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#431690 Oxford Study Says Alien Life Would ...

The alternative universe known as science fiction has given our culture a menagerie of alien species. From overstuffed teddy bears like Ewoks and Wookies to terrifying nightmares such as Alien and Predator, our collective imagination of what form alien life from another world may take has been irrevocably imprinted by Hollywood.
It might all be possible, or all these bug-eyed critters might turn out to be just B-movie versions of how real extraterrestrials will appear if and when they finally make the evening news.
One thing for certain is that aliens from another world will be shaped by the same evolutionary forces as here on Earth—natural selection. That’s the conclusion of a team of scientists from the University of Oxford in a study published this month in the International Journal of Astrobiology.
A complex alien that comprises a hierarchy of entities, where each lower level collection of entities has aligned evolutionary interests.Image Credit: Helen S. Cooper/University of Oxford.
The researchers suggest that evolutionary theory—famously put forth by Charles Darwin in his seminal book On the Origin of Species 158 years ago this month—can be used to make some predictions about alien species. In particular, the team argues that extraterrestrials will undergo natural selection, because that is the only process by which organisms can adapt to their environment.
“Adaptation is what defines life,” lead author Samuel Levin tells Singularity Hub.
While it’s likely that NASA or some SpaceX-like private venture will eventually kick over a few space rocks and discover microbial life in the not-too-distant future, the sorts of aliens Levin and his colleagues are interested in describing are more complex. That’s because natural selection is at work.
A quick evolutionary theory 101 refresher: Natural selection is the process by which certain traits are favored over others in a given population. For example, take a group of brown and green beetles. It just so happens that birds prefer foraging on green beetles, allowing more brown beetles to survive and reproduce than the more delectable green ones. Eventually, if these population pressures persist, brown beetles will become the dominant type. Brown wins, green loses.
And just as human beings are the result of millions of years of adaptations—eyes and thumbs, for example—aliens will similarly be constructed from parts that were once free living but through time came together to work as one organism.
“Life has so many intricate parts, so much complexity, for that to happen (randomly),” Levin explains. “It’s too complex and too many things working together in a purposeful way for that to happen by chance, as how certain molecules come about. Instead you need a process for making it, and natural selection is that process.”
Just don’t expect ET to show up as a bipedal humanoid with a large head and almond-shaped eyes, Levin says.
“They can be built from entirely different chemicals and so visually, superficially, unfamiliar,” he explains. “They will have passed through the same evolutionary history as us. To me, that’s way cooler and more exciting than them having two legs.”
Need for Data
Seth Shostak, a lead astronomer at the SETI Institute and host of the organization’s Big Picture Science radio show, wrote that while the argument is interesting, it doesn’t answer the question of ET’s appearance.
Shostak argues that a more productive approach would invoke convergent evolution, where similar environments lead to similar adaptations, at least assuming a range of Earth-like conditions such as liquid oceans and thick atmospheres. For example, an alien species that evolved in a liquid environment would evolve a streamlined body to move through water.
“Happenstance and the specifics of the environment will produce variations on an alien species’ planet as it has on ours, and there’s really no way to predict these,” Shostak concludes. “Alas, an accurate cosmic bestiary cannot be written by the invocation of biological mechanisms alone. We need data. That requires more than simply thinking about alien life. We need to actually discover it.”
Search Is On
The search is on. On one hand, the task seems easy enough: There are at least 100 billion planets in the Milky Way alone, and at least 20 percent of those are likely to be capable of producing a biosphere. Even if the evolution of life is exceedingly rare—take a conservative estimate of .001 percent or 200,000 planets, as proposed by the Oxford paper—you have to like the odds.
Of course, it’s not that easy by a billion light years.
Planet hunters can’t even agree on what signatures of life they should focus on. The idea is that where there’s smoke there’s fire. In the case of an alien world home to biological life, astrobiologists are searching for the presence of “biosignature gases,” vapors that could only be produced by alien life.
As Quanta Magazine reported, scientists do this by measuring a planet’s atmosphere against starlight. Gases in the atmosphere absorb certain frequencies of starlight, offering a clue as to what is brewing around a particular planet.
The presence of oxygen would seem to be a biological no-brainer, but there are instances where a planet can produce a false positive, meaning non-biological processes are responsible for the exoplanet’s oxygen. Scientists like Sara Seager, an astrophysicist at MIT, have argued there are plenty of examples of other types of gases produced by organisms right here on Earth that could also produce the smoking gun, er, planet.

