Europe wants to have one exascale supercomputer by 2023

On March 23rd, in Rome, seven European countries signed a joint declaration on High Performance Computing (HPC), committing to an initiative that aims at securing the required budget and developing the technologies necessary to acquire and deploy two exascale supercomputers, in Europe, by 2023. Other Member States will be encouraged to join this initiative.

Exascale computers, defined as machines that execute 10 to the 18th power operations per second will be roughly 10 times more powerful than the existing fastest supercomputer, the Sunway TaihuLight, which clocks in at 93 petaflop/s, or 93 times 10 to the 15 floating point operations per second. No country in Europe has, at the moment, any machine among the 10 most powerful in the world. The declaration, and related documents, do not fully specify that these machines will clock at more than one exaflop/s, given that the requirements for supercomputers are changing with the technology, and floating point operations per second may not be the right measure.

This renewed interest of European countries in High Performance Computing highlights the fact that this technology plays a significant role in the economic competitiveness of research and development. Machines with these characteristics are used mainly in complex system simulations, in physics, chemistry, materials, fluid dynamics, but they are also useful in storing and processing the large amounts of data required to create intelligent systems, namely by using deep learning.

Andrus Ansip, European Commission Vice-President for the Digital Single Market remarked that: “High-performance computing is moving towards its next frontier – more than 100 times faster than the fastest machines currently available in Europe. But not all EU countries have the capacity to build and maintain such infrastructure, or to develop such technologies on their own. If we stay dependent on others for this critical resource, then we risk getting technologically ‘locked’, delayed or deprived of strategic know-how. Europe needs integrated world-class capability in supercomputing to be ahead in the global race. Today’s declaration is a great step forward. I encourage even more EU countries to engage in this ambitious endeavour”.

The European Commission press release includes additional information on the next steps that will be taken in the process.

Photo of the signature event, by the European Commission. In the photo, from left to right, the signatories: Mark Bressers (Netherlands), Thierry Mandon (France), Etienne Schneider (Luxembourg), Andrus Ansip (European Commission), Valeria Fedeli (Italy), Manuel Heitor (Portugal), Carmen Vela (Spain) and Herbert Zeisel (Germany).

 

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Intel buys Mobileye by $15 billion

Mobileye, a company that develops computer vision and sensor fusion technology for autonomous and computer assisted driving, has been bought by Intel, in a deal worth 15.3 billion dollars.

The company develops a large range of technologies and services related with computer based driving. These technologies include rear facing and front facing cameras, sensor fusions, and high-definition mapping. Mobileye has been working with a number of car manufacturers, including Audi and BMW.

Mobileye already sells devices that you install in your car, to monitor the road and warn the driver of impeding risks. A number of insurance companies in Israel have reduced the insurance premium for drivers who have installed the devices in their cars.

This sale is another strong indication that autonomous and computer assisted driving will be a mature technology within the next decade, changing profoundly our relation with cars and driving.

The products of Mobileye have been extensively covered in the news recently, including TechCrunchThe New York Times and Forbes.

Image by Ranbar, available at Wikimedia Commons.

IBM TrueNorth neuromorphic chip does deep learning

In a recent article, published in the Proceedings of the National Academy of Sciences, IBM researchers demonstrated that the TrueNorth chip, designed to perform neuromorphic computing, can be trained using deep learning algorithms.

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The TrueNorth chip was designed to efficiently simulate the efficient modeling of spiking neural networks, a model for neurons that closely mimics the way biological neurons work. Spiking neural networks are based on the integrate and fire model, inspired on the fact that actual neurons integrate the incoming ion currents caused by synaptic firing and generate an output spike only when sufficient synaptic excitation has been accumulated. Spiking neural network models tend to be less efficient than more abstract models of neurons, which simply compute the real valued output directly from the values of the real valued inputs multiplied by the input weights.

As IEEE Spectrum explains: “Instead of firing every cycle, the neurons in spiking neural networks must gradually build up their potential before they fire. To achieve precision on deep-learning tasks, spiking neural networks typically have to go through multiple cycles to see how the results average out. That effectively slows down the overall computation on tasks such as image recognition or language processing.

In the article just published, IBM researchers have adapted deep learning algorithms to run on their TrueNorth architecture, and have achieved comparable precision, with lower energy dissipation. This research raises the prospect that energy-efficient neuromorphic chips may be competitive in deep learning tasks.

Image from Wikimedia Commons

Writing a Human Genome from scratch: the Genome Project-write

The Genome Project-write has released a white paper, with a clear proposal of the steps and timeline that will be required to design and assemble a human genome from scratch.

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The project is a large scale project, involving a significant number of institutions, and many well-known researchers, including George Church and Jef Boeke. According to the project web page:

“Writing DNA is the future of science and medicine, and holds the promise of pulling us forward into a better future. While reading DNA code has continued to advance, our capability to write DNA code remains limited, which in turn restricts our ability to understand and manipulate biological systems. GP-write will enable scientists to move beyond observation to action, and facilitate the use of biological engineering to address many of the global problems facing humanity.”

