A New Reality Materializing: Humans Can Be the New Supercomputer

Illustration: Colourbox

Today, people of all backgrounds can contribute to solving serious scientific problems by playing computer games. A Danish research group has extended the limits of quantum physics calculations and simultaneously blurred the boundaries between man and mac. The Danish research team, CODER, has found out, that the human brain can beat the calculating powers of a computer, when it comes to solving quantum-problems. The saying of philosopher René Descartes of what makes humans unique is beginning to sound hollow. 'I think -- therefore soon I am obsolete' seems more appropriate. When a computer routinely beats us at chess and we can barely navigate without the help of a GPS, have we outlived our place in the world? Not quite. Welcome to the front line of research in cognitive skills, quantum computers and gaming. Today there is an on-going battle between man and machine. While genuine machine consciousness is still years into the future, we are beginning to see computers make choices that previously demanded a human's input. Recently, the world held its breath as Google's algorithm AlphaGo beat a professional player in the game Go--an achievement demonstrating the explosive speed of development in machine capabilities. A screenshot of one of the many games that are available. In this case the task is to shoot spiders in the "Quantum-Shooter" but there are many other

Credit: CODER/AU

kinds of games. But we are not beaten yet -- human skills are still superior in some areas. This is one of the conclusions of a recent study by Danish physicist Jacob Sherson, published in the prestigious science journal Nature. "It may sound dramatic, but we are currently in a race with technology -- and steadily being overtaken in many areas. Features that used to be uniquely human are fully captured by contemporary algorithms. Our results are here to demonstrate that there is still a difference between the abilities of a man and a machine," explains Jacob Sherson. What are quantum computers and how goes playing games help physicist in cutting edge research?Get a few answers in this video about ScienceAtHome. At the interface between quantum physics and computer games, Sherson and his

research group at Aarhus University have identified one of the abilities that still makes us unique compared to a computer's enormous processing power: our skill in approaching problems heuristically and solving them intuitively. The discovery was made at the AU Ideas Centre CODER, where an interdisciplinary team of researchers work to transfer some human traits to the way computer algorithms work. ? Quantum physics holds the promise of immense technological advances in areas ranging from computing to high-precision measurements. However, the problems that need to be solved to get there are so complex that even the most powerful supercomputers struggle with them. This is where the core idea behind CODER--combining the processing power of computers with human ingenuity -- becomes clear. ? Our common intuition: Like Columbus in QuantumLand, the CODER research group mapped out how the human brain is able to make decisions based on intuition and accumulated experience. This is done using the online game "Quantum Moves". Over 10,000 people have played the game that allows everyone contribute to basic research in quantum physics. "The map we created gives us insight into the strategies formed by the human brain. We behave intuitively when we need to solve an unknown problem, whereas for a computer this is incomprehensible. A computer churns through enormous amounts of information, but we can choose not to do this by basing our decision on experience or intuition. It is these intuitive insights that we discovered by analysing the Quantum Moves player solutions," explains Jacob Sherson. ? This is how the "Mind Atlas" looks. Based on 500.000 completed games the group has been able to visualize our ability to solve problems. Each peak on the 'map' represents a good idea, and the area with the most peaks - marked by red rings - are where the human intuition has hit a solution. A computer can then learn to focus on these areas, and in that way 'learn'