Life as We Know It
Indeed, the existence of Earth-bound extremophiles—organisms that defy conventional wisdom about where life can exist, such as in the vacuum of space—offer another clue as to what kind of aliens we might eventually meet.
Lynn Rothschild, an astrobiologist and synthetic biologist in the Earth Science Division at NASA’s Ames Research Center in Silicon Valley, takes extremophiles as a baseline and then supersizes them through synthetic biology.
For example, say a bacteria is capable of surviving at 120 degrees Celsius. Rothschild’s lab might tweak an organism’s DNA to see if it could metabolize at 150 degrees. The idea, as she explains, is to expand the envelope for life without ever getting into a rocket ship.

While researchers may not always agree on the “where” and “how” and “what” of the search for extraterrestrial life, most do share one belief: Alien life must be out there.
“It would shock me if there weren’t [extraterrestrials],” Levin says. “There are few things that would shock me more than to find out there aren’t any aliens…If I had to bet on it, I would bet on the side of there being lots and lots of aliens out there.”
Image Credit: NASA Continue reading

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#431682 Oxford Study Says Alien Life Would ...

The alternative universe known as science fiction has given our culture a menagerie of alien species. From overstuffed teddy bears like Ewoks and Wookies to terrifying nightmares such as Alien and Predator, our collective imagination of what form alien life from another world may take has been irrevocably imprinted by Hollywood.
It might all be possible, or all these bug-eyed critters might turn out to be just B-movie versions of how real extraterrestrials will appear if and when they finally make the evening news.
One thing for certain is that aliens from another world will be shaped by the same evolutionary forces as here on Earth—natural selection. That’s the conclusion of a team of scientists from the University of Oxford in a study published this month in the International Journal of Astrobiology.
A complex alien that comprises a hierarchy of entities, where each lower level collection of entities has aligned evolutionary interests.Image Credit: Helen S. Cooper/University of Oxford.
The researchers suggest that evolutionary theory—famously put forth by Charles Darwin in his seminal book On the Origin of Species 158 years ago this month—can be used to make some predictions about alien species. In particular, the team argues that extraterrestrials will undergo natural selection, because that is the only process by which organisms can adapt to their environment.
“Adaptation is what defines life,” lead author Samuel Levin tells Singularity Hub.
While it’s likely that NASA or some SpaceX-like private venture will eventually kick over a few space rocks and discover microbial life in the not-too-distant future, the sorts of aliens Levin and his colleagues are interested in describing are more complex. That’s because natural selection is at work.
A quick evolutionary theory 101 refresher: Natural selection is the process by which certain traits are favored over others in a given population. For example, take a group of brown and green beetles. It just so happens that birds prefer foraging on green beetles, allowing more brown beetles to survive and reproduce than the more delectable green ones. Eventually, if these population pressures persist, brown beetles will become the dominant type. Brown wins, green loses.
And just as human beings are the result of millions of years of adaptations—eyes and thumbs, for example—aliens will similarly be constructed from parts that were once free living but through time came together to work as one organism.
“Life has so many intricate parts, so much complexity, for that to happen (randomly),” Levin explains. “It’s too complex and too many things working together in a purposeful way for that to happen by chance, as how certain molecules come about. Instead you need a process for making it, and natural selection is that process.”
Just don’t expect ET to show up as a bipedal humanoid with a large head and almond-shaped eyes, Levin says.
“They can be built from entirely different chemicals and so visually, superficially, unfamiliar,” he explains. “They will have passed through the same evolutionary history as us. To me, that’s way cooler and more exciting than them having two legs.”
Need for Data
Seth Shostak, a lead astronomer at the SETI Institute and host of the organization’s Big Picture Science radio show, wrote that while the argument is interesting, it doesn’t answer the question of ET’s appearance.
Shostak argues that a more productive approach would invoke convergent evolution, where similar environments lead to similar adaptations, at least assuming a range of Earth-like conditions such as liquid oceans and thick atmospheres. For example, an alien species that evolved in a liquid environment would evolve a streamlined body to move through water.
“Happenstance and the specifics of the environment will produce variations on an alien species’ planet as it has on ours, and there’s really no way to predict these,” Shostak concludes. “Alas, an accurate cosmic bestiary cannot be written by the invocation of biological mechanisms alone. We need data. That requires more than simply thinking about alien life. We need to actually discover it.”
Search is On
The search is on. On one hand, the task seems easy enough: There are at least 100 billion planets in the Milky Way alone, and at least 20 percent of those are likely to be capable of producing a biosphere. Even if the evolution of life is exceedingly rare—take a conservative estimate of .001 percent or 200,000 planets, as proposed by the Oxford paper—you have to like the odds.
Of course, it’s not that easy by a billion light years.
Planet hunters can’t even agree on what signatures of life they should focus on. The idea is that where there’s smoke there’s fire. In the case of an alien world home to biological life, astrobiologists are searching for the presence of “biosignature gases,” vapors that could only be produced by alien life.
As Quanta Magazine reported, scientists do this by measuring a planet’s atmosphere against starlight. Gases in the atmosphere absorb certain frequencies of starlight, offering a clue as to what is brewing around a particular planet.
The presence of oxygen would seem to be a biological no-brainer, but there are instances where a planet can produce a false positive, meaning non-biological processes are responsible for the exoplanet’s oxygen. Scientists like Sara Seager, an astrophysicist at MIT, have argued there are plenty of examples of other types of gases produced by organisms right here on Earth that could also produce the smoking gun, er, planet.

