Links and micro-summaries from my 1000+ daily headlines. I filter them so you don't have to.
First posted on my Steem blog: SteemIt, SteemPeak*, StemGeeks.
- Characteristics, drivers and feedbacks of global greening - The planet has been getting greener - more rich with vegetation - since 1981. In some places, this is because of increases in farms and improvements in forestry, but it is also happening in places with low human footprints like deserts and tundra regions. These researchers suggest that (i) this provides compelling evidence of the existence of "climate change; (ii) the main driver of the greening is from carbon dioxide (CO2) fertilization, a long-used technique in greenhouses, whereby plants grow better when they are breathing more CO2; and (iii) the existence of more and healthier green plants will help to mitigate future effects of climate change by expanding the Earth's capability to remove CO2 from the atmosphere. -h/t Daniel Lemire
- Powerful antibiotic discovered using machine learning for first time - According to a team at MIT, halicin is the first antibiotic to be created through the use of a machine learning algorithm that was created by directing an artificial intelligence (AI) agent towards databases of existing compounds. The team also says that the antibiotic is effective against "some of the most dangerous drug-resistant bacteria, and it acts through a mechanism that is different from previous antibiotics. MIT's Regina Barzilay says that it is a first of its kind discovery, and James Collins adds that it is among the most powerful of antibiotics. The discovery was made by training the AI to find molds that would kill bacteria, based upon their atomic and molecular structure and knowledge about how effective they are at killing the E coli bacteria. The training database contained atomic and molecular information from 2500 drugs and natural compounds along with data about how effective they were at killing E coli, and the candidate database contained 6,000 compounds that are under investigation as possible treatments for a variety of diseases. In a matter of hours, the algorithm came up with halicin (name inspired by "Hal from 2001.) Next, the team turned its attention to a larger candidate database with 107 million compounds. From this pool, in a period of three days, the AI gave back a list of 23 possible antibiotics, of which two seem to be especially potent. Future plans are to run the algorithm through an even larger database, and also to tailor it towards finding antibiotics that target specific bacteria. The results were published in the journal, Cell. Jacob Durrant, an unaffiliated researcher from the University of Pittsburgh is quoted saying that the research is remarkable, and that,
Given typical drug-development costs, in terms of both time and money, any method that can speed early-stage drug discovery has the potential to make a big impact.
-h/t Communications of the ACM: Artificial Intelligence
- This Technique Uses AI to Fool Other AIs - Along with colleagues, MIT's Di Jin has developed an adversarial technique to confuse artificial intelligence (AI) text interpreters by making use of word substitution on a small portion of a text. For example, changing the sentence:
The characters, cast in impossibly contrived situations, are totally estranged from reality.
toThe characters, cast in impossibly engineered circumstances, are fully estranged from reality.
caused an AI system to switch its rating of the sentence from negative to positive. In contrast, people generally consider the two sentences to mean the same thing. The team tested their adversarial technique against a suite of popular AI algorithms and datasets, and they were able to reduce accuracy from 90% to 10%. At a time when AI is increasing in use for job candidate screening, assessing medical claims, and processing legal documents. The technique has been implemented in the TextFooler github repository. - Spells, threats, and dragons: The secret messages of Viking runestones - Jesse Byock - According to this video, the Vikings navigated from Scandanavia to European and American shores and forged new trade routes to the middle east for about 300 years, starting in the 8th century (CE). Their success is attributed to the advanced technology of their "long boats" and expertise at navigation. What they did not do, however, is leave behind monuments. Instead, archaeologists can learn about Vikings from fragments of bone, bark, and stone that can be found in graves, bogs, and sites of ancient settlements. Additionally, the Vikings also scratched runes into household goods like pottery and clothing that can still be found. Deciphering the runes is difficult, however, because of the absence of standards and regional differences in pronunciation. Many runes have been deciphered, though. Some contain evidence of their interaction with other cultures, like "love conquers all", which originated as a Latin phrase by the poet, Virgil. Others include memorials for the dead, poetry, mythology, and even magical spells that were meant to promote healing, safety in travel, or victory in battle. Although the era of viking conquest ended around the 11th century, these runes were in continued use for another 800 years.
Here is the video:
-h/t RealClearScience Videos
- Steem @indextrader24: COVID-19 Community - Pandemic information and news - discussions and background information - emerging infectious diseases - This post announces a new Steem community, Coronavirus Pandemic. The group was established in order to help people protect their health by exchanging news and background information from around the world. The introduction post is written in English and German, but the community's first couple entries are exclusively in German, so it remains to be seen whether it will be suitable for English-only speakers. (A 10% beneficiary setting has been applied to this post for @indextrader24.)
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