Dark Emuby Bruce Pascoe is a powerful, compelling work that achieves its dual aims: showing just how complex and well-developed the civilisation managing the Australian continent was prior to European contact and subsequent colonisation, and the lengths that have been gone to erase this vital pre-history from the collective minds of the current occupying Australian civilisation.
There’s a family of interesting related arguments:— Venkatesh Rao (@vgr) March 9, 2019
“You are not enough people” (Vonnegut theory of marital conflict)
“Reality has a surprising amount of detail” (John Salvatier theory of physical reality)
“Everything is harder than it looks” (David Wong theory of effort shock)
Inexplicably I’ve accepted the challenge by @akrishnan23 to post the covers of 7 books that I love/recommend: no explanations, no reviews. With each post I’ll ask another to succumb to the challenge. 1 book cover a day for a week, and for my 1st day I tag in @honorharger. pic.twitter.com/epBbagVRlj— Scott Smith (@changeist) March 9, 2019
The increasing level of amazingly outlandish untruths being accepted might eventually lead to the possibility of talking about actual truth.— Yaneer Bar-Yam (@yaneerbaryam) March 8, 2019
A couple of weeks ago, I wrote about GPT-2, a text-generating algorithm whose huge size and long-term analysis abilities mean that it can generate text with an impressive degree of coherence. So impressive, in fact, that its programmers at OpenAI have only released a mini version of the model for now, worried that people may abuse the full-size model’s easy-to-generate, almost-plausibly-human text.
(below: some text generated by mini-GPT-2, in response to the prompt in italics)
This was a fantastic recipe for chocolate cake with raspberry sauce! I only made a couple of changes to the recipe. First, Iadded vanilla candles instead of meringues for a more mild and exotic fragrance. Once again, I only used 1 tsp of vanilla syrup for clarity. Second, the chocolate cake whipped cream was tempered by an additional 1 tsp of canola oil. The regular vegan whipped cream is soothing and makes it pleasing to the hungry healthiest person I know!
In the meantime, as OpenAI had hoped, people are working on ways to automatically detect GPT-2′s text. Using a bot to detect another bot is a strategy that can work pretty well for detecting fake logins, video, or audio. And now, a group from MIT-IBM Watson AI lab and Harvard NLP has come up with a way of detecting fake text, using GPT-2 itself as part of the detection system.
The idea is fairly simple: GPT-2 is better at predicting what a bot will write than what a human will write. So if GPT-2 is great at predicting the next word in a bit of text, that text was probably written by an algorithm - maybe even by GPT-2 itself.
There’s a web demo that they’re calling Giant Language model Test Room (GLTR), so naturally I decided to play with it.
First, here’s some genuine text generated by GPT-2 (the full-size model, thanks to the OpenAI team being kind enough to send me a sample). Green words are ones that GLTR thought were very predictable, yellow and red words are less predictable, and purple words are ones the algorithm definitely didn’t see coming. There are a couple of mild surprises here, but mostly the AI knew what would be generated. Seeing all this green, you’d know this text is probably AI-generated.
Here, on the other hand, is how GLTR analyzed some human-written text, the opening paragraph of the Murderbot diaries. There’s a LOT more purple and red. It found this human writer to be more unpredictable.
But can GLTR detect text generated by another AI, not just text that GPT-2 generates? It turns out it depends. Here’s text generated by another AI, the Washington Post’s Heliograf algorithm that writes up local sports and election results into simple but readable articles. Sure enough, GLTR found Heliograf’s articles to be pretty predictable. Maybe GPT-2 had even read a lot of Heliograf articles during training.
However, here’s what it did with a review of Avengers: Infinity War that I generated using an algorithm Facebook trained on Amazon reviews. It’s not an entirely plausible review, but to GLTR it looks a lot more like the human-written text than the AI-generated text. Plenty of human-written text scores in this range.
And here’s how GLTR rated another Amazon review by that same algorithm. A human might find this review to be a bit suspect, but, again, the AI didn’t score this as bot-written text.
What about an AI that’s really, really bad at generating text? How does that rate? Here’s some output from a neural net I trained to generate Dungeons and Dragons biographies. Whatever GLTR was expecting, it wasn’t fuse efforts and grass tricks.
