Helix will sequence your genes for $80 and lure app developers to sell you access to different parts of it.
Read more
Is this the beginning of Skynet? A robot is being hired to help out shoppers at a St. Louis grocery store chain.
Tally will be working the aisles at Schnucks grocery stores looking for items that are out of stock and checking on prices, the St. Louis Post-Dispatch reported.
Read more
At Jef Boeke’s lab, you can whiff an odor that seems out of place, as if they were baking bread here.
But he and his colleagues are cooking up something else altogether: yeast that works with chunks of man-made DNA.
Scientists have long been able to make specific changes in the DNA code. Now, they’re taking the more radical step of starting over, and building redesigned life forms from scratch. Boeke, a researcher at New York University, directs an international team of 11 labs on four continents working to “rewrite” the yeast genome, following a detailed plan they published in March.
Read more
Google’s DeepMind has revealed a radical new research project designed to give AI’s an imagination.
The breakthrough means that systems will be able to think about their actions, and undertake ‘deliberate reasoning.’
The radical system uses an internal ‘imagination encoder’ that helps the AI decide what are and what aren’t useful predictions about its environment.
Read more
Researchers from Tsinghua University in Beijing have now developed a new type of electronic skin, with a colour change easily seen at just 0–10 per cent strain.
The material is made from graphene — a form of pure carbon that is 200 times stronger than steel.
Two layers of graphene are included — a highly-resistive strain sensor, alongside a stretchable organic electrochromic device (ECD) that changes colour when a current is applied.
Read more
By Marc Pollefeys, Director of Science, HoloLens
It is not an exaggeration to say that deep learning has taken the world of computer vision, and many other recognition tasks, by storm. Many of the most difficult recognition problems have seen gains over the past few years that are astonishing.
Although we have seen large improvements in the accuracy of recognition as a result of Deep Neural Networks (DNNs), deep learning approaches have two well-known challenges: they require large amounts of labelled data for training, and they require a type of compute that is not amenable to current general purpose processor/memory architectures. Some companies have responded with architectures designed to address the particular type of massively parallel compute required for DNNs, including our own use of FPGAs, for example, but to date these approaches have primarily enhanced existing cloud computing fabrics.
Read more
Gene editing aims to make precise changes to the target DNA whilst avoiding altering other parts of the DNA. The objective of this is to remove undesirable genetic traits and introduce desirable changes in both plants and animals. For example, it could be used to make crops more drought resistant, prevent or cure inherited genetic disorders or even treat age-related diseases.
As some of you may recall, back in May a study was published which claimed that the groundbreaking gene editing technique CRISPR caused thousands of off target and potentially dangerous mutations[1]. The authors of the paper called for regulators to investigate the safety of the technique, a move that could potentially set back research years if not decades.
This publication has been widely blasted by the research community due to serious questions about the study design being raised. One of the problems with this original paper was that it involved only three mice, this is an extremely poor number to make the kind of conclusions the paper did. There have been calls for the paper to be withdrawn and critical responses to the study.
Read more