Life as We Know It
Indeed, the existence of Earth-bound extremophiles—organisms that defy conventional wisdom about where life can exist, such as in the vacuum of space—offer another clue as to what kind of aliens we might eventually meet.
Lynn Rothschild, an astrobiologist and synthetic biologist in the Earth Science Division at NASA’s Ames Research Center in Silicon Valley, takes extremophiles as a baseline and then supersizes them through synthetic biology.
For example, say a bacteria is capable of surviving at 120 degrees Celsius. Rothschild’s lab might tweak an organism’s DNA to see if it could metabolize at 150 degrees. The idea, as she explains, is to expand the envelope for life without ever getting into a rocket ship.

While researchers may not always agree on the “where” and “how” and “what” of the search for extraterrestrial life, most do share one belief: Alien life must be out there.
“It would shock me if there weren’t [extraterrestrials],” Levin says. “There are few things that would shock me more than to find out there aren’t any aliens…If I had to bet on it, I would bet on the side of there being lots and lots of aliens out there.”
Image Credit: NASA Continue reading

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#431678 This Week’s Awesome Stories From ...

ARTIFICIAL INTELLIGENCE
Can A.I. Be Taught to Explain Itself?Cliff Kuang | New York Times“Kosinski’s results suggested something stranger: that artificial intelligences often excel by developing whole new ways of seeing, or even thinking, that are inscrutable to us. It’s a more profound version of what’s often called the ‘black box’ problem—the inability to discern exactly what machines are doing when they’re teaching themselves novel skills—and it has become a central concern in artificial-intelligence research.”
BIOTECH
Semi-Synthetic Life Form Now Fully Armed and OperationalAntonio Regalado | MIT Technology Review “By this year, the team had devised a more stable bacterium. But it wasn’t enough to endow the germ with a partly alien code—it needed to use that code to make a partly alien protein. That’s what Romesberg’s team, reporting today in the journal Nature, says it has done.”
COMPUTING
4 Strange New Ways to ComputeSamuel K. Moore | IEEE Spectrum “With Moore’s Law slowing, engineers have been taking a cold hard look at what will keep computing going when it’s gone…What follows includes a taste of both the strange and the potentially impactful.”
INNOVATION
Google X and the Science of Radical CreativityDerek Thompson | The Atlantic “But what X is attempting is nonetheless audacious. It is investing in both invention and innovation. Its founders hope to demystify and routinize the entire process of making a technological breakthrough—to nurture each moonshot, from question to idea to discovery to product—and, in so doing, to write an operator’s manual for radical creativity.”
PRIVACY AND SECURITY
Uber Paid Hackers to Delete Stolen Data on 57 Million PeopleEric Newcomer | Bloomberg “Hackers stole the personal data of 57 million customers and drivers from Uber Technologies Inc., a massive breach that the company concealed for more than a year. This week, the ride-hailing firm ousted its chief security officer and one of his deputies for their roles in keeping the hack under wraps, which included a $100,000 payment to the attackers.”
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#431559 Drug Discovery AI to Scour a Universe of ...

