Anyone who’s had a frustrating interaction with Siri or Alexa knows that digital assistants just don’t get humans. What they need is what psychologists call theory of mind, an awareness of others’ beliefs and desires. Now, computer scientists have created an artificial intelligence (AI) that can probe the “minds” of other computers and predict their actions, the first step to fluid collaboration among machines—and between machines and people.

Run by Methodist missionaries at the time, Nigeria’s first primary school opened in Badagry, Lagos in 1843, marking the beginning of formal education in Nigeria. Then came the CMS grammar school (also in Lagos) in 1859 and by 1914 there were 91 mission schools run by missionaries and 59 run by the government of the day.

If Reddit and Initialized Capital co-founder Alexis Ohanian could give his 20-year-old self one piece of advice, it would be to stick with computer science. He took the one CS class offered at his high school in Columbia, Maryland, and even thought he might become a programmer, he said during a Facebook Live Q&A hosted by 1850 Brand Coffee. But when he got to the University of Virginia and met a few computer science majors, he lost confidence.

I think that a lot of companies are looking for interns who they know are capable of building things and getting things done in practice. This should (hopefully) align with your interests as members of the CS world, so the answer becomes simple — start building things! Of course, this shouldn’t be something you force yourself to do. If you don’t like web development, don’t lock yourself in a room memorizing Javascript. The great part about CS is that so many skills transfer from place to place.

Some teachers have incorporated computer science into their lessons, but what about the students who don’t have those teachers? Many schools offer coding classes, but what about the students who don’t sign up for them? How helpful is an after-school robotics club if students without transportation can’t participate?

Researchers at the National Institute of Standards and Technology (NIST) have made a silicon chip that distributes optical signals precisely across a miniature brain-like grid, showcasing a potential new design for neural networks.

The University of Pennsylvania will offer a completely online master’s degree in computer science, in a bid to make the field more accessible to non-traditional learners. Penn’s School of Engineering and Applied Science will begin offering an online Master of Computer and Information Technology (MCIT) degree beginning in January 2019, the Ivy League university.

A team of researchers at the University of California has developed a novel kind of neural network—one that uses light instead of electricity to arrive at results. In their paper published in the journal Science, the group describes their ideas, their working device, its performance, and the types of applications they believe could be well served by such a network.

An international group of researchers has achieved the world's first multi-qubit demonstration of a quantum chemistry calculation performed on a system of trapped ions, one of the leading hardware platforms in the race to develop a universal quantum computer. The research, led by University of Sydney physicist Dr Cornelius Hempel, explores a promising pathway for developing effective ways to model chemical bonds and reactions using quantum computers.

Earlier this month, a newspaper in Ohio invited its Facebook followers to read the Declaration of Independence, which it posted in 12 bite-sized chunks in the days leading up to July 4. The first nine snippets posted fine, but the 10th was held up after Facebook flagged the post as “hate speech.” Apparently, the company’s algorithms didn’t appreciate Thomas Jefferson’s use of the term “Indian Savages.”

Enterprises that want to leverage the huge amounts of data they are generating to gain useful insights and make faster and better business decisions are going to have to use machine learning at scale for modeling and training. It’s commonplace among hyperscalers like Google, Amazon and Microsoft, and larger corporations are rapidly embracing the technologies.

Despite transitional growing pains, the promise of artificial intelligence (AI) in innovation and decision-making offers a future with better decisions made at the command of but not by humans. That’s what Pradeep Dubey, director of the Parallel Computing Laboratory at Intel, told attendees of a plenary talk at the PEARC18 conference in Pittsburgh, Pa. “Humans and machines have had this very nice separation of labor,” Dubey said. “Humans make decisions; machines crunch numbers … but humans are terrible decision makers.”

Next generation workloads in high performance computing (HPC) involve more unstructured data than ever before. Single files can be in the multi-petabyte range, with millions of files in a directory, possibly billions of files within a file system, and requiring hundreds of petabytes of capacity for a file system. The sheer volume of data places ever greater demands for data management capabilities to streamline data workflows, minimize Total Cost of Ownership and maintain data integrity. Simply gathering and collecting files to create a data set can be problematic.

The computer scientist who has become a leading voice on the threat posed by killer robots describes himself as an “accidental activist.” But Professor Toby Walsh, a leading artificial intelligence researcher who first started sounding the warning over use of AI to develop lethal autonomous weapons in 2015, has helped create a global movement among his peers.

In December 1989 Guido van Rossum, a Dutch computer scientist, set himself a Christmas project. Irked by shortcomings in other programming languages, he wanted to build his own. His principles were simple. First, it should be easy to read. Rather than sprawling over line-endings and being broken up by a tangle of curly braces, each chunk would be surrounded with indented white space.

Quantum computers are still in their infancy, but builders of the exotic machines want to encourage software developers to experiment with them. Programming the circuits on quantum machines is a real challenge . Instead of standard digital bits, which represent either 1 or 0, quantum computers use “qubits,” which can be in both states at once thanks to a phenomenon known as superposition.

How fundamentally difficult is a problem? That’s the basic task of computer scientists who hope to sort problems into what are called complexity classes. These are groups that contain all the computational problems that require less than some fixed amount of a computational resource — something like time or memory.

Standards and curricula in America’s public schools are long overdue for an overhaul. Educators today face a dizzying array of new learning imperatives for students: engineering and design, computer science and computational thinking, media studies, ethnic and gender studies, and entrepreneurship, to name a few.

Being a Girl Scout is about a lot more than selling extremely delicious cookies; being a part of the organization means learning major skills that can help you in all areas of life. Now, Girl Scouts of the USA has announced that girls aged 5 to 18 can earn an entirely new set of 30 badges to add to their collection, and they're based on the technologies and needs of the future. The Girl Scouts' new STEM badges will help girls hone their skills in "environmental stewardship," coding and robotics, cybersecurity, and mechanical engineering, a press release reported.

Early on in the study of quantum computers, computer scientists posed a question whose answer, they knew, would reveal something deep about the power of these futuristic machines. Twenty-five years later, it’s been all but solved. In a paper posted online at the end of May, computer scientists Ran Raz and Avishay Tal provide strong evidence that quantum computers possess a computing capacity beyond anything classical computers could ever achieve.

Thousands of K-8 students will soon be able to take advantage of free after school coding classes that will be funded under California’s latest state budget. The $15 million pilot program approved by the Department of Education earlier this month will allow more than 4,000 after school sites to apply for grants of up to $80,000 over three years. The program aims to offer kids a high-quality coding curriculum, keep lower-income students in a safe environment and prepare them for careers in science, technology, engineering and mathematics (STEM).

A new computer program works smarter, not harder, to solve problems faster than its predecessors. The algorithm is designed to find the best solution to a given problem among all possible options. Whereas other computer programs winnow down the possibilities one at a time, the new program — at the International Conference on Machine Learning in Stockholm — rules out many choices at once.

Last week, at the International Conference on Machine Learning (ICML), a group of researchers described a turtle they had 3D printed. Most people would say it looks just like a turtle, but an artificial intelligence (AI) algorithm saw it differently. Most of the time, the AI thought the turtle looked like a rifle. Similarly, it saw a 3D-printed baseball as an espresso. These are examples of “adversarial attacks”—subtly altered images, objects, or sounds that fool AIs without setting off human alarm bells.

In research published in Physical Review X, the international team show that a quantum computer is less in thrall to the arrow of time than a classical computer. In some cases, it's as if the quantum computer doesn't need to distinguish between cause and effect at all. The new work is inspired by an influential discovery made almost ten years ago by complexity scientists James Crutchfield and John Mahoney at the University of California, Davis. They showed that many statistical data sequences will have a built-in arrow of time.

Artificial intelligence is now so smart that silicon brains frequently outthink people. Computers operate self-driving cars, pick friends' faces out of photos on Facebook, and are learning to take on jobs typically entrusted only to human experts. Researchers from the University of Wisconsin-Madison and Oak Ridge National Laboratory have trained computers to quickly and consistently detect and analyze microscopic radiation damage to materials under consideration for nuclear reactors. And the computers bested humans in this arduous task.