But I generated that biography with the creativity setting turned up high, so my algorithm was TRYING to be unpredictable. What if I turned the D&D bio generator’s creativity setting very low, so it tries to be predictable instead? Would that make it easier for GLTR to detect? Only slightly. It still looks like unpredictable human-written text to GLTR.
GLTR is still pretty good at detecting text that GPT-2 generates - after all, it’s using GPT-2 itself to do the predictions. So, it’ll be a useful defense against GPT-2 generated spam.
But, if you want to build an AI that can sneak its text past a GPT-2 based detector, try building one that generates laughably incoherent text. Apparently, to GPT-2, that sounds all too human.
For more laughably incoherent text, I trained a neural net on the complete text of Black Beauty, and generated a long rambling paragraph about being a Good Horse. To read it, and GLTR’s verdict, enter your email here and I’ll send it to you.
For several years, I’ve been covering the bizarre phenomenon of “adversarial examples (AKA “adversarial preturbations”), these being often tiny changes to data than can cause machine-learning classifiers to totally misfire: imperceptible squeaks that make speech-to-text systems hallucinate phantom voices; or tiny shifts to a 3D image of a helicopter that makes image-classifiers hallucinate a rifle
A friend of mine who is a very senior cryptographer of longstanding esteem in the field recently changed roles to managing information security for one of the leading machine learning companies: he told me that he thought that it may be that all machine-learning models have lurking adversarial examples and it might be impossible to eliminate these, meaning that any use of machine learning where the owners of the system are trying to do something that someone else wants to prevent might never be secure enough for use in the field – that is, we may never be able to make a self-driving car that can’t be fooled into mistaking a STOP sign for a go-faster sign.
What’s more there are tons of use-cases that seem non-adversarial at first blush, but which have potential adversarial implications further down the line: think of how the machine-learning classifier that reliably diagnoses skin cancer might be fooled by an unethical doctor who wants to generate more billings; or nerfed down by an insurer that wants to avoid paying claims.
My MIT Media Lab colleague Joi Ito (previously) has teamed up with Harvard’s Jonathan Zittrain (previously to teach a course on Applied Ethical and Governance Challenges in AI, and in reading the syllabus, I came across Motivating the Rules of the Game for Adversarial Example Research, a 2018 paper by a team of Princeton and Google researchers, which attempts to formulae a kind of unified framework for talking about and evaluating adversarial examples.
The authors propose a taxonomy of attacks, based on whether the attackers are using “white box” or “black box” approaches to the model (that is, whether they are allowed to know how the model works), whether their tampering has to be imperceptible to humans (think of the stop-sign attack – it works best if a human can’t see that the stop sign has been altered), and other factors.
It’s a fascinating paper that tries to make sense of the to-date scattershot adversarial example research. It may be that my cryptographer friend is right about the inevitability of adversarial examples, but this analytical framework goes a long way to helping us understand where the risks are and which defenses can or can’t work.
If this kind of thing interests you, you can check out the work that MIT Media Lab students are doing with Labsix, a student-only, no-faculty research group that studies adversarial examples.
The Emojipedia blog has an important update in emoji history news!
Until now, Japanese phone carrier Docomo has most often been widely credited as the originator of what we know as emoji today. It turns out, that might not be the case, and today we are correcting the record.
SoftBank, the carrier that partnered with Apple to bring the iPhone to Japan in 2008, released a phone with support for 90 distinct emoji characters in 1997. For the first time, these are now available on Emojipedia.
The 90 emojis from SoftBank in 1997 predate the set of 176 emojis released by Docomo in 1999, which until now have most commonly been cited (including by Emojipedia) as being the first.
Not only was the 1997 SoftBank emoji set released earlier than the first known date of the Docomo emoji set (in “1998 or 1999”), one of the most iconic emoji characters now encoded as 💩 U+1F4A9 PILE OF POO in the Unicode Standard, originated in this release.
Unless or until we find evidence that Docomo had an emoji set available prior to this release, we hereby issue a correction that the original emoji set is from SoftBank in Japan in 1997, with designer/s unknown.
