Summary of “DNA from old skeleton suggests humanity’s been here longer than we thought”

Anatomically modern humans have a distinct set of features that are easy to identify on a complete skeleton.
Given some measures-like the frequency of mutations and the typical time for each generation of humans to reproduce-it’s possible to use that diversity to estimate the age of the Khoe-San split at between 100,000 and 150,000 years ago.
The authors only got one decent-quality genome out of the three Stone Age bones from which they obtained DNA. But that skeleton clearly groups with the Khoe-San genetically, indicating that the researchers’ expectation about its affinities were correct.
A comparison with modern Khoe-San genomes indicated that the modern ones have gotten contributions from an additional human lineage.
How old are they? Comparing the Stone Age genome with other modern human genomes produces values of 285,000 to 365,000 years.
These estimates are very sensitive to the frequency at which new mutations arise in human lineages, as well as the typical human generation time.
The authors also point out it’s possible that the split looks older because the ancestors of the Khoe-San had interbred with a population of archaic humans, much as the ancestor of non-Africans interbred with Neanderthals.
In the big picture of human evolution, a date of roughly 300,000 years ago would place the origin of modern humans almost half way between the present and when Neanderthals and Denisovans split off from our lineage.

The orginal article.

Summary of “Is a Life Without Struggle Worth Living?”

Perhaps we can learn something about ourselves, and our political moment, by peering into Mill’s own crisis of faith.
Why on earth wouldn’t Mill want to achieve his life goals?
Mill never did abandon utilitarianism, though he later modified Bentham’s doctrine in subtle ways.
Mill is not at all clear about his line of thought here.
Perhaps Mill thought the same is true for adults – that facing a degree of “Struggle and privation” in life is essential to happiness, because it provides us with a vivid reminder of how lucky we are when we have it good.
Realistically, the work of improving human life and social conditions will never be “Done.” Still, it is easy to sympathize with Mill’s anxiety.
Did Mill, who admits to being something of a “Reasoning machine” throughout his teenage years, suddenly grow weary of mechanistic perfection? Perhaps he was disturbed by the imagined inhumanity of a world without struggle or privation – by the possibility that it might lack the romantic charms of human failure and frailty.
As Mill says, imaginative pleasures are available to “All human beings,” not just poets and philosophers.

The orginal article.

Summary of “How algorithms are transforming artistic creativity”

Human creativity was even more paramount under these conditions.
From automated essay critiques to algorithms that advise people on fashion errors and coordinating outfits, computation is changing aesthetics.
Algorithms are wonderful for extrapolating from past information, but they still lag behind human creativity when it comes to radical, interesting leaps.
How many art critiques and book reviews boil down to the judgment ‘this is a predictable extrapolation’? Newness is necessary but not sufficient for human surprise.
There is a future for human aesthetics in the modulation, the casting of surprise.
So we come to the second major opportunity for human creativity in the face of increasingly intelligent, competent and aesthetically capable machines.
In order to survive, but more importantly to thrive, in the age of algorithms, we need to cultivate a deep respect for algorithmic literacy and the capacity to ‘read’ the impact of computational influences on our work – not necessarily to resist those influences, but to understand them and use them to become better humans.
Human creativity has always been a response to the immense strangeness of reality, and now its subject has evolved, as reality becomes increasingly codeterminate, and intermingled, with computation.

The orginal article.

Summary of “Mapping’s Intelligent Agents: Autonomous Cars and Beyond”

Everything from autonomous warfare to logistics to geo-targeted advertising depends on map superiority.
Beyond those tools of looking and listening, most self-driving cars also generate a real-time map of the world.
Just as we have Siri and Google and mental maps, driverless cars tap into external sources of geospatial data.
Mobileye is attempting to speed things up by compressing new map information into a “Road Segment Data” capsule, which can be pushed between the master map in the Cloud and cars in the field.
Machine Mapping for the Rest of Us. Honestly, I don’t give a leaping Lidar about self-driving cars.
As Jer Thorp of the Office for Creative Research explained, the maps were intentionally big, to allow various physical modes of interaction: “Groups of people can gather around a map to look at it from different vantage points. People can walk across the map, experiencing distance in a meaningful way.” Shifts in scale and perspective abet a new spatial awareness.
While community mapping projects are not uncommon, the Map Room was notable for its use of projected overlays and robot assistants, which plotted fixed cartographic objects like roads and landmarks, leaving the more interpretive, aesthetic, and connotative map activity to people.
We need to recognize the world’s myriad intelligent agents not only on our maps, but also in our cartographic methods.

The orginal article.

Summary of “Corporations Have Rights. Why Shouldn’t Rivers?”

If a corporation has rights, the authors argue too, should an ancient waterway that has sustained human life for as long as it has existed in the Western United States.
The lawsuit claims the state violated the river’s right to flourish by polluting and draining it and threatening endangered species.
The lawsuit comes as hurricanes and wildfires in recent weeks have left communities across the country devastated, intensifying the debate over how humans should treat the earth in the face of global climate change.
Mr. Flores-Williams characterized the suit as an attempt to level the playing field as rivers and forests battle human exploitation.
Imbuing rivers with the right to sue, he argued, would force humans to take care of the water and trees they need to survive – or face penalties.
A court in the northern Indian state of Uttarakhand has called the Ganges and its main tributary, the Yamuna, to be living human entities.
The Colorado River cuts through or along seven Western states and supplies water to approximately 36 million people, including residents of Denver, Salt Lake City, Las Vegas, Phoenix, Tucson, San Diego and Los Angeles.
Mr. Flores-Williams is a criminal defense lawyer known for suing the city of Denver over its treatment of homeless people.

The orginal article.

