In 2008, the journalist Jonah Lehrer paid a visit to a lab in Lausanne, Switzerland, to profile Henry Markram, a world-renowned neuroscientist. Markram, a South African, had trained at a series of élite institutions in Israel, the United States, and Germany; in the nineties, he published foundational papers on neural connections and synaptic activity. Markram's work in the laboratory, which involved piercing neural membranes with what Lehrer described as an "invisibly sharp glass pipette," was known for its painstaking precision. Lehrer's visit, however, had been occasioned not by Markram's incremental contributions to the field--it's not easy to sell a colorful profile on the basis of such publications as "The neural code between neocortical pyramidal neurons depends on neurotransmitter release probability"--but by Markram's pivot, in the early two-thousands, to brain simulation. Neuroscience, Markram declaimed to Lehrer, had reached an impasse. Researchers had generated an enormous wealth of fine-grained data, but the marginal returns had begun to diminish.

In fact, a few years earlier, Henry Markram, a neuroscientist at the École Polytechnique Fédérale de Lausanne in Switzerland, had set an even loftier goal: to make a computer simulation of a living human brain. Markram wanted to build a fully digital, three-dimensional model at the resolution of the individual cell, tracing all of those cells' many connections. "We can do it within 10 years," he boasted during a 2009 TED talk. In January 2013, a few months before the American project was announced, the EU awarded Markram $1.3 billion to build his brain model. The US and EU projects sparked similar large-scale research efforts in countries including Japan, Australia, Canada, China, South Korea, and Israel.

In the summer of 2009, the Israeli neuroscientist Henry Markram strode onto the TED stage in Oxford, England, and made an immodest proposal: Within a decade, he said, he and his colleagues would build a complete simulation of the human brain inside a supercomputer. They'd already spent years mapping the cells in the neocortex, the supposed seat of thought and perception. "It's a bit like going and cataloging a piece of the rain forest," Markram explained. "How many trees does it have? What shapes are the trees?"

In the summer of 2009, the Israeli neuroscientist Henry Markram endeavored onto the TED stage in Oxford, England, and introduced an immodest proposal: he and his colleagues would develop a full human brain simulation inside a supercomputer within a decade. They had been mapping the cells in the neocortex, the supposed seat of thought and perception, for years already. "It's a bit like going and cataloging one piece of rainforest," explained Markram. "How many trees it has? What features are the trees? "His team would now establish a virtual Silicon rainforest from which they hoped artificial intelligence would evolve organically.

In the summer of 2009, the Israeli neuroscientist Henry Markram strode onto the TED stage in Oxford, England, and made an immodest proposal: Within a decade, he said, he and his colleagues would build a complete simulation of the human brain inside a supercomputer. They'd already spent years mapping the cells in the neocortex, the supposed seat of thought and perception. "It's a bit like going and cataloging a piece of the rain forest," Markram explained. "How many trees does it have? What shapes are the trees?"

Artificial Intelligence Review Assistant -- into Frontiers' digital peer-review platform enables better, more efficient quality control and manuscript handling Frontiers peer review now incorporates powerful AI technology to safeguard both manuscript and peer-review quality more efficiently and keep pace with ever-growing submissions. AIRA assists editors, reviewers and internal teams by analyzing, interpreting and communicating the quality of submitted manuscripts and the review process, as well as suggesting actions and identifying potential reviewers. Built in-house and fully integrated into the Frontiers Review Forum and internal workflows, these groundbreaking capabilities have already streamlined Frontiers' publishing process -- and will continually drive further optimization through ongoing learning and inclusion of new quality checks. "AIRA is the next generation of peer review, in which Artificial Intelligence and machine learning enable fast, rigorous and efficient peer review at ever-larger scales," says Frontiers CEO and Co-Founder Kamila Markram. "The technology does not replace people -- to the contrary, it empowers people to take editorial decisions in a more effective way, by helping our editors, reviewers and internal teams to focus on the right things and take critical decisions at the right time. This speeds up the review process and reduces time to publication, while ensuring the highest quality control."

Kathryn Hess can't tell the difference between a coffee mug and a bagel. Hess, a researcher at the Swiss Federal Institute of Technology, is one of the world's leading thinkers in the field of algebraic topology--in super simplified terms, the mathematics of rubbery shapes. It uses algebra to attack the following question: If given two geometric objects, can you deform one to another without making any cuts? The answer, when it comes to bagels and coffee mugs, is yes, yes you can. If that all sounds annoyingly abstract, well, it kind of is.

Even by the standards of the TED conference, Henry Markram's 2009 TEDGlobal talk was a mind-bender. He took the stage of the Oxford Playhouse, clad in the requisite dress shirt and blue jeans, and announced a plan that--if it panned out--would deliver a fully sentient hologram within a decade. He dedicated himself to wiping out all mental disorders and creating a self-aware artificial intelligence. And the South African–born neuroscientist pronounced that he would accomplish all this through an insanely ambitious attempt to build a complete model of a human brain--from synapses to hemispheres--and simulate it on a supercomputer. Markram was proposing a project that has bedeviled AI researchers for decades, that most had presumed was impossible. He wanted to build a working mind from the ground up. In the four years since Markram's speech, he hasn't backed off a nanometer. The self-assured scientist claims that the only thing preventing scientists from understanding the human brain in its entirety--from the molecular level all the way to the mystery of consciousness--is a lack of ambition. If only neuroscience would follow his lead, he insists, his Human Brain Project could simulate the functions of all 86 billion neurons in the human brain, and the 100 trillion connections that link them.

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.