Lifeboat Foundation

The bottomless bucket is Karl Marx’s utopian creed: “From each according to his ability, to each according to his needs.” In this idyllic world, everyone works for the good of society, with the fruits of their labor distributed freely — everyone taking what they need, and only what they need. We know how that worked out. When rewards are unrelated to effort, being a slacker is more appealing than being a worker. With more slackers than workers, not nearly enough is produced to satisfy everyone’s needs. A common joke in the Soviet Union was, “They pretend to pay us, and we pretend to work.”

In addition to helping those who in the great lottery of life have drawn blanks, governments should adopt myriad policies that expand the economic pie, including education, infrastructure, and the enforcement of laws and contracts. Public safety, national defense, dealing with externalities are also important. There are many legitimate government activities and there are inevitably tradeoffs. Governing a country is completely different from playing a simple, rigged distribution game.

I love computers. I use them every day — not just for word processing but for mathematical calculations, statistical analyses, and Monte Carlo simulations that would literally take me several lifetimes to do by hand. Computers have benefited and entertained all of us. However, AI is nowhere near ready to rule the world because computer algorithms do not have the intelligence, wisdom, or commonsense required to make rational decisions.

The potential to disseminate disinformation on a large scale and undermine scientifically established facts represents an existential risk to humanity. While vigorously defending the right to freedom of expression everywhere, higher education institutions must also develop the capacity to reach a shared, empirically backed consensus based on facts, science and established knowledge.

New research provides evidence that high intensity interval training improves metabolism in a brain structure responsible for memory formation and retention. The study, published in Psychophysiology, found increased metabolism in the left hippocampus following a 6-month physical activity intervention for adolescents.

“The primary focus of my research is the design, evaluation, and dissemination of school-based physical activity interventions,” said David Lubans, a professor at the University of Newcastle and the corresponding author of the study.

“My secondary area of interest is studying the effects and mechanisms of physical activity on young people’s mental health and cognition. I have found that providing evidence for the benefits of physical activity for academic outcomes, including test performance, cognitive function and on-task behavior in the classroom provides a strong impetus for schools to provide additional activity for young people.”

The story of future video games starts when artificial intelligence takes over building the games for players — while they play them. And human brains are mapped by virtual reality headsets.

This sci fi documentary also covers A.I. npc characters, Metaverse scoreboards, brain to computer chips and gaming, Elon Musk and Neuralink, and the simulation hypothesis.

Continue reading “Timelapse of Future Gaming Worlds (2030 & Beyond)” »

In today’s business world, machine-learning algorithms are increasingly being applied to decision-making processes, which affects employment, education, and access to credit. But firms usually keep algorithms secret, citing concerns over gaming by users that can harm the predictive power of algorithms. Amid growing calls to require firms to make their algorithms transparent, a new study developed an analytical model to compare the profit of firms with and without such transparency. The study concluded that there are benefits but also risks in algorithmic transparency.

Conducted by researchers at Carnegie Mellon University (CMU) and the University of Michigan, the study appears in Management Science.

“As managers face calls to boost transparency, our findings can help them make decisions to benefit their firms,” says Param Vir Singh, Professor of Business Technologies and Marketing at CMU’s Tepper School of Business, who coauthored the study.

No homework. Grades you can change. This school is challenging everything about our approach to education — and it’s working with a 98% college acceptance rate.

This artificial intelligence software can acutely analyze facial expressions and brain waves to monitor if subjects were attentive to thought and political education by using a combination of polygraphs and facial scans. It can provide real data for organizers of ideological and political education, so they can keep improving their methods of education and enrich content. It can judge how party members have accepted thought and political education.

The Smart Political Education Bar analyses user’s brain waves and deploys facial recognition to discern the level of acceptance for ideological and political education. Making it possible to ascertain the levels of concentration, recognition, and mastery of ideological and political education so as to better understand its effectiveness.

President Xi, secretary of the Communist Party and leader of the nation of 1.4 billion, has demanded absolute loyalty to the party and has previously declared that thought and political education is an essential part of the government’s doctrine. They are using this technology to treat all party members as potential anti-CCP agents. The use of these techniques on officials demonstrates the sorry state of affairs within party ranks.

In a now-deleted video, researchers reportedly said the software could analyze citizens’ reactions to “thought and political education.”

Circa 2021

Finding and fixing bugs in code is a time-consuming, and often frustrating, part of everyday work for software developers. Can deep learning address this problem and help developers deliver better software, faster? In a new paper, Self-Supervised Bug Detection and Repair, presented at the 2021 Conference on Neural Information Processing Systems (NeurIPS 2021), we show a promising deep learning model, which we call BugLab can be taught to detect and fix bugs, without using labelled data, through a “hide and seek” game.

To find and fix bugs in code requires not only reasoning over the code’s structure but also understanding ambiguous natural language hints that software developers leave in code comments, variable names, and more. For example, the code snippet below fixes a bug in an open-source project in GitHub.

Continue reading “Finding and fixing bugs with deep learning” »