Responding to reports of mass surveillance, engineers say they'll make encryption standard in all Web traffic.
One wonders why encryption hasn't been the default already.
A cautionary tale...I saw lots of references to this on blogs I track in Feedly. Thought my brother-in-law should know about it since he works in electrical engineering. Tracked down the source to Kickstarter. It's an idea -- and probably a good one -- but not real yet.
Is it possible to reverse-engineer this trend in museums by recasting "traditional" exhibitions and programs for a younger audience by promoting them using youth-oriented aesthetics?
ybrid work requires the company to maintain office space and all the costs that go with that. If they have to pay people extra to work at home while still paying for office space, the work-from-home perk will likely be the thing that goes away.
Back here on Earth, Foursquare users will be able to earn a Curiosity-themed badge on the social media platform for check-ins at locations that generate an interest in science, technology, engineering and mathematics. Available late this year, this new badge will encourage Foursquare users to explore science centers, laboratories and museums that pique scientific curiosity.
a high-throughput flow-through optical microscope with the ability to detect rare cells with sensitivity of one part per million in real time.
This technology builds on the photonic time-stretch camera technology created by Jalali's team in 2009 to produce the world's fastest continuous-running camera.
we’ve realised that artificial intelligences (AIs), particularly a form of machine learning called neural networks, which learn from data without having to be fed explicit instructions, are themselves fallible.
The second is that humans turn out to be deeply uncomfortable with theory-free science.
there may still be plenty of theory of the traditional kind – that is, graspable by humans – that usefully explains much but has yet to be uncovered.
The theories that make sense when you have huge amounts of data look quite different from those that make sense when you have small amounts
The bigger the dataset, the more inconsistencies the AI learns. The end result is not a theory in the traditional sense of a precise claim about how people make decisions, but a set of claims that is subject to certain constraints.
theory-free predictive engines embodied by Facebook or AlphaFold.
“Explainable AI”, which addresses how to bridge the interpretability gap, has become a hot topic. But that gap is only set to widen and we might instead be faced with a trade-off: how much predictability are we willing to give up for interpretability?