A RULE OF THUMB THAT UNSCRAMBLES THE BRAIN

October 6, 2000

SCIENCE & ENGINEERING NEWS

New York, N.Y. — Sandra Blakeslee reports that a new breed of animal, dubbed the “sand mouse,” has been added to the annals of biological science, and it has become the subject of a scientific challenge.

Last week Dr. John J. Hopfield, a Princeton professor known for seminal discoveries in computer science, biology and physics, posed an unusual test to his fellow scientists.

Dr. Hopfield challenged them to discover a simple, new computational principle – a general rule of thumb – for how the brain of this creature works, using only the power of deductive reasoning and a set of facts about the animal that Dr. Hopfield and a former student, Dr. Carlos Brody, have posted on a Web site ( http://shadrach.cns.nyu.edu/ ~carlos/Organism/ ).

Dr. Hopfield said enough information was given about the animal so that any scientist who was willing to “think really deeply about the system” could discover the principle independently.

While the exercise describes the animal in realistic terms, including experiments to anesthetize it and take electrical recordings from its brain, the creature is actually a simulation composed of 660 artificial cells that behave exactly like real brain cells. That is, in computer calculations the cells fire signals at certain rates, connect in conventional ways, squirt out familiar chemicals and behave just like real brain cells do.

Moreover, the simulations show that these ordinary cells have acquired the ability to recognize the word “one” spoken by many different voices under noisy conditions – something that the human brain can do with ease but machines still cannot.

The new computational principle, says Dr. Hopfield, explains how the animal, called mus silicium or sand mouse, accomplishes this task. Dr. Hopfield boldly claims that the new principle may shed light on how the human brain works. Using the Web site, scientists can even do their own experiments with the sand mouse, according to the authors.

Those who take up the challenge have until Dec. 1 either to explain how the sand mouse recognizes the word “one” or to take the same number of neurons and use the new principle to make the mouse acquire a novel behavior, Dr. Hopfield said. Cash prizes will be awarded.

A paper revealing the new principle will be published on Dec. 14. Thus far, only Dr. Hopfield and Dr. Brody, a postdoctoral fellow at the Center for Neural Science at New York University, have figured out the answer.

In telephone interviews, each coyly said that scientists would not be disappointed by the discovery.

Asked why he did not just publish his findings in a scientific journal now, Dr. Hopfield said, “I could have, but I think it’s time to open a discussion on the role of deductive reasoning in neurobiology.”

The challenge in any complex problem is to figure out what is or is not relevant, he said. Because that is hard to do, neuroscientists tend to keep on collecting data or to hypothesize that there are as yet undiscovered cell properties that, once found, will solve the problem, rather than thinking hard about what they already know.

“Data gathering is getting out of hand,” Dr. Hopfield said. The challenge is to get scientists to start thinking deductively based on what is already known, he said.

“Very few scientists could pull this off,” said Dr. Christof Koch, a neuroscientist at the California Institute of Technology. “But John Hopfield is a leader in neural computation. His playful challenge is wonderful. Scientists love to compete. I think he’ll get a big response.”

Dr. Zachary Mainen, an assistant professor at Cold Spring Harbor Laboratory, in New York, who has seen the challenge, said: “Whether it’s a stunt or a lesson is going to depend on how the answer plays out. It has certainly sparked a bit of discussion.”

Because Dr. Hopfield has not published a paper in the normal way, it is not possible to judge the significance of his discovery, said Dr. Terrence J. Sejnowski, a neuroscientist at the Salk Institute in San Diego, Calif.

“But he has another goal in mind, namely an advertising gimmick,” Dr. Sejnowski said. “How can you get someone to read your paper? You offer a prize. A lot more people will pay attention to it this way. But it’s also a good object lesson to ask experimentalists to go beneath their data and develop a theoretical understanding of what they’re doing.”

While the brain is nothing like a digital computer, much of what it does can be described as computation, Dr. Brody said.

Associating two memories, commanding muscles to move or identifying odors are all computations in which nerve cells play the role of the on-off switches in computers.

To mimic, and perhaps understand, these behaviors, scientists build computer models of networks of brain cells, known as neural networks, using computational principles inspired by real brains.

