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!

Musk’s Latest Startup Eyes Brain-Computer Links

April 21, 2017

Elon Musk, the auto and space entrepreneur and severe critic of artificial intelligence, is forming a new venture that reportedly will seek to develop an interface between the human brain and computers. Read more…

By George Leopold

MIT Mathematician Spins Up 220,000-Core Google Compute Cluster

April 21, 2017

On Thursday, Google announced that MIT math professor and computational number theorist Andrew V. Sutherland had set a record for the largest Google Compute Engine (GCE) job. Sutherland ran the massive mathematics workload on 220,000 GCE cores using preemptible virtual machine instances. Read more…

By Tiffany Trader

Nvidia P100 Shows 1.3-2.3x Speedup Over K80 GPU on Financial Apps

April 20, 2017

When it comes to the true performance of the latest silicon, every end user knows that the best processor is the one that works best for their application. Read more…

By Tiffany Trader

Quantum Adds Global Smarts to StorNext File System

April 20, 2017

Companies that use Quantum’s StorNext platform to store massive amounts of data this week got a glimpse of new storage capabilities that should make it easier to access their data horde from anywhere in the world. Read more…

By Alex Woodie

HPE Extreme Performance Solutions

HPC-Driven Weather Simulations Improving Forecasting Capabilities

In September of 1938, a massive hurricane traversed the Atlantic Ocean and made landfall in New England. Due to inadequate and incorrect forecasting, the storm struck farther north and with greater intensity than had been predicted, leaving residents and authorities with virtually no warning or time to properly prepare. Read more…

Scaling an HPC Career in Nepal Can Be a Steep Climb

April 20, 2017

Umesh Upadhyaya works as an IT Associate at the International Centre for Integrated Mountain Development (ICIMOD) in Nepal, which supports the country’s one and only HPC facility. He is directly involved in an initiative that focuses on climate change and atmosphere modeling Read more…

By Nages Sieslack

Hyperion (IDC) Paints a Bullish Picture of HPC Future

April 20, 2017

Hyperion Research – formerly IDC’s HPC group – yesterday painted a fascinating and complicated portrait of the HPC community’s health and prospects at the HPC User Forum held in Albuquerque, NM. HPC sales are up and growing ($22 billion, all HPC segments, 2016). Read more…

By John Russell

Intel Open Sources All Lustre Work, Brent Gorda Exits

April 19, 2017

In a letter to the Lustre community posted on the Intel website, Vice President of Intel's Data Center Group Trish Damkroger writes that effective immediately the company will be contributing all Lustre development to the open source community. Damkroger also announced that Brent Gorda, General Manager, High Performance Data Division at Intel is leaving the company. Read more…

By Tiffany Trader

Facebook Open Sources Caffe2; Nvidia, Intel Rush to Optimize

April 18, 2017

From its F8 developer conference in San Jose, Calif., today, Facebook announced Caffe2, a new open-source, cross-platform framework for deep learning. Caffe2 is the successor to Caffe, the deep learning framework developed by Berkeley AI Research and community contributors. Read more…

By Tiffany Trader

Hyperion (IDC) Paints a Bullish Picture of HPC Future

April 20, 2017

Hyperion Research – formerly IDC’s HPC group – yesterday painted a fascinating and complicated portrait of the HPC community’s health and prospects at the HPC User Forum held in Albuquerque, NM. HPC sales are up and growing ($22 billion, all HPC segments, 2016). Read more…

By John Russell

Knights Landing Processor with Omni-Path Makes Cloud Debut

April 18, 2017

HPC cloud specialist Rescale is partnering with Intel and HPC resource provider R Systems to offer first-ever cloud access to Xeon Phi "Knights Landing" processors. The infrastructure is based on the 68-core Intel Knights Landing processor with integrated Omni-Path fabric (the 7250F Xeon Phi). Read more…

By Tiffany Trader

CERN openlab Explores New CPU/FPGA Processing Solutions

April 14, 2017

Through a CERN openlab project known as the ‘High-Throughput Computing Collaboration,’ researchers are investigating the use of various Intel technologies in data filtering and data acquisition systems. Read more…

