Credit: Pixabay.

Its not just the outside world that is shrouded in darkness at night. Scientists are making the observation that our minds are more susceptible to negative thinking during the night than in the daytime, and this could have significant consequences for our mental health. In a new study, researchers have presented this effect under the ominous name of Mind After Midnight to raise awareness and call for more research into the physiological and psychological processes that start to take over our brains deep into the night.

Unlike rats and owls, humans are not nocturnal creatures. We evolved to be diurnal, or active during the day, and this is easy to prove by studying the circadian rhythm the 24-hour cycle that determines wakefulness and sleep which, in humans, is obviously geared toward sleeping in the dark. The brain can tell when its nighttime based on the amount of light over time it detects via the eyes.

When its dark, the brain floods the body with hormones that lower blood pressure, stress levels, body temperature, and other things that generally make us sleepy and prime us for slumber. On the flip side, the morning sunshine flips chemical switches that make us more alert and wakeful.

When this natural rhythm is disrupted, such as by staying up late at night, a host of deleterious consequences can occur, including sleep disorders. Over time, it can make it hard to fall asleep and leave you constantly fatigued throughout the day, as well as affecting memory, mood, physical health, and overall function.

But while most research has focused on examining what poor nightly sleep does to us the next day, not much attention has been given to what actually happens in those instances when were wide awake in the middle of the night.

The basic idea is that from a high level, global, evolutionary standpoint, your internal biological circadian clock is tuned towards processes that promote sleep, not wakefulness, after midnight, says Elizabeth Klerman, MD, PhD, an investigator in the Department of Neurology at Massachusetts General Hospital, Professor of Neurology at Harvard Medical School and the senior author of the paper.

There are millions of people who are awake in the middle of the night, and theres fairly good evidence that their brain is not functioning as well as it does during the day, she added. My plea is for more research to look at that, because their health and safety, as well as that of others, is affected.

Klerman and colleagues reviewed a number of studies and publicly available statistics showing how staying active after dark can affect our brain systems and, in turn, our behavior. The evidence theyve gathered thus far suggests that staying awake late at night makes us more biased towards negative emotions and more prone to taking risks that may endanger our physical integrity.

For instance, suicides are much more likely to occur during nighttime hours than during the day. Homicides and other violent crimes are most common at night, as is the use of illicit drugs, as well as unhealthy eating habits like snacking on carb-rich foods in the middle of the night.

It seems like a lot of unhealthy choices come out at night to haunt us. This observation has prompted Klerman and colleagues to propose a new hypothesis called the Mind After Midnight, which argues there may be a biological basis for all of these reported nighttime negative effects.

The idea is that things like attentional biases, negative affect, altered reward processing, and prefrontal disinhibition interact to promote behavioral dysregulation and even psychiatric disorders. The researchers cite studies that show how the circadian rhythm influences neural activity over the course of 24 hours, thereby affecting our moods and the way we interact with the world. For instance, research shows that positive affect, that is the tendency to view information in a positive light, is at its highest during the morning, whereas negative affect is highest at night.

Research also shows that the human brain produces more dopamine at night, an important neurotransmitter that plays a role in many important body functions, including movement, memory, and pleasurable reward and motivation. This inflow of dopamine can hijack the reward and motivation system in the brain, making us more prone to risky and impulsive behavior, whether its snacking on a huge bucket of ice cream at 12:00 AM or shooting heroin at night after resisting the cravings during the day.

Almost everyone has probably had to face the nighttime blues at least at some point in their lives, a weird dark hour when your worldview becomes narrower and more negative. The world is suddenly much smaller than it actually is and it just sucks. Klerman herself is no exception.

While part of my brain knew that eventually I would fall asleep, while I was lying there and watching the clock go tick tick tickI was beside myself, she recalls.

Then I thought, What if I was a drug addict? I would be out trying to get drugs right now. Later I realized that this may be relevant also if its suicide tendencies, or substance abuse or other impulse disorders, gambling, other addictive behaviors. How can I prove that?

For now, the Mind After Midnight is just an unvalidated hypothesis, but a concerning one that deserves further attention. Ironically, though, in order to investigate it, there would have to be some researchers who would need to be working after midnight to supervise test subjects. This may include, for instance, taking fMRI images of the brains of volunteers with disrupted sleep cycles.

Most researchers dont want to be paged in the middle of the night. Most research assistants and technicians dont want to be awake in the middle of the night, Klerman concedes.

