Lifeboat Foundation: Safeguarding Humanity
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Some argue that only a “Sputnik” moment will wake the American people and government to act with purpose, just as the 1957 Soviet launch of a satellite catalyzed new educational and technological investments. We disagree. We have been struck by the broad, bipartisan consensus in America to “get AI right” now. We are in a rare moment when challenge, urgency, and consensus may just align to generate the energy we need to extend our AI leadership and build a better future.

Congress asked us to serve on a bipartisan commission of tech leaders, scientists, and national security professionals to explore the relationship between artificial intelligence (AI) and national security. Our work is not complete, but our initial assessment is worth sharing now: in the next decade, the United States is in danger of losing its global leadership in AI and its innovation edge. That edge is a foundation of our economic prosperity, military power and ultimately the freedoms we enjoy.

As we consider the leadership stakes, we are struck by AI’s potential to propel us towards many imaginable futures. Some hold great promise; others are concerning. If past technological revolutions are a guide, the future will include elements of both.

Some of us have dedicated our professional lives to advancing AI for the benefit of humanity. AI technologies have been harnessed for good in sectors ranging from health care to education to transportation. Today’s progress only scratches the surface of AI’s potential. Computing power, large data sets, and new methods have led us to an inflection point where AI and its sub-disciplines (including machine vision, machine learning, natural language understanding, and robotics) will transform the world.

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Leaving a vulnerable system unpatched can invite troubles for an organization. The issue can turn worse when the organization suffers a cyberattack that can result in, but not limited to, compromise of confidential data, DDoS attacks or stealing of customers’ details.

According to a report released by Recorded Future, it has been found that the same vulnerabilities kept showing up year-after-year. An interesting aspect of the report was that most of these vulnerabilities were found to be exploited via phishing attacks and exploit kits that specifically target flaws in Microsoft products.

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O.o.

A physicist at the University of California, Riverside, has performed calculations showing hollow spherical bubbles filled with a gas of positronium atoms are stable in liquid helium.

The calculations take scientists a step closer to realizing a , which may have applications in , spacecraft propulsion, and .

Extremely short-lived and only briefly stable, positronium is a hydrogen-like atom and a mixture of matter and antimatter—specifically, bound states of electrons and their antiparticles called positrons. To create a gamma-ray laser beam, positronium needs to be in a state called a Bose-Einstein condensate—a collection of positronium atoms in the same , allowing for more interactions and gamma radiation. Such a condensate is the key ingredient of a gamma-ray laser.

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Amidst rising hopes for using CRISPR gene editing tools to repair deadly mutations linked to conditions like cystic fibrosis and sickle cell disease, a study in Communications Biology describes a new innovation that could accelerate this work by rapidly revealing unintended and potentially harmful changes introduced by a gene editing process.

“We’ve developed a new process for rapidly screening all of the edits made by CRISPR, and it shows there may be many more unintended changes to DNA around the site of a CRISPR repair than previously thought,” said Eric Kmiec, Ph.D., director of ChristianaCare’s Gene Editing Institute and the principle author of the study.

The study describes a new tool developed at the Gene Editing Institute that in just 48 hours can identify “multiple outcomes of CRISPR-directed gene editing,” a process that typically required up to two months of costly and complicated DNA analysis.

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Computer scientists from Duke University and Harvard University have joined with physicians from Massachusetts General Hospital and the University of Wisconsin to develop a machine learning model that can predict which patients are most at risk of having destructive seizures after suffering a stroke or other brain injury.

A point system they’ve developed helps determine which patients should receive expensive continuous electroencephalography (cEEG) monitoring. Implemented nationwide, the authors say their could help hospitals monitor nearly three times as many patients, saving many lives as well as $54 million each year.

A paper detailing the methods behind the interpretable machine learning approach appeared online June 19 in the Journal of Machine Learning Research.

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Awesome!

A new approach to programing cancer-fighting immune cells called CAR-T cells can prolong their activity and increase their effectiveness against human cancer cells grown in the laboratory and in mice, according to a study by researchers at the Stanford University School of Medicine.

The ability to circumvent the exhaustion that the genetically engineered cells often experience after their initial burst of activity could lead to the development of a new generation of CAR-T cells that may be effective even against solid cancers—a goal that has until now eluded researchers.

The studies were conducted in mice harboring human leukemia and . The researchers hope to begin in people with leukemia within the next 18 months and to eventually extend the trials to include solid cancers.

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