Credit: CODER/AU

about the cognitive functions of a human.  The laws of quantum physics dictate an upper speed limit for data manipulation, which in turn sets the ultimate limit to the processing power of quantum computers -- the Quantum Speed ??Limit. Until now a computer algorithm has been used to identify this limit. It turns out that with human input researchers can find much better solutions than the algorithm. "The players solve a very complex problem by creating simple strategies. Where a computer goes through all available options, players automatically search for a solution that intuitively feels right. Through our analysis we found that there are common features in the players' solutions, providing a glimpse into the shared intuition of humanity. If we can teach computers to recognise these good solutions, calculations will be much faster. In a sense we are downloading our common intuition to the computer" says Jacob Sherson. And it works. The group has shown that we can break the Quantum Speed Limit by combining the cerebral cortex and computer chips. This is the new powerful tool in the development of quantum computers and other quantum technologies. We are the new supercomputer: Science is often perceived as something distant and exclusive, conducted behind closed doors. To enter you have to go through years of education, and preferably have a doctorate or two. Now a completely different reality is materializing? In recent years, a new phenomenon has appeared--citizen science breaks down the walls of the laboratory and invites in everyone who wants to contribute. The team at Aarhus University uses games to engage people in voluntary science research. Every week people around the world spend 3 billion hours playing games. Games are entering almost all areas of our daily life and have the potential to become an invaluable resource for science. "Who needs a supercomputer if we can access even a small fraction of this computing power? By turning science into games, anyone can do research in quantum physics. We have shown that games break down the barriers between quantum physicists and people of all backgrounds, providing phenomenal insights into state-of-the-art research. Our project combines the best of both worlds and helps challenge established paradigms in computational research," explains Jacob Sherson. The difference between the machine and us, figuratively speaking, is that we intuitively reach for the needle in a haystack without knowing exactly where it is. We 'guess' based on experience and thereby skip a whole series of bad options. For Quantum Moves, intuitive human actions have been shown to be compatible with the best computer solutions. In the future it will be exciting to explore many other problems with the aid of human intuition. "We are at the borderline of what we as humans can understand when faced with the problems of quantum physics. With the problem underlying Quantum Moves we give the computer every chance to beat us. Yet, over and over again we see that players are more efficient than machines at solving the problem. While Hollywood blockbusters on artificial intelligence are starting to seem increasingly realistic, our results demonstrate that the comparison between man and machine still sometimes favours us. We are very far from computers with human-type cognition," says Jacob Sherson and continues: "Our work is first and foremost a big step towards the understanding of quantum physical challenges. We do not know if this can be transferred to other challenging problems, but it is definitely something that we will work hard to resolve in the coming years."

• Contacts and sources: Jacob Sherson, Aarhus University, 
• Citation: " Exploring the quantum speed limit with computer games" Authors: Jens Jakob W. H. Sørensen, Mads Kock Pedersen, Michael Munch, Pinja Haikka, Jesper Halkjær Jensen, Tilo Planke, Morten Ginnerup Andreasen, Miroslav Gajdacz, Klaus Mølmer, Andreas Lieberoth & Jacob F. Sherson Nature 532, 210–213 (14 April 2016) doi:10.1038/nature17620 http://dx.doi.org/10.1038/nature17620A, Source: http://www.ineffableisland.com/