But we have millions of people who have to be awake at night or are awake at night involuntarily. Some of us will have to be inconvenienced so we can better prepare them, treat them, or do whatever we can to help.

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Concerning Mind After Midnight theory shows why you shouldnt stay up at night - ZME Science

Matt Higgins and his team of researchers at the University of Oxford had a problem.

For years, they had been studying the parasite that spreads malaria, a disease that still kills hundreds of thousands of people every year. They had identified an important protein on the surface of the parasite as a focal point for a potential future vaccine. They knew its underlying chemical code. But the proteins all-important 3D structure was eluding them. That shape was the key to developing the right vaccine to slide in and block the parasite from infecting human cells.

The teams best way of taking a photograph of the protein was using X-raysan imprecise tool that only returned the fuzziest of images. Without a clear 3D picture, their dream of developing truly effective malaria vaccines was just that: A dream. We were never able, despite many years of work, to see in sufficient detail what this molecule looked like, Higgins told reporters on Tuesday.

Then DeepMind came along. The artificial intelligence lab, which is a subsidiary of Googles parent company Alphabet, had set its sights on solving the longstanding grand challenge within science of accurately predicting the 3D structures of proteins and enzymes. DeepMind built a program called AlphaFold that, by analyzing the chemical makeup of thousands of known proteins and their 3D shapes, could use that information to predict the shapes of unknown proteins with startling accuracy.

When DeepMind gave Higgins and his colleagues access to AlphaFold, the team was amazed by the results. The use of AlphaFold was really transformational, giving us a really sharp view of this malaria surface protein, Higgins told reporters, adding that the new clarity had allowed his team to begin testing new vaccines that targeted the protein. AlphaFold has provided the ability to transform the speed and capability of our research.

On Thursday, DeepMind announced that it would now be making its predictions of the 3D structures of 200 million proteinsalmost all that are known to scienceavailable to the entire scientific community. The disclosure, DeepMind CEO Demis Hassabis told reporters, would turbocharge the world of biology, facilitating faster work in fields as diverse as sustainability, food security and neglected diseases. Now you can look up a 3D structure of a protein almost as easily as doing a keyword Google search, Hassabis said. Its sort of like unlocking scientific exploration at digital speed.

Read More: Demis Hassabis Is on the 2017 TIME 100

The AlphaFold project is good publicity for DeepMind, whose stated end goal is to build artificial general intelligence, or a theoretical computer that could carry out most imaginable tasks more competently and quickly than any human. Hassabis has described solving scientific challenges as necessary steps toward that end goal which, if successful, could transform scientific progress and human prosperity.

The DeepMind CEO has described AlphaFold as a gift to humanity. A DeepMind spokesperson told TIME that the company was making AlphaFolds code and data freely available for any use, commercial or academic, under irrevocable open source licenses in order to benefit humanity and the scientific community. But some researchers and AI experts have raised concerns that even if machine learning research does accelerate the pace of scientific progress, it could also concentrate wealth and power in the hands of a tiny number of companies, threatening equity and political participation in wider society.

The allure of artificial general intelligence perhaps explains why DeepMinds owner Alphabet (then known as Google), which paid more than $500 million for the lab in 2014, has historically allowed it to work on areas it sees as beneficial to humanity as a whole, even at great immediate cost to the company. DeepMind ran at a loss for years, with Alphabet writing off $1.1 billion of debt incurred from those losses in 2019, but it turned a modest profit of $60 million for the first time in 2020. That profit came entirely from selling its AI to other arms of the Alphabet empire, including tech that improves the efficiency of Googles voice assistant, its Maps service, and the battery life on its Android phones.

The combination of masses of data and computing power, combined with powerful methods for spotting patterns known as neural networks, are fast transforming the scientific landscape. These technologies, often described as artificial intelligence, are helping scientists in fields as diverse as understanding the evolution of stars and boosting drug discovery.

But this transformation isnt without its risks. In a recent study, researchers for a drug discovery company said that with only small tweaks, their drug discovery algorithm could generate toxic molecules like the VX nerve agentand others, unknown to science, that could be even more deadly. We have spent decades using computers and AI to improve human healthnot to degrade it, the researchers wrote. We were naive in thinking about the potential misuse of our trade.