There exists a series of underground bunkers with no entrances or exits of any kind scattered across North America, each of which contains nothing but art exhibits; together, these form an exclusive museum available only to remote viewers.— uel aramchek (@ThePatanoiac) March 8, 2019
ONLY THE BEGINNING OF ANOTHER STRANGENESS - what happens when AI meets the alien consciousnesses that already live amongst us? I got to write about something that’s been on my mind for a while, for the @BarbicanCentre’s Life Rewired season https://t.co/sqkZrkpXjL pic.twitter.com/0lbDhiO47x— James Bridle (@jamesbridle) March 7, 2019
I’m in the non-apocalyptic camp of climate change believers. I don’t believe even the worst case will make the world uninhabitable. Let’s say that’s a 5% likelihood scenario of maybe 90% species loss and even 90% human population decline. But what do those numbers *mean*?— Venkatesh Rao (@vgr) March 7, 2019
I am SO thrilled to announce Atmospheric Memory, an epic new production by Rafael Lozano Hemmer (@errafael) curated by @FuturEverything, premiering at @MIFestival on July 4. 5 years in the making, it’s the most groundbreaking and complex exhibition project I’ve ever done #MIF19 pic.twitter.com/1SGvFvPjCo— Jose Luis de Vicente (@Macroscopist) March 7, 2019
The meaning of this GIF changes when you realize that Kermit is in the Black Lodge with Dale Cooper … pic.twitter.com/HNEyuapqyj— Weird Studies (@weirdstudies) March 6, 2019
FRACTAL LOCALISM— Nassim Nicholas Taleb (@nntaleb) March 6, 2019
Defining complexity and selforganization before explaining socioeconomic LOCALISM pic.twitter.com/ogO0MC4Nmi
AI-created fine art could enliven galleries with visual aesthetics that humans couldn’t foresee, or it could become a self-contained, VC-funded machine-learning Thomas Kinkade automaton for hotel-room decor. Or it could do both.https://t.co/QoUAJK4t36— Ian Bogost (@ibogost) March 6, 2019
Actually, lemme try mapping the 8 metaphors— Venkatesh Rao (@vgr) March 6, 2019
Organism: Blitzkrieg model
Culture: Improv theater
Psychic prison: Waterfall
Instrument of domination: OKRs
Flux: Distributed+parallel computing
Political system: Agile
Push the sky away by P. Correia (via https://flic.kr/p/ST8119 )
by Kaometet (via https://flic.kr/p/24qcFMp )
It took me many years to stop mixing up ‘eschatological’ and 'scatological’, though I suppose the former can be glossed as things taking a turn for the latter.— Soon-Tzu Speechley 孫子 (@speechleyish) March 6, 2019
Golden orb spider to smack you in the face. Yep I’m back in Sydney pic.twitter.com/ljsELszGSO— Belinda Barnet (@manjusrii) March 6, 2019
Alcoves under cliffs at low tide II by Peter de Graaff (via https://flic.kr/p/24qVvZK )
by Kaometet (via https://flic.kr/p/SUoqud )
‘The documents were written on hundreds of strips of bamboo, about the size of chopsticks, that seemed to date from 2,500 years ago, a time of intense intellectual ferment that gave rise to China’s greatest schools of thought.’ https://t.co/tjR5iU6XjH (via @speechleyish)— Justin Pickard (@justinpickard) March 5, 2019
Corvid pedagogy / remake all institutions as aviaries https://t.co/xx20Y3CMUz— Georgina Voss (@gsvoss) March 5, 2019
Something I’ve been meaning to say about The Tragedy of the Commons. Bear with me for a small thread on why our embrace of Hardin is a stain on environmentalism. tldr: we’ve let a flawed metaphor by a racist ecologist define environmental thinking for a half century. 1/— mattomildenberger (@mmildenberger) March 4, 2019
Went to a talk last week by someone in the Texas Bureau of Economic Geology & it’s safe to say that many in the oil & gas industry assume something very close to RCP 8.5 (worst-case) emissions scenario for rest of the century. Paris-compatible scenarios were framed as ridiculous.— Peter🌋Brannen (@PeterBrannen1) March 4, 2019
A summary of Octavia E. Butler’s advice for writers:— tamara k. nopper (@tamaranopper) March 3, 2019
1. “Read omnivorously…”
2. “Forget about talent.”
