” at Joint Institute for Nuclear Research (JI Read more…

By Staff

New Device Spots Quantum Particle ‘Fingerprint’

April 18, 2018

Majorana particles have been observed by university researchers employing a device consisting of layers of magnetic insulators on a superconducting material. The advance opens the door to controlling the elusive particle Read more…

By George Leopold

HPE Extreme Performance Solutions

Hybrid HPC is Speeding Time to Insight and Revolutionizing Medicine

High performance computing (HPC) is a key driver of success in many verticals today, and health and life science industries are extensively leveraging these capabilities. Read more…

Cray Rolls Out AMD-Based CS500; More to Follow?

April 18, 2018

Cray was the latest OEM to bring AMD back into the fold with introduction today of a CS500 option based on AMD’s Epyc processor line. The move follows Cray’s introduction of an ARM-based system (XC-50) last November. Read more…

By John Russell

Cray Rolls Out AMD-Based CS500; More to Follow?

April 18, 2018

Cray was the latest OEM to bring AMD back into the fold with introduction today of a CS500 option based on AMD’s Epyc processor line. The move follows Cray’ Read more…

By John Russell

IBM: Software Ecosystem for OpenPOWER is Ready for Prime Time

April 16, 2018

With key pieces of the IBM/OpenPOWER versus Intel/x86 gambit settling into place – e.g., the arrival of Power9 chips and Power9-based systems, hyperscaler sup Read more…

By John Russell

US Plans $1.8 Billion Spend on DOE Exascale Supercomputing

April 11, 2018

On Monday, the United States Department of Energy announced its intention to procure up to three exascale supercomputers at a cost of up to $1.8 billion with th Read more…

By Tiffany Trader

Cloud-Readiness and Looking Beyond Application Scaling

April 11, 2018

There are two aspects to consider when determining if an application is suitable for running in the cloud. The first, which we will discuss here under the title Read more…

By Chris Downing

Transitioning from Big Data to Discovery: Data Management as a Keystone Analytics Strategy

April 9, 2018

The past 10-15 years has seen a stark rise in the density, size, and diversity of scientific data being generated in every scientific discipline in the world. Key among the sciences has been the explosion of laboratory technologies that generate large amounts of data in life-sciences and healthcare research. Large amounts of data are now being stored in very large storage name spaces, with little to no organization and a general unease about how to approach analyzing it. Read more…

By Ari Berman, BioTeam, Inc.

IBM Expands Quantum Computing Network

April 5, 2018

IBM is positioning itself as a first mover in establishing the era of commercial quantum computing. The company believes in order for quantum to work, taming qu Read more…

By Tiffany Trader

FY18 Budget & CORAL-2 – Exascale USA Continues to Move Ahead

April 2, 2018

It was not pretty. However, despite some twists and turns, the federal government’s Fiscal Year 2018 (FY18) budget is complete and ended with some very positi Read more…

By Alex R. Larzelere

Nvidia Ups Hardware Game with 16-GPU DGX-2 Server and 18-Port NVSwitch

March 27, 2018

Nvidia unveiled a raft of new products from its annual technology conference in San Jose today, and despite not offering up a new chip architecture, there were still a few surprises in store for HPC hardware aficionados. Read more…

By Tiffany Trader

Inventor Claims to Have Solved Floating Point Error Problem

January 17, 2018

"The decades-old floating point error problem has been solved," proclaims a press release from inventor Alan Jorgensen. The computer scientist has filed for and Read more…

By Tiffany Trader

Researchers Measure Impact of ‘Meltdown’ and ‘Spectre’ Patches on HPC Workloads

January 17, 2018

Computer scientists from the Center for Computational Research, State University of New York (SUNY), University at Buffalo have examined the effect of Meltdown Read more…

By Tiffany Trader

Russian Nuclear Engineers Caught Cryptomining on Lab Supercomputer

February 12, 2018

Nuclear scientists working at the All-Russian Research Institute of Experimental Physics (RFNC-VNIIEF) have been arrested for using lab supercomputing resources to mine crypto-currency, according to a report in Russia’s Interfax News Agency. Read more…

By Tiffany Trader

How the Cloud Is Falling Short for HPC

March 15, 2018

The last couple of years have seen cloud computing gradually build some legitimacy within the HPC world, but still the HPC industry lies far behind enterprise I Read more…

By Chris Downing

Chip Flaws ‘Meltdown’ and ‘Spectre’ Loom Large

January 4, 2018

The HPC and wider tech community have been abuzz this week over the discovery of critical design flaws that impact virtually all contemporary microprocessors. T Read more…

By Tiffany Trader

How Meltdown and Spectre Patches Will Affect HPC Workloads

January 10, 2018

There have been claims that the fixes for the Meltdown and Spectre security vulnerabilities, named the KPTI (aka KAISER) patches, are going to affect applicatio Read more…

By Rosemary Francis

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Fast Forward: Five HPC Predictions for 2018

December 21, 2017

What’s on your list of high (and low) lights for 2017? Volta 100’s arrival on the heels of the P100? Appearance, albeit late in the year, of IBM’s Power9? Read more…

By John Russell

Leading Solution Providers

Deep Learning at 15 PFlops Enables Training for Extreme Weather Identification at Scale

March 19, 2018

Petaflop per second deep learning training performance on the NERSC (National Energy Research Scientific Computing Center) Cori supercomputer has given climate Read more…

By Rob Farber

Lenovo Unveils Warm Water Cooled ThinkSystem SD650 in Rampup to LRZ Install

February 22, 2018

This week Lenovo took the wraps off the ThinkSystem SD650 high-density server with third-generation direct water cooling technology developed in tandem with par Read more…

By Tiffany Trader

AI Cloud Competition Heats Up: Google’s TPUs, Amazon Building AI Chip

February 12, 2018

Competition in the white hot AI (and public cloud) market pits Google against Amazon this week, with Google offering AI hardware on its cloud platform intended Read more…

By Doug Black

HPC and AI – Two Communities Same Future

January 25, 2018

According to Al Gara (Intel Fellow, Data Center Group), high performance computing and artificial intelligence will increasingly intertwine as we transition to Read more…

By Rob Farber

New Blueprint for Converging HPC, Big Data

January 18, 2018

After five annual workshops on Big Data and Extreme-Scale Computing (BDEC), a group of international HPC heavyweights including Jack Dongarra (University of Te Read more…

By John Russell

US Plans $1.8 Billion Spend on DOE Exascale Supercomputing

April 11, 2018

On Monday, the United States Department of Energy announced its intention to procure up to three exascale supercomputers at a cost of up to $1.8 billion with th Read more…

By Tiffany Trader

Momentum Builds for US Exascale

January 9, 2018

2018 looks to be a great year for the U.S. exascale program. The last several months of 2017 revealed a number of important developments that help put the U.S. Read more…

By Alex R. Larzelere

Google Chases Quantum Supremacy with 72-Qubit Processor

March 7, 2018

Google pulled ahead of the pack this week in the race toward "quantum supremacy," with the introduction of a new 72-qubit quantum processor called Bristlecone. Read more…

By Tiffany Trader

  • arrow
  • Click Here for More Headlines
  • arrow
Share This