On a dark night, away from city lights, the stars of the Milky Way can seem uncountable. Yet from any given location no more than 4,500 are visible to the naked eye. Meanwhile, our galaxy has 100–400 billion stars, and there are even more galaxies in the universe.
The numbers of the night sky are humbling. And they give us a deep perspective…on drugs.
Yes, this includes wow-the-stars-are-freaking-amazing-tonight drugs, but also the kinds of drugs that make us well again when we’re sick. The number of possible organic compounds with “drug-like” properties dwarfs the number of stars in the universe by over 30 orders of magnitude.
Next to this multiverse of possibility, the chemical configurations scientists have made into actual medicines are like the smattering of stars you’d glimpse downtown.
But for good reason.
Exploring all that potential drug-space is as humanly impossible as exploring all of physical space, and even if we could, most of what we’d find wouldn’t fit our purposes. Still, the idea that wonder drugs must surely lurk amid the multitudes is too tantalizing to ignore.
Which is why, Alex Zhavoronkov said at Singularity University’s Exponential Medicine in San Diego last week, we should use artificial intelligence to do more of the legwork and speed discovery. This, he said, could be one of the next big medical applications for AI.
Dogs, Diagnosis, and Drugs
Zhavoronkov is CEO of Insilico Medicine and CSO of the Biogerontology Research Foundation. Insilico is one of a number of AI startups aiming to accelerate drug discovery with AI.
In recent years, Zhavoronkov said, the now-famous machine learning technique, deep learning, has made progress on a number of fronts. Algorithms that can teach themselves to play games—like DeepMind’s AlphaGo Zero or Carnegie Mellon’s poker playing AI—are perhaps the most headline-grabbing of the bunch. But pattern recognition was the thing that kicked deep learning into overdrive early on, when machine learning algorithms went from struggling to tell dogs and cats apart to outperforming their peers and then their makers in quick succession.
[Watch this video for an AI update from Neil Jacobstein, chair of Artificial Intelligence and Robotics at Singularity University.]

In medicine, deep learning algorithms trained on databases of medical images can spot life-threatening disease with equal or greater accuracy than human professionals. There’s even speculation that AI, if we learn to trust it, could be invaluable in diagnosing disease. And, as Zhavoronkov noted, with more applications and a longer track record that trust is coming.
“Tesla is already putting cars on the street,” Zhavoronkov said. “Three-year, four-year-old technology is already carrying passengers from point A to point B, at 100 miles an hour, and one mistake and you’re dead. But people are trusting their lives to this technology.”
“So, why don’t we do it in pharma?”
Trial and Error and Try Again
AI wouldn’t drive the car in pharmaceutical research. It’d be an assistant that, when paired with a chemist or two, could fast-track discovery by screening more possibilities for better candidates.
There’s plenty of room to make things more efficient, according to Zhavoronkov.
Drug discovery is arduous and expensive. Chemists sift tens of thousands of candidate compounds for the most promising to synthesize. Of these, a handful will go on to further research, fewer will make it to human clinical trials, and a fraction of those will be approved.
The whole process can take many years and cost hundreds of millions of dollars.
This is a big data problem if ever there was one, and deep learning thrives on big data. Early applications have shown their worth unearthing subtle patterns in huge training databases. Although drug-makers already use software to sift compounds, such software requires explicit rules written by chemists. AI’s allure is its ability to learn and improve on its own.
“There are two strategies for AI-driven innovation in pharma to ensure you get better molecules and much faster approvals,” Zhavoronkov said. “One is looking for the needle in the haystack, and another one is creating a new needle.”
To find the needle in the haystack, algorithms are trained on large databases of molecules. Then they go looking for molecules with attractive properties. But creating a new needle? That’s a possibility enabled by the generative adversarial networks Zhavoronkov specializes in.
Such algorithms pit two neural networks against each other. One generates meaningful output while the other judges whether this output is true or false, Zhavoronkov said. Together, the networks generate new objects like text, images, or in this case, molecular structures.
“We started employing this particular technology to make deep neural networks imagine new molecules, to make it perfect right from the start. So, to come up with really perfect needles,” Zhavoronkov said. “[You] can essentially go to this [generative adversarial network] and ask it to create molecules that inhibit protein X at concentration Y, with the highest viability, specific characteristics, and minimal side effects.”
Zhavoronkov believes AI can find or fabricate more needles from the array of molecular possibilities, freeing human chemists to focus on synthesizing only the most promising. If it works, he hopes we can increase hits, minimize misses, and generally speed the process up.
Proof’s in the Pudding
Insilico isn’t alone on its drug-discovery quest, nor is it a brand new area of interest.
Last year, a Harvard group published a paper on an AI that similarly suggests drug candidates. The software trained on 250,000 drug-like molecules and used its experience to generate new molecules that blended existing drugs and made suggestions based on desired properties.
An MIT Technology Review article on the subject highlighted a few of the challenges such systems may still face. The results returned aren’t always meaningful or easy to synthesize in the lab, and the quality of these results, as always, is only as good as the data dined upon.
Stanford chemistry professor and Andreesen Horowitz partner, Vijay Pande, said that images, speech, and text—three of the areas deep learning’s made quick strides in—have better, cleaner data. Chemical data, on the other hand, is still being optimized for deep learning. Also, while there are public databases, much data still lives behind closed doors at private companies.
To overcome the challenges and prove their worth, Zhavoronkov said, his company is very focused on validating the tech. But this year, skepticism in the pharmaceutical industry seems to be easing into interest and investment.
AI drug discovery startup Exscientia inked a deal with Sanofi for $280 million and GlaxoSmithKline for $42 million. Insilico is also partnering with GlaxoSmithKline, and Numerate is working with Takeda Pharmaceutical. Even Google may jump in. According to an article in Nature outlining the field, the firm’s deep learning project, Google Brain, is growing its biosciences team, and industry watchers wouldn’t be surprised to see them target drug discovery.
With AI and the hardware running it advancing rapidly, the greatest potential may yet be ahead. Perhaps, one day, all 1060 molecules in drug-space will be at our disposal. “You should take all the data you have, build n new models, and search as much of that 1060 as possible” before every decision you make, Brandon Allgood, CTO at Numerate, told Nature.
Today’s projects need to live up to their promises, of course, but Zhavoronkov believes AI will have a big impact in the coming years, and now’s the time to integrate it. “If you are working for a pharma company, and you’re still thinking, ‘Okay, where is the proof?’ Once there is a proof, and once you can see it to believe it—it’s going to be too late,” he said.
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#431301 Collective Intelligence Is the Root of ...

