Lifeboat Foundation

Wow!

Mobile phone data may reveal an underlying mathematical connection between how we move and how we communicate that could make it easier to predict how diseases—and even ideas—spread through a population, according to an international team of researchers.

“This study really deepens our quantitative understanding of human behavior,” said Dashun Wang, assistant professor of information sciences and technology, Penn State. “We would like to think that we control our own behavior and we can do what we want to do. But, what we are starting to see with big data is that there is a very deep regularity underlying much of what we do.”

Continue reading “Walking and talking behaviors may help predict epidemics and trends” »

On May 11, 2016, the Berggruen Philosophy and Culture Center invited Yuval Noah Harari, a professor of history at Hebrew University of Jerusalem and author of the international bestseller “Sapiens: A Brief History of Humankind,” to deliver a talk on “The New Inequalities” at Tsinghua University in Beijing. Prior to the talk, Harari was interviewed by BPPC director Daniel A. Bell. This is an edited transcript of the interview.

You argue in your book that material progress, for example in the agriculture revolution and industrial capitalism doesn’t necessarily contribute to human happiness. In fact, it may lead to the opposite. Can you elaborate on that?

Until the middle of the 19th century there was a complete lack of correlation between material progress and the well-being of individual humans. For thousands of years until about 1850 you see humans accumulating more and more power by the invention of new technologies and by new systems of organization in the economy and in politics, but you don’t see any real improvement in the well-being of the average person. If you are the emperor of China, then obviously you’re much better off. But if you’re an average Chinese peasant in 1850, it’s very, very hard to say that your life is any better than the life of hunter-gatherers in the Yangtze Valley 20,000 years ago. You work much harder than them, your diet is worse, you suffer far more from infectious diseases, and you suffer far more from social inequality and economic exploitation.

Continue reading “Historian: When Computers and Biology Converge, Organisms Become Algorithms” »

When I 1st read this headline, I had to pause and ask myself “was the article’s author informed at all on QC?” especially given China’s own efforts much less D-Wave, Google, and University of Sydney. And, then I read the article and I still have to wonder if the author is on top of the emerging technologies such as BMI, graphene, QC, and other nanotechnology that are already being tested to go live in the next 7 to 10 years plus much of the content is very superficial at best. I am glad that the author did put the tid bit on Singularity as the endpoint state; however, that is pretty well known. Nonetheles, sharing to let you be the judge.

For decades, we relied on silicon as the semiconductor for our computer chips. But now, working at nanometer scales, it looks like physical limitations may end the current methods to include more and more processing power onto each individual chip.

Many companies are making billion-dollar investments to continue scaling down semiconductor technology. The pressures of big data and cloud computing are pushing the limits of the current semiconductor technology in terms of bandwidth, memory, processing speed, and device power consumption.

Continue reading “What Will Electronics & Semiconductors Be Like In 100 Years?” »

Georgia Institute of Technology developed a control algorithm that ‘taught’ 3-ft, 48lb rally cars how to plan and execute optimal handling decisions in real-time while on rough terrain.

“So there came a time in which the ideas, although accumulated very slowly, were all accumulations not only of practical and useful things, but great accumulations of all types of prejudices, and strange and odd beliefs.
Then a way of avoiding the disease was discovered. This is to doubt that what is being passed from the past is in fact true, and to try to find out ab initio again from experience what the situation is, rather than trusting the experience of the past in the form in which it is passed down. And that is what science is: the result of the discovery that it is worthwhile rechecking by new direct experience, and not necessarily trusting the [human] race[’s] experience from the past. I see it that way. That is my best definition…Science is the belief in the ignorance of experts.“
–Richard P Feynman, What is Science? (1968)[1]

TruthSift.com is a platform designed to support and guide individuals or crowds to rationality, and make them smarter collectively than any unaided individual or group. (Free) Members use TruthSift to establish what can be established, refute what can’t be, and to transparently publish the demonstrations. Anyone can browse the demonstrations and learn what is actually known and how it was established. If they have a rational objection, they can post it and have it answered.

Whether in scientific fields such as climate change or medical practice, or within the corporate world or political or government debate, or on day to day factual questions, humanity hasn’t had a good method for establishing rational truth. You can see this from consequences we often fail to perceive:
Peer reviewed surveys agree: A landslide majority of medical practice is *not* supported by science [2,3,4]. Scientists are often confused about the established facts in their own field [5]. Within fields like climate science and vaccines, that badly desire consensus, no true consensus can be reached because skeptics raise issues that the majority brush aside without an established answer (exactly what Le Bon warned of more than 100 years ago[6]). Widely consulted sources like Wikipedia are reported to be largely paid propaganda on many important subjects [7], or the most popular answer rather than an established one [8]. Quora shows you the most popular individual answer, generated with little or no collaboration, and often there is little documentation of why you should believe it. Existing systems for crowd sourced wisdom largely compound group think, rather than addressing it. Existing websites for fact checking give you someone’s point of view.

Corporate or government planning is no better. Within large organizations, where there is inevitably systemic motivation to not pass bad news up, leadership needs active measures to avoid becoming clueless as to the real problems [9]. Corporate or government plans are subject to group think, or takeover by employee or other interests competing with the mission. Individuals who perceive mistakes have no recourse capable of rationally pursuading the majority, and may anyway be discouraged from speaking up by various consequences[6].

Continue reading “TruthSift: A Platform for Collective Rationality” »

MIT biological engineers have developed an algorithm for building DNA nanoparticles automatically, paving the way to many more applications for “DNA origami.”

Perhaps it’s serendipitous, then, that the machines have finally arrived. Truly smart, truly impressive robots and machine learning algorithms that may help usher in a new Green Revolution to keep humans fed on an increasingly mercurial planet. Think satellites that automatically detect drought patterns, tractors that eyeball plants and kill the sick ones, and an AI-powered smartphone app that can tell a farmer what disease has crippled their crop.

Forget scarecrows. The future of agriculture is in the hands of the machines.

A Digital Green Thumb

Continue reading “The Future of Humanity’s Food Supply Is in the Hands of AI” »

A modified version of the Drake Equation, and what it tells us.

Math isn’t everyone’s strong suit, especially those who haven’t stretched that part of their brain since college. Thanks to the wonders of image recognition technology, we now have Mathpix, an iOS app that lets you point your phone camera at a problem and calculates solutions in seconds.

The interface looks like any standard camera app: simply drag the on-screen reticle over the equation and the app solves it and provides graph answers where appropriate. More useful is a step-by-step guide offering multiple methods to reach a solution, making this a bona fide educational tool. It uses image recognition to process problems and pings its servers to do the mathematical heavy lifting, so it likely requires an internet connection to work.

Mathpix was envisioned by Stanford PhD student Nico Jimenez, who was advised by Stanford grad Paul Ferrell. The app’s other developers are high schoolers Michael Lee and August Trollback, which is impressive for an app that claims to be the first to visually recognize and solve handwritten math problems.

Continue reading “Point your phone at an equation and Mathpix will solve it” »