Summary of “Alibaba’s Jack Ma says successful leaders need EQ, IQ, and “LQ””

Good leaders generally develop different kinds of intelligence.
“If you want to be respected, you need LQ,” said Ma, the founder and executive chairman of Chinese internet giant Alibaba, who spoke in New York today to a packed audience of CEOs and government leaders at the Bloomberg Global Business Forum.
“And what is LQ? The quotient of love, which machines never have.”
At the forum, a successor of sorts to the Clinton Global Initiative annual confab of movers and shakers, Ma said he believes humans will find solutions for the most dire issues facing global development today, including poverty, climate change, and disease, by having confidence in their imaginations and their ability to out-think machines.
Ma said the answers won’t come from people over age 50, mainly because older people tend to worry too much.
Ma, a former teacher, says he always warns government leaders to also “Pay attention to education,” because right now we’re teaching children the wrong thing: that machines are better than humans.
Rather than encouraging humans to become more like machines, we should be building our machines to be more like humans, he suggested.
“A machine does not have a heart, [a] machine does not have soul, and [a] machine does not have a belief. Human being have the souls, have the belief, have the value; we are creative, we are showing that we can control the machines,” he said.

The orginal article.

Summary of “Genetics Spills Secrets From Neanderthals’ Lost History”

These approaches paint strikingly different pictures of what Neanderthal populations would have looked like.
Some gene-based estimates put the Neanderthals’ effective population at a measly 1,000; others claim they hovered at a few thousand at most.
Working from the genetic sequences and their revised model, the researchers gleaned new insights into how Neanderthal, Denisovan and modern human populations grew, shrank, separated and periodically merged through prehistory.
Paleoanthropologists have disagreed about how they relate to other human groups, some positing they were ancestors of both modern humans and Neanderthals, others that they were a nonancestral species replaced by the Neanderthals, who spread across Europe.
“The separation time we estimate is so early that a European hominid from 600,000 years ago pretty much has to be a Neanderthal,” he said, “At least genetically, even if they didn’t look entirely like Neanderthals yet.”
Coincidentally or otherwise, this new reconstruction of the Neanderthals’ complicated early history closely resembles what we learned about the populations of anatomically modern people who first spread into Europe and Asia.
Understanding the true structure of the Neanderthal population may help scientists dig deeper and more productively into the dynamics of those ancient people and their interactions with us.
The approach could also help elucidate the evolutionary history of some genetic diseases: Neanderthal genes have been linked to increased risks of depression, diabetes, heart disease and other disorders.

The orginal article.

Summary of “The Chatbot That’s Acing the Largest Turing test in History”

As a result, personal conversations with Xiaoice can appear remarkably realistic.
Human: Hey, Xiaoice, what are you doing? Xiaoice: Chatting with you.
Human: Hey, Xiaoice, what are you doing? Xiaoice: Well, I am chatting with you while playing minesweeper and applying a facial mask.
Human: Hey, Xiaoice, what are you doing? Xiaoice: Is this the only sentence you know?
Xiaoice structures her conversations into a continuous flow of multiple tasks, different domains of knowledge, and multiple turns of chit-chat, which humans will not consciously distinguish in natural conversation.
Xiaoice means “Little Bing.” Microsoft has made many technology breakthroughs in developing its chatbot technology, such as detecting facial expressions and searching for and identifying emotional features in text.
Through the tens of billions of conversations she’s had over the past 18 months, Xiaoice has added considerably to her store of known conversational scenarios, and improved her ability to rank answer candidates.
Today, 26 percent of the data in Xiaoice’s core chat software derives from her own conversations with humans, and 51 percent of common human conversations are covered by her known scenarios.

The orginal article.

Summary of “Facebook’s war on free will”

In the hands of Google and Facebook, these algorithms grew ever more powerful.
Here’s a brief explanation for the sliver of humanity who have apparently resisted Facebook: the news feed provides a reverse chronological index of all the status updates, articles and photos that your friends have posted to Facebook.
So Facebook makes its own choices about what should be read. The company’s algorithms sort the thousands of things a Facebook user could possibly see down to a smaller batch of choice items.
Facebook’s algorithm couldn’t be more opaque.
There’s no doubting the emotional and psychological power possessed by Facebook – or, at least, Facebook doesn’t doubt it.
Facebook has even touted the results from these experiments in peer-reviewed journals: “It is possible that more of the 0.60% growth in turnout between 2006 and 2010 might have been caused by a single message on Facebook,” said one study published in Nature in 2012.
In the meantime, Facebook will keep probing – constantly testing to see what we crave and what we ignore, a never-ending campaign to improve Facebook’s capacity to give us the things that we want and things we don’t even know we want.
Facebook would never put it this way, but algorithms are meant to erode free will, to relieve humans of the burden of choosing, to nudge them in the right direction.

The orginal article.

Summary of “You Are Already Living Inside a Computer”

Its remoteness might lessen the fear of an AI apocalypse, but it also obscures a certain truth about machines’ role in humankind’s destiny: Computers already are predominant, human life already plays out mostly within them, and people are satisfied with the results.
Turing then imagined a version in which one of the players behind the door is a human and the other a machine, like a computer.
A Turing machine, and therefore a computer, is a machine that pretends to be another machine.
Like how Turing’s original thinking machine strived to pass as a man or woman, a computer tries to pass, in a way, as another thing.
Grill as computer, bike lock as computer, television as computer.
Forget Ring, the doorbell has already retired in favor of the computer.
Another take, advocated by the philosopher of mind David Chalmers and the computer scientist Ray Kurzweil, is the “Singularity,” the idea that with a sufficient processing power, computers will be able to simulate human minds.
Computers already have persuaded people to move their lives inside of them.

The orginal article.