For its part, DeepMind says it has carefully considered the risks of releasing the AlphaFold database to the public, saying it had made the decision after consulting with more than 30 experts in bioethics and security. The assessment came back saying that [with] this release, the benefits far outweigh any risks, Hassabis, DeepMinds CEO, told TIME at a briefing with reporters on Tuesday.

Hassabis added that DeepMind had made some adjustments in response to the risk assessment, to be careful with the structure of viral proteins. A DeepMind spokesperson later clarified that viral proteins had been excluded from AlphaFold for technical reasons, and that the consensus among experts was that AlphaFold would not meaningfully lower the barrier to entry for causing harm with proteins.

The risks of making it possible for anybody to determine the 3D structure of a protein are far lower than the risk of allowing anybody access to a drug discovery algorithm, according to Ewan Birney, the director of the European Bioinformatics Institute, which partnered with DeepMind on the research. Even if AlphaFold were to facilitate a bad actor to design a dangerous compound, the same technology in the hands of the scientific community at large could be a force-multiplier for efforts to design antidotes or vaccines. I think, like all risks, you have to think about the balance here and the positive side, Birney told reporters Tuesday. The accumulation of human knowledge is just a massive benefit. And the entities which could be risky are likely to be a very small handful. So I think we are comfortable.

But DeepMind acknowledges the balance of risks may play out differently in the future. Artificial intelligence research has long been characterized by a culture of openness, with researchers at competing labs often sharing their source code and results publicly. But Hassabis indicated to reporters on Tuesday that as machine learning makes greater headway into other potentially more-risky areas of science, that open culture may need to narrow. Future [systems], if they do carry risks, the whole community would need to consider different ways of giving access to that systemnot necessarily open sourcing everythingbecause that could enable bad actors, Hassabis said.

Open-sourcing isnt some sort of panacea, Hassabis added. Its great when you can do it. But there are often cases where the risks may be too great.

More Must-Read Stories From TIME

Write to Billy Perrigo at billy.perrigo@time.com.

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DeepMind AI Lab Releases 200 Million 3D Images of Proteins - TIME

Since their 2017 debut as a novel approach to natural language processing (NLP), transformers have achieved epoch-making performance across an increasingly wide variety of tasks and fields and are now the architecture of choice for many academic and industry machine learning researchers and practitioners. Countless papers have been published on transformers and new and improved variants, but these rarely if ever include pseudocode a simplified outline of a models operations formatted similarly to computer source code but with plain-language annotations.

In the new paper Formal Algorithms for Transformers, DeepMind researchers present a precise and compact overview of transformer architectures and formal algorithms. The unique study provides pseudocode for 15 transformer algorithms, along with explanations of what transformers are, how they are trained, what theyre used for, their key architectural components, tokenization, and practical considerations for prominent models.

The researchers introduce transformers as neural networks for sequential data that, in most cases, are used for two common tasks: sequence modelling and sequence-to-sequence prediction. They detail formal algorithms for both tasks and provide pseudocode that can be used as templates and adapted to describe future variations. An explanation of the main approaches for tokenization is also included to offer readers insights on how text is represented in such models.

The researchers present formal algorithms for the key components of transformer architectures, including token and positional embedding, basic single-query attention (e.g. bidirectional self-attention and unidirectional self-attention), multi-head attention, layer normalization, and unembedding; and detail prominent transformer architectures such as the Encoder-Decoder Transformer, BERT, and GPT. The team notes that pseudocodes representations for reasoning can also benefit theoreticians interested in transformers and deep learning.

Overall, this paper neatly describes all aspects of transformer architectures, training, and inference; provides pseudocode for various algorithms used in their training and deployment; and includes a useful notation glossary. The researchers hope the work can provide readers of various levels with a better understanding of transformers and enable them to contribute to the literature on the topic; and aid developers in the implementation of their own transformer models by using the pseudocode as templates.

The paper Formal Algorithms for Transformers is on arXiv.

Author: Hecate He |Editor: Michael Sarazen

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DeepMind Paper Provides a Mathematically Precise Overview of Transformer Architectures and Algorithms - Synced

By Deidre Freitas In the mid 90s, there were three different Justice League teams, all run by separate leaders. They had all disagreed on the best way to lead The League, so they split up. Why and how was this possible? Sticking with tried and true comic book logic, I can only say that its just how it was.

Extreme Justice was one of these teams (even though the team never referred to themselves as extreme justice on the page), with a 19-issue run that started in November 94 and wrapped up in May of 96. This team was led by Captain Atom, who disagreed with how Wonder Woman wanted to work with the United Nations, claiming that the UN was too slow to let the heroes help people in need, so he and his team set out to do things differently.