By Linda Barney

DOE Supercomputer Achieves Record 45-Qubit Quantum Simulation

April 13, 2017

In order to simulate larger and larger quantum systems and usher in an age of “quantum supremacy,” researchers are stretching the limits of today’s most advanced supercomputers. Read more…

By Tiffany Trader

Penguin Takes a Run at the Big Cloud Providers

April 12, 2017

HPC specialist Penguin Computing recently re-ran benchmarks from a study of its larger brethren and says the results show its ‘public cloud’ – Penguin on Demand (POD) – is among the leaders in cost and performance. Read more…

By John Russell

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

HPC and the Colocation Datacenter – a Bridge Too Far?

April 7, 2017

A more standardised HPC platform approach is making the running of HPC projects within increasing financial reach. Read more…

By Clive Longbottom, Quocirca

Google Pulls Back the Covers on Its First Machine Learning Chip

April 6, 2017

This week Google released a report detailing the design and performance characteristics of the Tensor Processing Unit (TPU), its custom ASIC for the inference phase of neural networks (NN). Read more…

By Tiffany Trader

Google Pulls Back the Covers on Its First Machine Learning Chip

April 6, 2017

This week Google released a report detailing the design and performance characteristics of the Tensor Processing Unit (TPU), its custom ASIC for the inference phase of neural networks (NN). Read more…

By Tiffany Trader

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Read more…

By John Russell

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the campaign. Read more…

By John Russell

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its assets. Read more…

By Tiffany Trader

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

For IBM/OpenPOWER: Success in 2017 = (Volume) Sales

January 11, 2017

To a large degree IBM and the OpenPOWER Foundation have done what they said they would – assembling a substantial and growing ecosystem and bringing Power-based products to market, all in about three years. Read more…

By John Russell

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

In this contributed perspective piece, Intel’s Jim Jeffers makes the case that CPU-based visualization is now widely adopted and as such is no longer a contrarian view, but is rather an exascale requirement. Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

Leading Solution Providers

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

IBM Wants to be “Red Hat” of Deep Learning

January 26, 2017

IBM today announced the addition of TensorFlow and Chainer deep learning frameworks to its PowerAI suite of deep learning tools, which already includes popular offerings such as Caffe, Theano, and Torch. Read more…

By John Russell

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling was pretty much the exclusive realm of the Cray-2 and IBM mainframe class products. That’s changing. We are now seeing an emergence of x86 class server products with exotic plumbing technology ranging from Direct-to-Chip to servers and storage completely immersed in a dielectric fluid. Read more…

By Steve Campbell

BioTeam’s Berman Charts 2017 HPC Trends in Life Sciences

January 4, 2017

Twenty years ago high performance computing was nearly absent from life sciences. Today it’s used throughout life sciences and biomedical research. Genomics and the data deluge from modern lab instruments are the main drivers, but so is the longer-term desire to perform predictive simulation in support of Precision Medicine (PM). There’s even a specialized life sciences supercomputer, ‘Anton’ from D.E. Shaw Research, and the Pittsburgh Supercomputing Center is standing up its second Anton 2 and actively soliciting project proposals. There’s a lot going on. Read more…

By John Russell

HPC Startup Advances Auto-Parallelization’s Promise

January 23, 2017

The shift from single core to multicore hardware has made finding parallelism in codes more important than ever, but that hasn’t made the task of parallel programming any easier. Read more…

By Tiffany Trader

HPC Technique Propels Deep Learning at Scale

February 21, 2017

Researchers from Baidu’s Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural network training and now they are sharing their implementation with the larger deep learning community. Read more…

By Tiffany Trader

US Supercomputing Leaders Tackle the China Question

March 15, 2017

Joint DOE-NSA report responds to the increased global pressures impacting the competitiveness of U.S. supercomputing. Read more…

By Tiffany Trader

IDG to Be Bought by Chinese Investors; IDC to Spin Out HPC Group

January 19, 2017

US-based publishing and investment firm International Data Group, Inc. (IDG) will be acquired by a pair of Chinese investors, China Oceanwide Holdings Group Co., Ltd. Read more…

By Tiffany Trader

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