Last Week Ben Goertzel and his company, Aidyia, turned on a hedge fund that makes all stock trades using artificial intelligence—no human intervention required. “If we all die,” says Goertzel, a longtime AI guru and the company’s chief scientist, “it would keep trading.” He means this literally. Goertzel and other humans built the system, of course, and they’ll continue to modify it as needed. But their creation identifies and executes trades entirely on its own, drawing on multiple forms of AI, including one inspired by genetic evolution and another based on probabilistic logic.

University of Saskatchewan professor Stephen Foley and his team appear to have the Midas touch when it comes to gold extraction research. Foley, along with Loghman Moradi and Hiwa Salimi, have discovered a new financially viable and environmentally friendly way to recover and recycle gold from electronic waste. "We've found a simple, cheap and environmentally benign solution that extracts gold in seconds, and can be recycled and reused," said Foley. "This could change the gold industry." The biggest issue with gold is it is one of the least reactive chemical elements, making it difficult to dissolve, Foley explained.

One of the stranger objectives of President Obama’s Brain Initiative Project is a new DARPA program that is funding the creation of an implantable neural interface that would bridge the brain-machine divide. But it’s not like in the movies, right? Not quite, but ideas like thought-activated Googling and plugging into the grid are beginning to sound less and less far-fetched. The program is aimed at developing an implantable neural device, no larger than one cubic centimeter in size, that would enable data-transfer between the human brain and the digisphere. The interface would be able to resolve the brain’s signal, converting it from the electrochemical language used by neurons in the brain into the the ones and zeros of digital computing.

Many will be familiar with HPC and industrial or scientific applications, but now HPC is making its impact on something that touches the soul of millions and millions of people every day — music. In an interview with the inventor of HPC for Music, Antonis Karalis shared a brief explanation of how the future of music has been compromised and what steps are being taken to revolutionize music composition, the creative workflow, and deliver new entertainment experiences.

The human brain’s memory-storage capacity is an order of magnitude greater than previously thought, researchers at the Salk Institute for Biological Studies reported last week. The findings, recently detailed in eLife, are significant not only for what they say about storage space but more importantly because they nudge us toward a better understanding of how, exactly, information is encoded in our brains.

Carnegie Mellon University is embarking on a five-year, $12 million research effort to reverse-engineer the brain, seeking to unlock the secrets of neural circuitry and the brain’s learning methods. Researchers will use these insights to make computers think more like humans. The research project, led by Tai Sing Lee, professor in the Computer Science Department and the Center for the Neural Basis of Cognition, is funded by the Intelligence Advanced Research Projects Activity (IARPA) through its Machine Intelligence from Cortical Networks research program. MICrONS is advancing President Barack Obama’s BRAIN Initiative to revolutionize the understanding of the human brain.

Five million jobs in the world's leading economies could disappear over the next five years because of advances in technology. Developments in artificial intelligence, robotics, and biotechnology, would disrupt the business world in a similar way to previous industrial revolutions, the World Economic Forum said. Administrative and white collar office jobs are most at risk from a "fourth industrial revolution," the forum said. The forum surveyed senior executives from over 350 of the biggest companies in 15 of the world's major emerging and developed economies. Together, those economies account for 65% of the global workforce.

The sun's magnetic fields are pretty complex and hard to appreciate; however, to make them easier to understand, NASA has built a moving computer model that is aimed at mapping the star's fields. The model itself shows closed magnetic field lines, and open ones which project out into space. The open lines are colored pink or green while bright spots appear when the closed lines run into each other. Studying the solar magnetic fields is important because these magnetic explosions can cause solar flares and solar storms.

Simulating even small biological systems has long proven computational difficult. Practically speaking, data-driven bioinformatics such as DNA sequence analysis has progressed more rapidly. Development of Anton 1, the ASIC-based supercomputer specifically designed for simulating molecular dynamics by D. E. Shaw Research in 2008, was a major advance. In 2010 DESRES provided an Anton machine at no charge to the Pittsburgh Supercomputer Center, which in turn provided access to a wider biomedical research community. History is now repeating itself. Anton 2, a significant upgrade, was developed in 2014 and PSC announced this week it planned to retire its Anton 1 and provide access to an Anton 2 machine in the fall 2016.