Read More........→April 14, 2016

Researchers Teach Machines To Learn Like Humans

A team of scientists has developed an algorithm that captures our learning abilities, enabling computers to recognize and draw simple visual concepts that are mostly indistinguishable from those created by humans. The work, which appears in the latest issue of the journal Science, marks a significant advance in the field -- one that dramatically shortens the time it takes computers to 'learn' new concepts and broadens their application to more creative tasks. A team of scientists has developed an algorithm that captures our learning abilities, enabling computers to recognize and draw simple visual concepts that are mostly indistinguishable from those created by humans. "Our results show that by reverse engineering how people think about a problem, we can develop better algorithms," explains Brenden Lake, a Moore-Sloan Data Science Fellow at New York University and the paper's lead author. "Moreover, this work points to promising methods to narrow the gap for other machine learning tasks." The paper's other authors were Ruslan Salakhutdinov, an assistant professor of Computer Science at the University of Toronto, and Joshua Tenenbaum, a professor at MIT in the Department of Brain and Cognitive Sciences and the Center for Brains, Minds and Machines. When humans are exposed to a new concept -- such as new piece of kitchen equipment, a new dance move, or a new letter in an unfamiliar alphabet -- they often need only a few examples to understand its make-up and recognize new instances. While machines can now replicate some pattern-recognition tasks previously done only by humans -- ATMs reading the numbers written on a check, for instance -- machines typically need to be given hundreds or thousands of examples to perform with similar accuracy. "It has been very difficult to build machines that require as little data as humans when learning a new concept," observes Salakhutdinov. "Replicating these abilities is an exciting area of research connecting machine learning, statistics, computer vision, and cognitive science." Salakhutdinov helped to launch recent interest in learning with 'deep neural networks,' in a paper published in Science almost 10 years ago with his doctoral advisor Geoffrey Hinton. Their algorithm learned the structure of 10 handwritten character concepts -- the digits 0-9 -- from 6,000 examples each, or a total of 60,000 training examples. In the work appearing in Science this week, the researchers sought to shorten the learning process and make it more akin to the way humans acquire and apply new knowledge -- i.e., learning from a small number of examples and performing a range of tasks, such as generating new examples of a concept or generating whole new concepts. To do so, they developed a 'Bayesian Program Learning' (BPL) framework, where concepts are represented as simple computer programs. For instance, the letter 'A' is represented by computer code -- resembling the work of a computer programmer -- that generates examples of that letter when the code is run. Yet no programmer is required during the learning process: the algorithm programs itself by constructing code to produce the letter it sees. Also, unlike standard computer programs that produce the same output every time they run, these probabilistic programs produce different outputs at each execution. This allows them to capture the way instances of a concept vary, such as the differences between how two people draw the letter 'A.' While standard pattern recognition algorithms represent concepts as configurations of pixels or collections of features, the BPL approach learns "generative models" of processes in the world, making learning a matter of 'model building' or 'explaining' the data provided to the algorithm. In the case of writing and recognizing letters, BPL is designed to capture both the causal and compositional properties of real-world processes, allowing the algorithm to use data more efficiently. The model also "learns to learn" by using knowledge from previous concepts to speed learning on new concepts -- e.g., using knowledge of the Latin alphabet to learn letters in the Greek alphabet. The authors applied their model to over 1,600 types of handwritten characters in 50 of the world's writing systems, including Sanskrit, Tibetan, Gujarati, Glagolitic -- and even invented characters such as those from the television series Futurama. In addition to testing the algorithm's ability to recognize new instances of a concept, the authors asked both humans and computers to reproduce a series of handwritten characters after being shown a single example of each character, or in some cases, to create new characters in the style of those it had been shown. The scientists then compared the outputs from both humans and machines through 'visual Turing tests.' Here, human judges were given paired examples of both the human and machine output, along with the original prompt, and asked to identify which of the symbols were produced by the computer. While judges' correct responses varied across characters, for each visual Turing test, fewer than 25 percent of judges performed significantly better than chance in assessing whether a machine or a human produced a given set of symbols. "Before they get to kindergarten, children learn to recognize new concepts from just a single example, and can even imagine new examples they haven't seen," notes Tenenbaum. "I've wanted to build models of these remarkable abilities since my own doctoral work in the late nineties. We are still far from building machines as smart as a human child, but this is the first time we have had a machine able to learn and use a large class of real-world concepts -- even simple visual concepts such as handwritten characters -- in ways that are hard to tell apart from humans."Contacts and sources:James Devitt, New York University Source: http://www.ineffableisland.com/, Image: https://pixabay.com/, under Creative Commons CC0

Read More........→December 13, 2015

China scientist ‘ready’ to clone humans

Boyalife Group shows three cloned puppies in an incubator at a facility in Tianjin, China. (Photo: AFP)

