Lifeboat Foundation

Alphabet’s healthcare and tech company Verily will use a sex-sorting computer vision algorithm to help Singapore battle mosquitoes.

Machine-learning algorithms are helping to unravel the quantum behaviour of a type of superconductor that has baffled physicists for decades.

Researchers used artificial intelligence to spot hidden order in images of a bizarre state in high-temperature superconductors.

Don’t know your machine learning from your evolutionary algorithms? Our handy A.I. buzzword guide is here to help.

This video is the first in a two-part series discussing big data. In this video, we’ll be discussing the importance of data and the role, it has played in advancing humankind as well as the exponential rate of growth of data.

[0:29–4:19] — Starting off we’ll look at, how data has been used as a tool from the origins of human evolution, starting at the hunter-gatherer age and leading up to the present information age.

[4:19–7:48] — Following that we’ll discuss, the many statistics demonstrating the exponential rate of growth and future growth of data.

Continue reading “The Exponential Growth of Data” »

Since its acquisition of ITA Matrix Software eight years ago, Google has been quietly rolling out new tools for travelers. Its progress has been even more notable over the past months and weeks as it began unveiling tools to help predict flight delays, plan trips, and manage itineraries — among other things.

These changes have some wondering: Is Google making a run at total domination in the travel space? If it is, there’s a strong case to be made for its potential to disrupt the travel and hospitality sector with a similar approach to Amazon’s run at retail, and more recently grocery.

Realistic climate simulations require huge reserves of computational power. An LMU study now shows that new algorithms allow interactions in the atmosphere to be modeled more rapidly without loss of reliability.

Forecasting global and local climates requires the construction and testing of mathematical climate models. Since such models must incorporate a plethora of physical processes and interactions, climate simulations require enormous amounts of computational power. And even the best models inevitably have limitations, since the phenomena involved can never be modeled in sufficient detail. In a project carried out in the context of the DFG-funded Collaborative Research Center “Waves to Weather”, Stephan Rasp of the Institute of Theoretical Meteorology at LMU (Director: Professor George Craig) has now looked at the question of whether the application of artificial intelligence can improve the efficacy of climate modelling. The study, which was performed in collaboration with Professor Mike Pritchard of the University of California at Irvine und Pierre Gentine of Columbia University in New York, appears in the journal PNAS.

General circulation models typically simulate the global behavior of the atmosphere on grids whose cells have dimensions of around 50 km. Even using state-of-the-art supercomputers the relevant physical processes that take place in the atmosphere are simply too complex to be modelled at the necessary level of detail. One prominent example concerns the modelling of clouds which have a crucial influence on climate. They transport heat and moisture, produce precipitation, as well as absorb and reflect solar radiation, for instance. Many clouds extend over distances of only a few hundred meters, much smaller than the grid cells typically used in simulations – and they are highly dynamic. Both features make them extremely difficult to model realistically. Hence today’s climate models lack at least one vital ingredient, and in this respect, only provide an approximate description of the Earth system.

A new AI algorithm developed at Facebook could enable translating between obscure languages and across disparate domains.

Citi has produced another of its Disruptive Innovations publications, which takes a look at what it considers to be the top ten disruptive technologies. It is a sign of the changing times that anti-aging medicines are number 2 in its list.

1. All-Solid-State Batteries 2. Anti-Aging Medicines 3. Autonomous Vehicle Networks 4. Big Data & Healthcare 5. Dynamic Spectrum Access 6. eSports 7. 5G Technology 8. Floating Offshore Wind Farms 9. Real Estate Market Disruptors 10. Smart Voice-Activated Assistants.

What was considered fringe science a decade ago is now rapidly becoming a mainstream industry. Our understanding of aging has advanced quickly in the last 10 years, and the tools and innovations seem to come more quickly with each passing year. A variety of therapies that target different aging processes are in development, and some are at fairly advanced stages; if you are interested in their progress, check out the Rejuvenation Roadmap.

This AI can JUDGE how attractive you are and more… and it could be a dangerous sign of things to come.