Researchers at MIT and Texas Instruments have developed a new type of radio frequency identification (RFID) chip that is virtually impossible to hack. If such chips were widely adopted, it could mean that an identity thief couldn't steal your credit card number or key card information by sitting next to you at a café, and high-tech burglars couldn't swipe expensive goods from a warehouse and replace them with dummy tags. Texas Instruments has built several prototypes of the new chip, to the researchers' specifications, and in experiments the chips have behaved as expected.

With one foot in its fields and another edged toward Silicon Valley, Salinas is trying to reboot itself as the agricultural technology center of California. It hopes to turn the sons and daughters of farmworkers into coders for the next generation of data-driven, automated farming in a valley known as the salad bowl of the world. "We're not trying to reinvent ourselves," said Andrew Myrick, the city's economic development manger. "There's cities all across the country that are trying to attract Google to come and build their headquarters. That's not who we are. We're agriculture." No public high school in the Salinas valley taught computer science and only a sliver of Salinas' workforce worked in computer science for a living when the ag-tech idea took hold here about four years ago.

The room looked like something you'd see in Palo Alto or Mountain View: pizza boxes strewn across a table at one end, young people clustered around computer screens at the other, working in near silence except for the occasional mumble or electronic bleep. They were York High School students searching for viruses, malware, backdoors, password crackers and other Internet terrors on simulated computer networks. After scanning the contents of one folder, Amelia O'Halloran spotted an ominous file. "Keystroke logger?" she said. "That's bad," replied Alaina Bottens. Their discovery came in the opening minutes of the CyberPatriot competition, in which students aim to lock down virtual computer networks from the threat of hackers and rogue agents.

A multi-disciplinary team of researchers at the University of California Los Angeles have developed a detailed computer model of an injured human leg that includes the complex workings of blood flow. The aim of the project, sponsored by the Office of Naval Research, is to provide combat medics with a realistic training tool to enable them to better control hemorrhaging. Medics need to know how to treat traumatic limb injuries and severe bleeding, but existing simulators lacked realistic blood mechanics.The simulator was created at UCLA’s Center for Advanced Surgical and Interventional Technology by a team that included surgeons, fluid dynamicists, biomedical engineers, mathematicians and psychologists.

I just returned from this year's annual gathering of the World Economic Forum at Davos, where leaders from around the world gathered to discuss the implications of a new industrial revolution. This fourth industrial revolution (after the revolutions brought about by steam power, electricity and electronics) is using digital technology to revolutionize almost every part of our life at an unprecedented pace, from self-driving cars to AI-enabled assistants. One of the biggest implications, outlined in The Industry Gender Gap report, is just how harmful this revolution may be to the progress of women because they are underrepresented in tech.

A team of researchers from Microsoft and the Broad Institute of MIT and Harvard has developed a new system that allows researchers to more quickly and effectively use the powerful gene editing tool CRISPR. The system, dubbed Azimuth, uses machine learning, in which a computer takes a limited set of training data and uses that to learn how to make predictions about data it hasn't yet seen. In this case, the machine learning system is being used to predict which part of a gene to target when a scientist wants to knockout – or shut off – a gene. Machine learning enables the model to make predictions for any gene of interest, including those not seen in the experimental training data.

When he went to university in South Africa, Riaz Moola came face to face with the huge differences in educational opportunity in his country, particularly in his own subject, Computer Science. Instead of just getting on with his course, Riaz - now a Gates Cambridge Scholar at the University of Cambridge - devised a way of tackling the problem. Inspired by recent MOOC platforms such as Coursera, he created an online course platform adapted to Africa which paired tutors - typically Computer Science graduates - with students trying to learn programming through a low-bandwidth, text-based resource.