The Chinese scientist behind the world’s biggest cloning factory has technology advanced enough to replicate humans, he said, and is only holding off for fear of the public reaction. Boyalife Group and its partners are building the giant plant in the northern Chinese port of Tianjin, where it is due to go into production within the next seven months and aims for an output of one million cloned cows a year by 2020. But cattle are only the beginning of chief executive Xu Xiaochun’s ambitions. In the factory pipeline are also thoroughbred racehorses, as well as pet and police dogs, specialised in searching and sniffing. Boyalife is already working with its South Korean partner Sooam and the Chinese Academy of Sciences to improve primate cloning capacity to create better test animals for disease research. And it is a short biological step from monkeys to humans, potentially raising a host of moral and ethical controversies. “The technology is already there,” Xu said. “If this is allowed, I don’t think there are other companies better than Boyalife that make better technology.” The firm does not currently engage in human cloning activities, Xu said, adding that it has to be “self-restrained” because of possible adverse reaction. But social values can change, he pointed out, citing changing views of homosexuality and suggesting that in time humans could have more choices about their own reproduction. “Unfortun-ately, currently, the only way to have a child is to have it be half its mum, half its dad,” he said. “Maybe in the future you have three choices instead of one,” he went on. “You either have fifty-fifty, or you have a choice of having the genetics 100 per cent from daddy or 100 per cent from mummy. This is only a choice.” Xu, 44, went to university in Canada and the US, and has previously worked for US pharmaceutical giant Pfizer, and in drug development. Presenting cloning as a safeguard of biodiversity, the Tianjin facility will house a gene bank capable of holding up to approximately five million cell samples frozen in liquid nitrogen, a catalogue of the world’s endangered species for future regeneration. Boyalife’s South Korean partner Sooam is already working on a project to bring the woolly mammoth back from extinction by cloning cells preserved for thousands of years in the Siberian permafrost. Sooam also serves a niche market recreating customers’ dead pet dogs, reportedly for $100,000 a time. Sooam founder Hwang Woo-Suk was a national hero with his own postage stamp before being embroiled in controversy a decade ago after his claims to be the first in the world to clone a human embryo were discredited. Hwang, who created Snuppy, the world’s first cloned dog, in 2005, lost his university position, had two major papers retracted, and was accused of crimes ranging from violation of bioethics laws to embezzling research funds. Earlier this year, he was quoted in South Korea’s Dong-A Ilbo newspaper saying that his firm was planning a cloning joint venture in China “because of South Korea’s bioethics law that prohibits the use of human eggs”. “We have decided to locate the facilities in China in case we enter the phase of applying the technology to human bodies,” he was quoted as saying. For now, Xu seeks to become the world’s first purveyor of “cloned” beef, breeding genetically identical super-cattle that he promises will taste like Kobe and allow butchers to “slaughter less and produce more” to meet the demands of China’s booming middle class. Cloning differs from genetic modification, but its application to animals would enable the firm to homogenise its output. Source: The Asian Age

Read More........→December 13, 2015

4 Million Year Old Menu: What Our Ancestors Ate

The diet of Australopithecus anamensis, a hominid that lived in the east of the African continent more than 4 million years ago, was very specialized and, according to a scientific study whose principal author is Ferran Estebaranz, from the Department of Animal Biology at the University of Barcelona, it included foods typical of open environments (seeds, sedges, grasses, etc.), as well as fruits and tubers. 

Artist's concept for Australopithecus anamensi, Credit: Universidad de Barcelona

Australopithecus anamensis (or Praeanthropus anamensis) is a stem-human species that lived approximately four million years ago. Nearly one hundred fossil specimens are known from Kenya and Ethiopia, representing over 20 individuals.

Australopithecus anamensis bone fragment, Credit: University of Zurich

The work, published in the Journal of Anthropological Sciences, is directed by lecturer Alejandro Pérez Pérez, from the Anthropology Unit of the Department of Animal Biology at the UB, and its co-authors are professor Daniel Turbón and experts Jordi Galbany and Laura M. Martínez. Australipithecus anamensis is a fossil hominid species described in 1995 by a team led by the researcher Meave Leakey and it is considered to be the direct ancestor of Australopithecus afarensis, known as Lucy, which lived in the same region half a million years later. The paleoecological reconstructions of the sites with Australipithecus anamensis fossil remains are quite similar to those of Australipithecus afarensis, and suggest a scene with different habitats, from open forests to thick plant formations, with herbaceous strata and gallery forests.Traditionally, the reconstruction of the diet of Australipithecus anamensis was carried out by means of indirect evidence (specifically, studies of microstructure and enamel thickness, and the dental size and morphology). In this new study, the team of the UB analyzes the pattern of microstriation of the post-canine dentition, from microscopic traces that some structural components of plants (phytoliths) and other external elements (sand, dust, etc.) leave in the dental enamel during the chewing of food. It is, therefore, a direct analysis of the result of the interaction of the diet with the teeth. SEM images of buccal microstriation pattern of specimens studied: Au. anamensis (a-e) and Au. afarensis (f).