Many of us intuitively think about intelligence as an individual trait. As a society, we have a tendency to praise individual game-changers for accomplishments that would not be possible without their teams, often tens of thousands of people that work behind the scenes to make extraordinary things happen.
Matt Ridley, best-selling author of multiple books, including The Rational Optimist: How Prosperity Evolves, challenges this view. He argues that human achievement and intelligence are entirely “networking phenomena.” In other words, intelligence is collective and emergent as opposed to individual.
When asked what scientific concept would improve everybody’s cognitive toolkit, Ridley highlights collective intelligence: “It is by putting brains together through the division of labor— through trade and specialization—that human society stumbled upon a way to raise the living standards, carrying capacity, technological virtuosity, and knowledge base of the species.”
Ridley has spent a lifetime exploring human prosperity and the factors that contribute to it. In a conversation with Singularity Hub, he redefined how we perceive intelligence and human progress.
Raya Bidshahri: The common perspective seems to be that competition is what drives innovation and, consequently, human progress. Why do you think collaboration trumps competition when it comes to human progress?
Matt Ridley: There is a tendency to think that competition is an animal instinct that is natural and collaboration is a human instinct we have to learn. I think there is no evidence for that. Both are deeply rooted in us as a species. The evidence from evolutionary biology tells us that collaboration is just as important as competition. Yet, at the end, the Darwinian perspective is quite correct: it’s usually cooperation for the purpose of competition, wherein a given group tries to achieve something more effectively than another group. But the point is that the capacity to co-operate is very deep in our psyche.
RB: You write that “human achievement is entirely a networking phenomenon,” and we need to stop thinking about intelligence as an individual trait, and that instead we should look at what you refer to as collective intelligence. Why is that?
MR: The best way to think about it is that IQ doesn’t matter, because a hundred stupid people who are talking to each other will accomplish more than a hundred intelligent people who aren’t. It’s absolutely vital to see that everything from the manufacturing of a pencil to the manufacturing of a nuclear power station can’t be done by an individual human brain. You can’t possibly hold in your head all the knowledge you need to do these things. For the last 200,000 years we’ve been exchanging and specializing, which enables us to achieve much greater intelligence than we can as individuals.
RB: We often think of achievement and intelligence on individual terms. Why do you think it’s so counter-intuitive for us to think about collective intelligence?
MR: People are surprisingly myopic to the extent they understand the nature of intelligence. I think it goes back to a pre-human tendency to think in terms of individual stories and actors. For example, we love to read about the famous inventor or scientist who invented or discovered something. We never tell these stories as network stories. We tell them as individual hero stories.

