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Airbus’s plan to bring to market a zero-emission passenger aircraft by 2035 means it needs to start plotting a course in terms of technology in 2025. In fact it needs to plot several courses.


It looks like something out of “Star Trek,” and runs on a fuel experts once thought “crazy,” but Airbus hopes that in 15 years we’ll be flying into a greener future aboard this new zero-emission aircraft concept.

Grid AI, a startup founded by the inventor of the popular open-source PyTorch Lightning project, William Falcon, that aims to help machine learning engineers work more efficiently, today announced that it has raised an $18.6 million Series A funding round, which closed earlier this summer. The round was led by Index Ventures, with participation from Bain Capital Ventures and firstminute.

Falcon co-founded the company with Luis Capelo, who was previously the head of machine learning at Glossier. Unsurprisingly, the idea here is to take PyTorch Lightning, which launched about a year ago, and turn that into the core of Grid’s service. The main idea behind Lightning is to decouple the data science from the engineering.

The time argues that a few years ago, when data scientists tried to get started with deep learning, they didn’t always have the right expertise and it was hard for them to get everything right.

Anxious couples are approaching fertility doctors in the US with requests for a hotly debated new genetic test being called “23andMe, but on embryos.”

The baby-picking test is being offered by a New Jersey startup company, Genomic Prediction, whose plans we first reported on two years ago.

The company says it can use DNA measurements to predict which embryos from an IVF procedure are least likely to end up with any of 11 different common diseases. In the next few weeks it’s set to release case studies on its first clients.

The team’s findings have been published in Nature: Scientific Reports: “Transition delay using biomimetic fish scale arrays,” and in the Journal of Experimental Biology: “Streak formation in flow over biomimetic fish scale arrays.”

Reducing drag means faster aircraft speeds and less fuel consumption—an important area of study for aerodynamicists such as Professor Bruecker, City’s Royal Academy of Engineering Research Chair in Nature-Inspired Sensing and Flow Control for Sustainable Transport, and City’s Sir Richard Oliver BAE Systems Chair for Aeronautical Engineering.

Through their biomimetic study, Professor Bruecker’s team has discovered that the fish-scale array produces a zig-zag motion of fluid in overlapping regions of the surface of the fish, which in turn causes periodic velocity modulation and a streaky flow that can eliminate Tollmien-Schlichting wave induced transition to reduce by more than 25 percent.