A cercopithecoid model for the study of the diet, Credit: Universidad de Barcelona 

The work published in the Journal of Anthropological Sciences studies the microstriation pattern of all the specimens of Australipithecus anamensis recovered up to the year 2003, of which only five are in a good state of preservation. According to the study of the microstriation pattern, the diet of Anthropological anamensis was similar to other present day species of cercopithecoid primates, such as Papiogenus(baboons) and Chlorocebus (green monkey), which live in shrubby savannah areas with a marked seasonal influence. The work arrived at the conclusion that the diet of Australipithecus anamensis was quite abrasive and rich in seeds, leaves and corms, as it is with the baboons of today. This fossil hominid must also have fed on fruit, but in smaller proportions than Australipithecus afarensis.

Graphical representation of the analysis of the groups studied that shows the differences between striation patterns of Au. anamensis and Au. afarensis, Credit: Universidad de Barcelona

What did Australopithecus afarensis eat? The results of the study on the palaeodiet of Australipithecus anamensis match the characteristics of dental morphology and increased robustness of the dentition and the masticatory apparatus compared with its ancestor, Ardipithecus ramidus. The new questions now focus on the diet of Australipithecus afarensis, direct descendent of Australipithecus anamensis, which has a frugivorous and much softer diet, like present day chimpanzees and gorillas in Cameroon. As explained by the researcher Ferran Estebaranz,“the microstriation pattern of Australipithecus anamensis and Australipithecus afarensis is clearly different. This could indicate that the former consumed much harder foodstuffs, whereas the latter had a basically frugivorous diet, of a seasonal character, more similar to the direct ancestor of the two species, Ardipithecus ramidus”. 

Ardipithecus ramidus, Credit: Wikipedia

Contacts and sources: Universidad de Barcelona, http://www.ub.edu, Citaiton: Buccal dental microwear analyses support greater specialization in consumption of hard foodstuffs for Australopithecus anamensis. Ferran Estebaranz, Jordi Galbany, Laura M Martínez, Daniel Turbón and Alejandro Pérez-Pérez. Journal of Anthropological Sciences. Vol. 90 (2012), pp. 1-244, Source: Article, 

Read More........→November 24, 2015

Human embryos genetically modified by Chinese scientists

In a world first, researchers at Sun Yat-sen University in Guangzhou, China, admit to having edited the genome of live human embryos to see the effect on a fatal blood disorder, thalassaemia. The research is banned in Europe – but Chinese scientists have confirmed that they recently edited the DNA of human embryos for the very first time. Researchers at Sun Yat-sen University, led by Junjiu Huang, have tried to ease concerns by explaining that they used non-viable embryos, which cannot result in a successful live birth, that were obtained from local fertility clinics. Huang's team used a revolutionary new technique known as CRISPR/Cas9, discovered by scientists at MIT. A total of 86 embryos were injected with the Cas9 protein and left for two days while the gene-editing process took place. Of these, 71 survived and subsequent tests revealed that 28 were successfully spliced, but only a fraction contained the genetic material needed to prevent the fatal blood disorder thalassaemia. Unexpected mutations were also noticed in the genes. "I think that this is a significant departure from currently accepted research practice," said Shirley Hodgson, Professor of Cancer Genetics, St George's University of London. "Can we be certain that the embryos that the researchers were working on were indeed non-viable? Any proposal to do germline genetic manipulation should be very carefully considered by international regulatory bodies before it should be considered a serious research prospect." "This news emphasises the need for an immediate global ban on the creation of GM designer babies," comments Dr David King, director of UK watchdog Human Genetics Alert. "It is critical that we avoid a eugenic future in which the rich can buy themselves a baby with built-in genetic advantages. It is entirely unnecessary since there are already many ethical ways to avoid thalassaemia. This research is a classic example of scientific careerism – assuring one's place in the history books even though the research is unnecessary and unethical." "The study is a landmark, as well as a cautionary tale," says George Daley, a stem-cell biologist at Harvard Medical School in Boston. "Their study should be a stern warning to any practitioner who thinks the technology is ready for testing to eradicate disease genes." The research appears in the journal Protein and Cell after the prestigious journals Nature and Science refused to publish it on ethical grounds. Source: Article

Read More........→July 15, 2015