Captain Atom in this era of comics was an act first, think later kind of guy. After his solo run and a stint leading Justice League Europe, he had no love for the government that had betrayed and tricked him into becoming a hero. Instead, he became a hero on his own terms. With the team of Blue Beetle II, Booster Gold, Maxima, The Amazing Man (Will Everett III), Firestorm (Ronnie Raymond), and eventually the Wonder Twins, Atom and his crew would go on to save the planet from several world-shattering events, over the course of the 19 total Extreme Justice issues.

This series seems to get overlooked, with the most common complaint I could find amongst fans being that it has an inconsistent art style (although Ken Branch inking and Lee Loughridge coloring the full run provide some consistency). Its true that six different artists pencil this run, but really, Im more impressed with how the series had multiple writers (four, to be exact), and still seemed to keep hold of its main storylines throughout its run.

Its certainly not perfect, not even close, and personally, my biggest issue was that Maxima (the only woman on the team until Jayna joins about halfway through) was only ever used as a love-interest. Her first major conflict with the team came when she seemed to fabricate a flirtation between herself and Captain Atom and was upset when he decided to rekindle things with his then ex-girlfriend Plastique, aka Bette Sans Souci.

Looking past that bad romantic subplot, it did make me laugh when the second issue ended with Captain Atom blowing up (like he always does) and an editors note saying sorry about killing one of your favs, but well probably do it again. We should bring back these sassy-but-happy editors notes. Especially when its in reference to a character like Atom, whos blown up more times than I can count, and always comes back.

Anyway, much of Extreme Justice focuses on Captain Atom trying to come to terms with how he acted under the governments thumb, and trying to reconcile that with who he is now that hes free. And naturally, when we have a main character in an identity crisis (sorry!), we have to throw another wrench in their inevitable self-actualization. In this case, the main villain of the story, the newest version of Monarch, reveals himself to be the real Nathaniel Adams, explaining that the Captain Atom everyone has come to know since his accident in the 60s is just a clone of the original man.

Maxima, whose powers included telepathy, helped Atom look deeper into Monarchs mind to see Nates own memories about his wife and children. This leads Atom to believe Monarch really is telling the truth, and hes nothing but a metallic copy of the original man. Maxima doesnt seem to be entirely convinced, but they are both booted from Monarchs mind before she can draw her own conclusions.

Regardless, Captain Atom tells everyone to call him by the name Cameron Scott only, and breaks off his rushed engagement to Plastique, claiming he needs to figure out who he is outside of the life he thought was his own.

One thing about this series is that it seems to be discarded as a byproduct of the 90s, and its certainly of its time, from its Extreme label to the outfits, hairstyles and even mannerisms of the characters. But beneath the lingo and fashion choices, there are some genuinely good storylines in this book.

Booster Gold, who had nearly died at the end of Justice League America, is kept alive by a suit that Blue Beetle made him. He lost an arm, and his vitals are only stable because of the alien technology surrounding his body. For all intents and purposes, Booster is disabled for much of this run. Several times in the series he questions his own usefulness, wondering if all of this is worth it. Booster even goes after his former manager, spiraling into a dark depression and anger because the man embezzled all of his money.

Its interesting to see Booster so down-trodden, especially when he seems to be more popular than ever with the public at this time. And with modern writing of him emphasizing how much he craves the attention and glory of people seeing him as a real hero, it just adds an extra layer of interesting tragedy. He is at his core still the man who wanted to go back in time and become an immortalized hero, just like the ones in the museum where he used to work. And instead of appreciating all the people who did see him as a Justice Leaguer and real force for good, his judgment gets clouded by his resentment for his former manager.

At his lowest point, Booster takes up Monarchs offer to heal him and rid him of his chronic pain and failing machinery. Things seem fine, before it is revealed he was implanted with something to make his mind go haywire, and turn him into some sort of mechanical monster. But hes saved by the League, and gets a new suit that has Skeets as a mainframe.

Despite it all, its important to remember that the Justice League was never a perfect group. They definitely get mythologized, but in the best runs, Leagues have always had their flaws, be it the original seven, or a hodge-podge of other heroes just trying to do good, as seen in this run at times. What made them a team was their ability to lift one another up, and be there when another fell. Oftentimes, it feels like people dont consider a team to be the real League unless one of the Trinity is present. But runs like this one show that not only can the League exist without one of them, it can still tell interesting, character-drive stories..