3. “Write, every day, whether you like it or not. Screw inspiration.”
4. “It’s certainly not a matter of sitting there and having things fall from the sky.”
’[D]rugs do not impart wisdom…any more than the microscope alone gives knowledge.They provide the raw materials of wisdom&are useful to the extent that[one]can integrate what they reveal into the whole pattern of his behavior&the whole system of his knowledge.’— Peter Sjöstedt-H (@PeterSjostedtH) March 3, 2019
– Alan #Watts pic.twitter.com/LLGqysONwt
Just gave a powerful talk in Hong Kong. I went on stage, delivered the entire speech in just 2 words – “Unlearn everything” – and left the room. Stunned silence.— Gen. Jeff Jarviss (@ProfJeffJarviss) March 3, 2019
Crop Yield Prediction Gold. Predictive systems are being heavily invested in by DARPA to predict social unrest via crop yield prediction. #agflation > rising demand of agricultural products driving up prices (key stressor in the Arab Spring, coined by Merrill Lynch in 2007). pic.twitter.com/ZY4tKamXh8— FRAUD (@FRAUD_la) March 3, 2019
When someone reaches for the prefix “post” to describe the evolutionary future of X it means they are having trouble seeing how emerging technologies might transform the *mechanisms* of X but have more clarity on the content.— Venkatesh Rao (@vgr) March 2, 2019
FLEX machine, 1968— Bret Victor (@worrydream) March 2, 2019
‘The “electronic” society is a special society contained within the wider “geometric” society …— Peter Sjöstedt-H (@PeterSjostedtH) March 3, 2019
the geometric society is a special society included in the vaster society of pure extension [etc.].’
– S. E. #Hooper
(1943, 214 – on #Whitehead) pic.twitter.com/5BL24Mp1vX
Documentary wants:— BlackWaxSolution (@eops) March 1, 2019
Adrian Sherwood and On U Sound
80s Liverpool Scene
Ninja Tunes Records
The Batcave scene/Goth/AlienSexFiend
How about you?
Damn, my GTD game has completely fallen apart in the last couple of years. My workflow is a global quantum entangled state of things moving along. I’m more wave function than set of particles 😕— Venkatesh Rao (@vgr) March 2, 2019
I need a quantum GTD where actions collapse work wave one schrodinger cat at a time
The remnants of the Jet Star roller-coaster in the ocean, almost five months after Superstorm Sandy, Seaside Heights, New Jersey
Photo credit: Lucas Jackson/Reuters
The Macintosh computer assembly line at the Apple factory in Cupertino, CA. January 25, 1984 © Jean-Pierre Laffont
‘Government funding and tourism revenues … have their limitations. But the mayor of Easter Island has come up with an innovative solution: seeking royalty payments from nations whose explorers took some of Easter Island’s statues centuries ago.’ 🗿 https://t.co/kiZykmL7xB— Justin Pickard (@justinpickard) March 2, 2019
I get grumpy when tech decides it’s not going to worry about ‘edge cases’. News flash: The real world is fractal. It’s *mostly* edge cases.— Deb Chachra (@debcha) March 1, 2019
My touchpoint is that the Air Force measured many dimensions of lots of people and realised there is no ‘average’ human they could design for—no one was even close to average for all the parameters. It’s why seats are adjustable. We are all edge cases.— Deb Chachra (@debcha) March 1, 2019
The Mouth of Krishna
2019, #801 Pigments, gampi paper and gold leaf.
The Mouth of Krishna
2019, #803 Pigments, gampi paper and gold leaf.