“It’s absolutely vital to see that everything from the manufacturing of a pencil to the manufacturing of a nuclear power station can’t be done by an individual human brain.”

This idea of a brilliant hero who saves the world in the face of every obstacle seems to speak to tribal hunter-gatherer societies, where the alpha male leads and wins. But it doesn’t resonate with how human beings have structured modern society in the last 100,000 years or so. We modern-day humans haven’t internalized a way of thinking that incorporates this definition of distributed and collective intelligence.
RB: One of the books you’re best known for is The Rational Optimist. What does it mean to be a rational optimist?
MR: My optimism is rational because it’s not based on a feeling, it’s based on evidence. If you look at the data on human living standards over the last 200 years and compare it with the way that most people actually perceive our progress during that time, you’ll see an extraordinary gap. On the whole, people seem to think that things are getting worse, but things are actually getting better.
We’ve seen the most astonishing improvements in human living standards: we’ve brought the number of people living in extreme poverty to 9 percent from about 70 percent when I was born. The human lifespan is expanding by five hours a day, child mortality has gone down by two thirds in half a century, and much more. These feats dwarf the things that are going wrong. Yet most people are quite pessimistic about the future despite the things we’ve achieved in the past.
RB: Where does this idea of collective intelligence fit in rational optimism?
MR: Underlying the idea of rational optimism was understanding what prosperity is, and why it happens to us and not to rabbits or rocks. Why are we the only species in the world that has concepts like a GDP, growth rate, or living standard? My answer is that it comes back to this phenomena of collective intelligence. The reason for a rise in living standards is innovation, and the cause of that innovation is our ability to collaborate.
The grand theme of human history is exchange of ideas, collaborating through specialization and the division of labor. Throughout history, it’s in places where there is a lot of open exchange and trade where you get a lot of innovation. And indeed, there are some extraordinary episodes in human history when societies get cut off from exchange and their innovation slows down and they start moving backwards. One example of this is Tasmania, which was isolated and lost a lot of the technologies it started off with.
RB: Lots of people like to point out that just because the world has been getting better doesn’t guarantee it will continue to do so. How do you respond to that line of argumentation?
MR: There is a quote by Thomas Babington Macaulay from 1830, where he was fed up with the pessimists of the time saying things will only get worse. He says, “On what principle is it that with nothing but improvement behind us, we are to expect nothing but deterioration before us?” And this was back in the 1830s, where in Britain and a few other parts of the world, we were only seeing the beginning of the rise of living standards. It’s perverse to argue that because things were getting better in the past, now they are about to get worse.

“I think it’s worth remembering that good news tends to be gradual, and bad news tends to be sudden. Hence, the good stuff is rarely going to make the news.”

Another thing to point out is that people have always said this. Every generation thought they were at the peak looking downhill. If you think about the opportunities technology is about to give us, whether it’s through blockchain, gene editing, or artificial intelligence, there is every reason to believe that 2017 is going to look like a time of absolute misery compared to what our children and grandchildren are going to experience.
RB: There seems to be a fair amount of mayhem in today’s world, and lots of valid problems to pay attention to in the news. What would you say to empower our readers that we will push through it and continue to grow and improve as a species?
MR: I think it’s worth remembering that good news tends to be gradual, and bad news tends to be sudden. Hence, the good stuff is rarely going to make the news. It’s happening in an inexorable way, as a result of ordinary people exchanging, specializing, collaborating, and innovating, and it’s surprisingly hard to stop it.
Even if you look back to the 1940s, at the end of a world war, there was still a lot of innovation happening. In some ways it feels like we are going through a bad period now. I do worry a lot about the anti-enlightenment values that I see spreading in various parts of the world. But then I remind myself that people are working on innovative projects in the background, and these things are going to come through and push us forward.
Image Credit: Sahacha Nilkumhang / Shutterstock.com

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