Extreme Justice is both a literal and spiritual successor to Justice League International/Justice League America in that it was published right after that run and also the team isnt made of well-known heroes. The membership here werent the A-listers people expect, but they were heroes in their own right. And even the biggest names on the team had their own struggles holding them back, making them question their involvement in the League.

The series may have only lasted a year and a half, but it had the spirit of The League, and if youre looking for a DC Deep Cut to revisit, you can do a lot worse than these 19 issues.

Extreme Justice #0 #18Writers:Dan Vado, Charlie Bracey, Ivan Velez Jr.,andRobert WashingtonArtists:Marc Campos, Mozart Cuoto, Al Rio, Pasqual Ferry, Tom Morgan,and Chris GardnerInker: Ken BranchColorist: Lee LoughridgeLetterer: Kevin Cunningham

Deidre Freitas is a pop culture lover and resident theatre kid whos sometimes funny on Twitter as @deidrefrittatas.

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DC DEEP CUTS: Extreme Justice is very 90s, yet worth a revisit - Comics Beat

With the release of theJames Webb Space Telescope's first images on July 12 (and asneaky reveal by US President Joe Biden on July 11), NASA, ESA and the Canadian Space Agency proved that the $10 billion, 1-million-miles-from-Earth, two-decades-in-the-making dream 'scope actually works. And it works flawlessly. Just take a look at theupgraded visuals Webb delivered over its predecessor, Hubble. They're visceral masterpieces that force us to think of the universe's magnificence and reflect on our solar system's negligible corner within.

But what we saw in early July was only the preface of JWST's book. It'll be the chapters that follow which will write out its legacy.

Even though the telescope's first full-color results were excellent, they're merely a taste of the instrument's capabilities. In truth, we may not even have words to describe what's to come, in the way the Hubble Space Telescope's first light image couldn't foreshadow the astounding deep fields that would one day plaster astronomy department walls or the nebulas that would inspire poetry.

Five galaxies locked in a dance make up Stephan's Quintet. Images by the JWST released on July 12, 2022.

But we might be able to infer some scenes of JWST's future because, despite this telescope's public recency, scientists have been lining up for years to use it.

Already, researchers are set to point it at phenomena that'll blow your mind: massive black holes, shattering galaxy mergers, luminescent binary stars emanating smoke signals, and even marvels closer to home like Ganymede, an icy moon of Jupiter.

More specifically, a lucky first few scientists hold proposals divided into six categories, each meticulously selected by the James Webb Space Telescope Advisory Committee and the Space Telescope Science Institute in November 2017 -- not to mention the more than 200 international projects separately awarded time on the telescope and those ready to join the waitlist.

But the initial cadre of JWST space explorers is meant to be a win-win for both scientist and 'scope. These studies will create datasets, baselines, handy life hacks and just generally prime the powerful machine's instruments for everything that comes next. For the big moments that'll go down in history.

An artist's conception of the James Webb Space Telescope.

"To realize the James Webb Space Telescope's full science potential, it is imperative that the science community quickly learns to use its instruments and capabilities," says a page aboutthe Director's Discretionary-Early Release Science Programs, which was put together to pick out which investigators will test out JWST for its first 5 months of science operations (following the 6-month telescope commissioning period).

Perusing the list has heightened my anticipation -- and I bet it'll elevate yours, too.

Here's a snippet.

Some 3.5 billion light-years from Earth lies an enormous cluster of galaxies called Abell 2744, also known as Pandora's Cluster.

One might say this is the perfect starting candidate for JWST, as it's part of the ancient, faraway universe. NASA's next-gen telescope contains a wealth of infrared imaging equipment that can access light emanating from the distant cosmos-- light neither human eyes nor standard optical telescopes can see. It's a science exploration match made in heaven.

Thus, a crew of investigators plans to observe what's going on in this brilliant galaxy cluster, hidden to human vision but vital to astrophysical advancement.

Abell 2744, imaged by combining X-rays from Chandra (diffuse blue emission) with optical light data from Hubble (red, green and blue).

They plan on using two of JWST's instruments, called the Near-Infrared Spectrograph and the Near Infrared Imager and Slitless Spectrograph, both of which can simply decode chemical composition of faraway worlds stuck in the infrared zone we can't trespass.