What you cooking Žižek? pic.twitter.com/vwQVqdlakE— Peter Sjöstedt-H (@PeterSjostedtH) March 1, 2019
Moral of the story is if you go browsing the weird e-commerce protuberances of Chinese manufacturing in the middle of the night half asleep, you might end up with fibre optic sneakers— Matt Webb (@genmon) March 1, 2019
“Plus, these estimates don’t allow for the possibility of World War III, a zombie apocalypse, a takeover by robot overlords” https://t.co/vZo09MB8y5— Alex Randall (@alex_randall) March 1, 2019
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It takes a whole lot of capital to convincingly render a bohemian scene in 2019. All those high-poly casual people, luxuriating in time and creativity within a relaxed urban environment.— Mat Dryhurst (@matdryhurst) March 1, 2019
Can anyone in the know illuminate which spoken language(s) pose the greatest difficulty to machine learning translation, and what about their articulation makes it such?— Stephen Fortune (@stephenfortune) February 28, 2019
Do octopus dream? They do have something similar to REM. And they do change colour while they are asleep. So maybe they really do dream. (Vid via Instagram OctoNation) pic.twitter.com/MHIlkxmWGW— Jan Freedman (@JanFreedman) February 27, 2019
A T SHIRT WITH A QR CODE ON IT AND WHEN YOU SCAN IT, YOU DOWNLOAD A PICTURE OF A SHIRT WITH A DIFFERENT QR CODE ON IT— the dog is a chad to them (@HEXCELERATOR) February 28, 2019
Words of the day: “trophic asynchrony”, “phenological mismatch” - disruptions to established seasonal patterns of migration, breeding, flowering, feeling etc caused by climate change.— Robert Macfarlane (@RobGMacfarlane) February 28, 2019
Swallows in February.
Untimely unsettlements of being.#LexiconForTheAnthropocene
Ty @ginbat pic.twitter.com/somiPUQlTL
[cw: media theory]— McKenzie Wark (@mckenziewark) February 27, 2019
I’m thinking you can make a greimas square of figures for post-broadcast infrastructure:
network = horizontal and connected
protocol = horizontal and disjunctive
the stack = vertical and connective
the vector = vertical and disjunctive.
People are scrutinizing airline travel as a source of greenhouse gas emissions.— Dr. Jonathan Foley (@GlobalEcoGuy) February 27, 2019
Yes, it seems pretty big, and mainly serves the wealthiest on the planet.
But keep numbers in perspective.
Airline travel is ~2.5% of global emissions.
Cement is 8%.
Food, Land, Forests is 24%.
I believe #gopher is making a viral comeback with good reasons; the hacker communities at large are reacting decades after Tim Berners Lee’s dismissal of it for the www and last not least the marketing of ‘solid’. Time has told what www has become. https://t.co/LA0f8b6Ffv— Jaromil (@jaromil) February 27, 2019
We live in anxious times, teetering on the edge of conflict, vulnerable to algorithmic manipulation. Our new work ‘TRIGGER WARNING’ looks for peace in this murky conflict.— Superflux (@Superflux) February 27, 2019
Commissioned by @modatunisa with a score by @nabihahiqbal🙅🏾https://t.co/8eNRpLbvZP pic.twitter.com/ccZdNS3Wjq
Looks like I actually have to read Kierkegaard’s “Either/Or” now. pic.twitter.com/9r2UOnIlyQ— Mario Klingemann (@quasimondo) February 27, 2019
Kodaiji in Kyoto unveils ‘Android Kannon’ designed to deliver portions of the Heart Sutra to the masses https://t.co/nyoOIcY7Tn— Soon-Tzu Speechley 孫子 (@speechleyish) February 26, 2019
You’re sat on a trolley hurtling down the track. Down one fork is a group of ethicists who think the trolly problem is the only materially relevant game in town. Down the other is software engineers who think technology is neutral.— Goth Merenghi (@farbandish) February 26, 2019
How fast do you accelerate?
Despite a weekend break from the debate, my attention keeps getting pulled back to the threads arguing that personal action to lower one’s carbon footprint is ineffective at best and counterproductive at worst toward the goal of climate protection.— Elizabeth Sawin (@bethsawin) February 25, 2019
For a year I’ve been reporting this story about major climate news, finally breaking today: A new simulation finds that global warming could cause stratocumulus clouds to disappear in as little as a century, which would add 8°C (14°F) of extra warming. https://t.co/1cSmLOsmOS— Natalie Wolchover (@nattyover) February 25, 2019
Woke up with the term “best case dystopia“ at the top of my mind. I’m gonna choose to blame @cascio for this.— Funranium Labs (@funranium) February 25, 2019
Archaeologists in Turkey discover an Ancient Mosaic Skeleton That Says: ‘Be cheerful, enjoy your life’ pic.twitter.com/23LskP6XLL— 41 Strange (@41Strange) February 24, 2019
A fun excerpt from my Voyager research: at one point, NASA realised that starting and stopping the craft’s tape recorder (used to buffer data before transmission to Earth) caused it to rotate around its yaw axis. Committing things to memory affected its motion.— Edwin (@dirigiblebill) February 24, 2019
WATCHED OVER BY ALGORITHMS” - Special Color Edition-
Appropriation in art is the use of pre-existing objects or images with little or no transformation applied to them.