The idea is to use existing technologies for DNA synthesis to accelerate research in a wide spectrum of life-sciences. The synthesis of human genomes may make it possible to understand the phenotypic results of specific genome sequences and will contribute to improve the quality of synthetic biology tools.

Special attention will be paid to the complex ethical, legal and social issues that are a consequence of the project.

The project has received wide coverage, in a number of news sources, including popular science sites such as Statnews and the journal Science.

Computers will always follow instructions. That may be the problem…

Many pessimistic scenarios about machines taking control of the world and harming humans are based on the idea that computers will eventually develop self-consciousness and define their own goals, incompatible with the goals of humanity. This is the basis of the argument of many science-fiction movies and books.

Many people believe, however, that this will not be the main problem. As reported in many news outlets, the University of California at Berkeley (my alma matter) has launched the Center for Human-Compatible Artificial Intelligence. The center will be headed by Stuart Russell, a famous expert in Artificial Intelligence (and  co-author, with Peter Norvig, of the most used textbook in the field, Artificial Intelligence: A Modern Approach). Russell has been a vocal advocate for incorporating human values into the design of AI, in order to avoid the pitfall that may come from AI systems running amok.

According to Stuart Russell, the issue is “that machines as we currently design them in fields like AI, robotics, control theory and operations research take the objectives that we humans give them very literally“. Therefore, they may approach tasks with an objective that is simply too literal. For instance, if instructed to solve the problem of “global warming”, a machine may decide that the most effective way is to wipe out the human race.

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According to the UC Berkeley press release, the center is being launched with a grant of $5.5 million from the Open Philanthropy Project, with additional grants from the Leverhulme Trust and the Future of Life Institute.

The center will work on mechanisms to guarantee that the AI systems of the future will act, by design, in a way that is aligned with human values. According to Stuart Russell, “AI systems must remain under human control, with suitable constraints on behavior, despite capabilities that may eventually exceed our own. This means we need cast-iron formal proofs, not just good intentions.

Image credits: UC Berkeley. The image illustrates BRETT, the Berkeley Robot for the Elimination of Tedious Tasks, tieing a knot after watching others demonstrate it.

Is there life out there?

As reported in an article in the journal Nature, Proxima Centauri (pictured), the star nearest to our sun, has an Earth sized planet, orbiting the “Goldilocks” zone (not too hot, not too cold).

The recently discovered planet orbits the mother star in 11 days, an orbit much smaller and much closer to its sun than the orbit of the Earth. However, since Proxima Centauri is a red dwarf, it is much cooler than our sun, which makes this orbit to be just the right size. The planet, named Proxima Centauri b, weights between 1.3 and 3 times the Earth, which makes it likely that it may be a rocky planet. The distance to the star makes it possible that it may exhibit liquid water.

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This combination of factors makes it the planet most likely to help us obtain additional information about the possible existence of life outside of Earth. Earth based instruments, such as the European Southern Observatory, ESO, an array of telescopes in the Atacama desert, in Chile, will be able to obtain additional information.

ESO was involved in the discovery of Proxima Centauri b, and likely to play an important role in the discovery of further information about this planet that, in astronomical terms, lies tantalising close to Earth, at “only” 4.2 light-years. Sending a spacecraft out to that planet may also be a possibility, albeit a very challenging one.

The challenges involved in obtaining further information about this planet are significant, but not unsurmountable, as the Economist reports. In a few years, we may have some better answers to Fermi’s famous question, “Where are they?”, referring to the possibility of extra-terrestrial life.

 

A new map of the human brain


More than one hundred years ago, the German anatomist Korbinian Brodmann undertook a systematic analysis of the microscopic features of the brain cortex of humans (and several other species) and was able to create a detailed map of the cortex. Brodmann 52 areas  (illustrated below) are still used today to refer to specific regions of the cortex.

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Despite the fact that he numbered brain cortex areas based mostly on the cellular composition of the tissues observed by microscope, there is remarkable correlation between specific Brodmann areas and specific functions in the cortex. For instance, area 17 is the primary visual cortex, while area 4 is the primary motor cortex.

This week, an article in Nature proposes a new map of the human cortex, much more detailed than the one developed by Brodmann. In this new map, each hemisphere of the cortex is subdivided into 180 regions.

A team led by Mathew Glasser used multiple types of imaging data collected from more than two hundred adults participants in the Human Connectome Project. The information included a number of different measurements including cortical thickness, brain function, connectivity between regions, and topographic organization of cells in brain tissue, among others.The following video, made available by Nature, gives an idea of the process followed by the researchers and the results obtained.

Image by Mark Dow, available at Wikimedia Commons.