For example, real cells add up arriving signals until they reach some threshold and then fire – a principle that can be described mathematically.

Dr. Hopfield said that he was particularly interested in the kinds of computations that occurred over time. The brain deals with a world that is constantly in motion, he said. “You see a friend walking toward you from 50 yards away,” Dr. Hopfield said. “If he’s standing still you might not recognize him but if he’s moving, you know who it is from the way he walks. Or touch a piece of velvet. You may not know what it is until you run your fingers across it.”

Such percepts require a few tenths of a second for the brain to recognize them, Dr. Hopfield said. The brain is constantly integrating information over time, but science does not know how that feat is done. To study the problem, Dr. Hopfield taught his neural network (the sand mouse) a spoken word, “one.”

Language also unfolds over time, he said. Words can be broken down into small units that have no inherent meaning, but when these units are held and combined over fractions of a second or more they become comprehensible.

It was in thinking deeply about how the brain did this that “the penny dropped,” as Dr. Hopfield put it.

Suddenly, Dr. Hopfield realized that the brain – or at least the sand mouse brain – uses a “novel, simple, powerful, plausible” computational principle for dealing with time delays.

He said the finding was not immediately applicable to speech recognition devices, which now surpass what the sand mouse can do. Rather, it sheds light on how a nervous system manipulates information over time, speech being one such problem.

Last spring, Dr. Hopfield dared Dr. Brody to discover the principle using the same challenge that is now on the Web site.

“I had to use a way of thinking that felt very different from what I normally use,” Dr. Brody said. “I never would have thought I had been given enough information, but it turned out that the data were enough to guide me ineluctably to the right answer.”

============================================================

Subscribe to HPCwire's Weekly Update!

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

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion XL — were added to the benchmark suite as MLPerf continues Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing power it brings to artificial intelligence.  Nvidia's DGX Read more…

Call for Participation in Workshop on Potential NSF CISE Quantum Initiative

March 26, 2024

Editor’s Note: Next month there will be a workshop to discuss what a quantum initiative led by NSF’s Computer, Information Science and Engineering (CISE) directorate could entail. The details are posted below in a Ca Read more…

Waseda U. Researchers Reports New Quantum Algorithm for Speeding Optimization

March 25, 2024

Optimization problems cover a wide range of applications and are often cited as good candidates for quantum computing. However, the execution time for constrained combinatorial optimization applications on quantum device Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at the network layer threatens to make bigger and brawnier pro Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HBM3E memory as well as the the ability to train 1 trillion pa Read more…

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing po Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HB Read more…

Nvidia Looks to Accelerate GenAI Adoption with NIM

March 19, 2024

Today at the GPU Technology Conference, Nvidia launched a new offering aimed at helping customers quickly deploy their generative AI applications in a secure, s Read more…

The Generative AI Future Is Now, Nvidia’s Huang Says

March 19, 2024

We are in the early days of a transformative shift in how business gets done thanks to the advent of generative AI, according to Nvidia CEO and cofounder Jensen Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, codenamed Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. Wh Read more…

Alibaba Shuts Down its Quantum Computing Effort

November 30, 2023

In case you missed it, China’s e-commerce giant Alibaba has shut down its quantum computing research effort. It’s not entirely clear what drove the change. Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia Read more…

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Leading Solution Providers

Contributors

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

Shutterstock 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

Google Introduces ‘Hypercomputer’ to Its AI Infrastructure

December 11, 2023

Google ran out of monikers to describe its new AI system released on December 7. Supercomputer perhaps wasn't an apt description, so it settled on Hypercomputer Read more…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E Read more…

Intel Won’t Have a Xeon Max Chip with New Emerald Rapids CPU

December 14, 2023

As expected, Intel officially announced its 5th generation Xeon server chips codenamed Emerald Rapids at an event in New York City, where the focus was really o Read more…

IBM Quantum Summit: Two New QPUs, Upgraded Qiskit, 10-year Roadmap and More

December 4, 2023

IBM kicks off its annual Quantum Summit today and will announce a broad range of advances including its much-anticipated 1121-qubit Condor QPU, a smaller 133-qu Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire