The chips in most modern desktop computers have four “cores,” or processing units, which can run different computational tasks in parallel. But the chips of the future could have dozens or even hundreds of cores, and taking advantage of all that parallelism is a stiff challenge.

Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory have developed a new system that not only makes parallel programs run much more efficiently but also makes them easier to code.

When organic chemists identify a useful chemical compound — a new drug, for instance — it’s up to chemical engineers to determine how to mass-produce it.

There could be 100 different sequences of reactions that yield the same end product. But some of them use cheaper reagents and lower temperatures than others, and perhaps most importantly, some are much easier to run continuously, with technicians occasionally topping up reagents in different reaction chambers.

High-resolution earth imagery has provided ecologists and conservationists with a dynamic new tool that is enabling everything from more accurate counting of wildlife populations to rapid detection of deforestation, illegal mining, and other changes in the landscape.

Researchers from the University of Oxford are using a unique blend of virtual reality and innovative genetic techniques to understand the causes of diseases such as diabetes and anaemia.

Beech trees should be considered native to Scotland – despite a long-running debate over their national identity, researchers at the University of Stirling and Science and Advice for Scottish Agriculture (SASA) report.

Worker and queen honeybees exposed to field-realistic levels of neonicotinoid insecticides die sooner, reducing the health of the entire colony, a new study led by York University biologists has found.

Researchers were also surprised to find the neonicotinoid-contaminated pollen collected by the honeybees came not from crops grown from neonicotinoid-treated seeds, but plants growing in areas adjacent to those crops.

The Montreal Protocol has been hailed for controlling chlorine-based chemicals that created a vast hole in the ozone layer over Antarctica. But new research by British and American scientists suggest a chemical not controlled by the international treaty poses a potential risk to the Earth’s protective ozone layer.

An ecological filter in a pond, such as voracious fish that feed on dragonflies and damselflies, can help ecologists predict how biodiversity loss may impact specific habitats, according to Rice University researchers who spent four years studying seasonal changes in ponds across East Texas.

In one of the first studies of its kind, the scientists show that strong environmental “filters” — in this case, predatory fish — cause dragonfly and damselfly communities to vary regularly from year to year and season to season in ponds across East Texas. The results, which appear online this week in the journal Ecology Letters, show how an ecological filter can help ecologists predict how biodiversity loss may impact specific habitats.

Using a state-of-the-art device for measuring mass, researchers at the National Institute of Standards and Technology (NIST) have made their most precise determination yet of Planck's constant, an important value in science that will help to redefine the kilogram, the official unit of mass in the SI, or international system of units. Accepted for publication (link is external) in the journal Metrologia, these new results come ahead of a July 1 international deadline for measurements that aim to redefine the entire SI in terms of fundamental constants of nature.

Neural networks, which learn to perform computational tasks by analyzing large sets of training data, are responsible for today’s best-performing artificial intelligence systems, from speech recognition systems, to automatic translators, to self-driving cars.

But neural nets are black boxes. Once they’ve been trained, even their designers rarely have any idea what they’re doing — what data elements they’re processing and how.

Two years ago, a team of computer-vision researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) described a method for peering into the black box of a neural net trained to identify visual scenes. The method provided some interesting insights, but it required data to be sent to human reviewers recruited through Amazon’s Mechanical Turk crowdsourcing service.