Yoshua Bengio leads one of the world’s preeminent research groups developing a powerful AI technique known as deep learning. The startling capabilities that deep learning has given computers in recent years, from human-level voice recognition and image classification to basic conversational skills, have prompted warnings about the progress AI is making toward matching, or perhaps surpassing, human intelligence. Prominent figures such as Stephen Hawking and Elon Musk have even cautioned that artificial intelligence could pose an existential threat to humanity.

Scott Porad badly wanted to hire Mike Hansen to work at Rover, a Seattle dog-sitting startup. Porad, Rover’s chief technology officer, knew just how to get Hansen, a software developer, to exit the interview process at Google, where he was being considered for a job that would probably pay much more. He would tell Hansen about Rover’s thoroughly dog-friendly benefits. “Mike is the owner of two dogs that he loves,” Porad said. “He felt like the purpose of what we were doing was more meaningful for him and appreciated the fact that he could bring his dogs to work here.”

Throughout the academic year, the Wozniak hosts the tech companies who come to Berkeley hoping to recruit computer-science and engineering students for internships and post-graduate programs. The attendee count at these events typically numbers well into the hundreds—computer science is now the most popular major at Berkeley, which has an undergraduate population of around 27,000 students. An introductory computer-science course, CS61A, had 1,277 students enrolled last semester, all of them encouraged by the department to watch the lectures online rather than physically attending (no lecture hall on campus has the capacity).

Drop-out rates for some IT courses are as high as 70%, according to a report from the Higher Education Authority published this week. And in individual maths-related courses across third-level education, up to 80% of students are failing to progress beyond year one. There are now serious concerns about high and persistent skill shortages across the information and computer technology sector. And while there are various theories as to why so many students are failing, it is clear (as the report from the HEA warns) that many who opt for courses in IT and computer science are simply not prepared - or lack the basic skills and aptitude - to stay the course.

When Julian Bleecker first set foot in a lab at the University of Washington Seattle researching human-computer interaction, he was at a loss. He’d studied electrical engineering as an undergrad, so the lab’s work on an early version of virtual reality was unfamiliar ground. To get the lay of the land, Bleecker was told to read “Neuromancer,” the 1984 science fiction novel by William Gibson in which people connect computers to their brains and experience the data of cyberspace as if it had physical form.

Members of Prospect High School's new Girls Who Code club learned from the founder of the national non-profit organization that it's important to fail. "When I was growing up in Schaumburg, I was terrified of math and science … and my parents were both engineers," Reshma Saujani, CEO of the group that aims to close the gender gap in technology by inspiring girls to pursue computer science-related careers, said last week. "In life, you should be failing as much as you can, and trying to be imperfect. If you do that, you will succeed."

Data scientist, named the best job in America for 2016 by job site Glassdoor, is the sexy mashup of traditional careers from data analysis, economics, statistics, computer science and others. But it goes beyond collecting and analyzing data. It's a job for the curious, for the intuitive and for those who like to not just solve problems but figure out the problem. It's part science, part art. The rise of data science is due to the explosive growth of data collection — or big data — and the need for companies to make sense of the mishmash of new types of data from smartphones, images, human behavior and even handwriting.

President Obama pledged $4 billion in funding for computer science education in the nation’s schools. The Computer Science for All Initiative slated for the president’s forthcoming budget plan would include an additional $100 million that would go directly to school districts to fund computer science programs. Under the president’s plan, the Department of Education will divide the $4 billion over three years to states that propose well-designed five-year plans to increase computer science access in classrooms. Along with billions in federal funding, the initiative also includes commitments from philanthropists and some of the country’s largest tech companies to help increase opportunities for computer science training, especially for underrepresented groups.

You can chalk it up as another victory for the machines. In what they called a milestone achievement for artificial intelligence, scientists said on Wednesday they have created a computer program that beat a professional human player at the complex board game called Go, which originated in ancient China. The feat recalled IBM supercomputer Deep Blue's 1997 match victory over chess world champion Garry Kasparov. But Go, a strategy board game most popular in places like China, South Korea and Japan, is vastly more complicated than chess.