But JWST isn't merely farsighted. It can turn on its reading glasses to scan nearby things, too.

That's why another team is more interested in figuring out how to navigate phenomena in our very own cosmic neighborhood. Their blueprints say they'll characterize Jupiter's cloud layers, winds, composition, temperature structure and even auroral activity -- aka, the Jovian version of our northern lights.

This research bit is poised to use nearly all of JWST's groundbreaking infrared equipment: Nirspec, Niriss, as well as the Near-Infrared Camera -- JWST's alpha imager -- and the Mid-Infrared Camera (MIRI), which, as you might guess, specializes in mid-infrared light detection. "Our program will thus demonstrate the capabilities of JWST's instruments on one of the largest and brightest sources in the solar system and on very faint targets next to it," they write in their abstract.

Some of the work on Jupiter has already been performed according to the status report for the project and observation windows continue into August. In addition, Jupiter's moon Ganymede, which is the largest in the solar system, and the extremely active Io, are also set to be examined with MIRI. The latter is particularly interesting, as the researchers hope to resolve Io's volcanoes and compare Webb's views to classical views.

Jupiter, center, and its moon Europa, left, are seen through the James Webb Space Telescope's NIRCam instrument 2.12 micron filter.

Next up are the scientists focused on dust. But not just any dust. Stardust.

We know dust is the main ingredient in the formation of stars and planets that decorate our universe, but we're still foggy on the timeline they followed to bring us where we are today -- especially because a lot of that crucial-to-our-existence dust is scattered in the early universe. And the early universe is illuminated purely by infrared light.

Aha. Precisely what JWST can -- and will -- delve into.

Breaking down the story of stardust means constructing an understanding of the building blocks of our cosmic universe -- similar to how studying atoms opens up knowledge about chunks of matter. And as Carl Sagan once said, "The cosmos is within us. We are made of star-stuff. We are a way for the universe to know itself."

Perhaps JWST can aid the universe in its quest to introspect.

Over the past many months in general, as a science writer I've witnessed the repetition of one striking sentiment. "Just wait until the James Webb Space Telescope sees this."

Not in those words, exactly, but definitely with that tone.

In April, for instance, the Hubble Space Telescope hit a record-breaking milestone when it delivered to us an image of the farthest star we've ever seen from the distant universe. A stellar beauty named Earendel, which aptly translates to "morning star" in Old English.

"Studying Earendel will be a window into an era of the universe that we are unfamiliar with, but that led to everything we do know," Brian Welch, one of the discovery astronomers from Johns Hopkins University, said in a statement.

Earendel (indicated with arrow) is positioned along a ripple in spacetime that gives it extreme magnification, allowing it to emerge into view from its host galaxy, which appears as a red smear across the sky.

But remember how JWST is armed to study the ancient, invisible universe? Exactly. The study authors are prepared to look at Earendel with JWST's lens, hopefully confirm whether it really is just one stellar body and quantify what kind of dawning star it is.

JWST could also solve a mysterious puzzle posed by Neptune, our solar system's gassy blue ornament: It's getting colder for no apparent reason. But "the exquisite sensitivity of the space telescope's mid-infrared instrument, MIRI, will provide unprecedented new maps of the chemistry and temperatures in Neptune's atmosphere," Leigh Fletcher, co-author of a study on the mystery, and planetary scientist at the University of Leicester, said in a statement.

There's also the intrigue of decoding our cosmic realm's violent majesties: supermassive black holes -- and even an odd, multibillion-year-old, burgeoning black hole ancestor.

"Webb will have the power to decisively determine how common these rapidly growing black holes truly are," Seiji Fujimoto, one of the discovery astronomers from the Niels Bohr Institute of the University of Copenhagen, said in a statement.

And finally, I'd say the most mind-boggling aspect of JWST -- to me, at least -- is that it's currently the best shot we have at finding proof of extraterrestrial life. Aliens.

Some scientists are even prematurely guarding against false positives of organic matter that JWST's software might pick up, so as not to alarm the general public (me) when that day comes. But if that day comes, our jaws will undoubtedly drop to the ground and our heart rate will pick up, unambiguously deeming July 12 a mild memory.

And even if that day doesn't arrive, it won't be long until NASA's new space exploration muse sends back an image as field-altering as the Hubble's first deep field in 1995-- one we can't yet fathom.

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The James Webb Space Telescope's Next Targets Are Potentially Mind-Blowing - CNET