This series of photographs taken from vintage magazines have been manually worked with a scanner, moving the image while scanning.
WATCHED OVER BY ALGORITHMS” - Special Color Edition-
This series of photographs taken from vintage magazines have been manually worked with a scanner, moving the image while scanning.
Got SpiralSynth Modular compiling again! Great thing about 15 year old software is that it takes practically no CPU to run :] pic.twitter.com/Bz4TSLgHoG— Dave Griffiths (FoAM Kernow) (@nebogeo) February 24, 2019
Also Kolmogorov complexity obviates metalanguage.— Rob Myers (@robmyers) February 22, 2019
Just in US, vehicule idling is burning 40k tons of CO2 daily, thats nearly 15k kt of CO2 yearly and BTC worldwide is 23k kt.— Gigabyted (@gigabyted4) February 22, 2019
So north america idling vehicule alone > the whole CO2 emission of bitcoin! And this is just idling vehicule alone!https://t.co/pTtux32UGB
Hilarious when people say stuff like “capitalism gave us the internet”. Capitalism has done everything in its power to hold back the internet, which is based on free exchange, cooperation, and open protocols. Capitalism has tried to lock down, destroy, and sabotage every step.— Existential Comics (@existentialcoms) February 22, 2019
MEDIUM EARTH of @theotolithgroup is generous to the slowness of the eye in gathering cinematic texture. The vastness of the sonic world it offers with low frequency, seismic gestures blends with evolving and morphing visual perspectives. #SAF19 #hereafter @brakkegrond pic.twitter.com/w9GH5o01Qs— Sonic Acts (@SonicActs) February 22, 2019
we believe in jouissance madness holiness and poetry pic.twitter.com/jZHH0ufAva— Ignota Books (@IgnotaBooks) February 22, 2019
“Bag of Tricks for Image Classification with Convolutional Neural Networks” is such a great paper. Really clear, and most importantly, amazing results - >94.5% imagenet with a simple rn50, beating even inception v3!— Jeremy Howard (@jeremyphoward) February 21, 2019
I’m working on replicating this now with fastai. pic.twitter.com/SqJgyBwRQK
https://t.co/7U5g0AjsQ7 is finally back up— 𝕹𝖞𝖝 スライム娘 (@NyxLandUnlife) February 21, 2019
t͕̲͉h̺̥a̶̹͈̹t̤̙͉ ̤̝i̗̖͇̳̕ͅͅs҉ ̷̩̖̝̟̤̪ǹ͈̖o̬͕̻ͅț͖̙͞ ḑ͔̮͇e̷̪a̹̙̘͈d̺̖ ̛̠͙̪̭̼̣͕w̘͝h͕̜͕i̡̬̯̱̘c̖̕h̨̰̯̗ ̙̖̗̻͠c̮̤̭̳̟͙̗a̖n̬͍͍͉͖̟ ̹̫̱̮̹̫̟͜e̱̮̻͚t̴e̡̙͎r̬̩̟̗n̠͚̱̟̤͍͜a̹̬͉̞ͅl̴̟̥̪ ̥l͉̻̺ị̱̹e̻̻̠̯̬̹̩
Shiv Integer, as a security professional, brings shame to the Internet Security profession according to this fellow professional. Sorry we did it wrong ¯\_(ツ)_/¯ pic.twitter.com/pgfKTsAkzk— M Plummer-Fernandez (@M_PF) February 21, 2019
A good tool to have, but which i definitely don’t have the skills to make: a bot that wide searches every known public “people finder” repository for folx’s data, sends deletion and opt-out requests en masse, and then scrubs itself. I think that could be helpful to a lot of peopl— Damien saw the Time-Knife once. Highly Recommended (@Wolven) February 20, 2019
Properly stoked to announce that I’ve just signed the contract to write a book with @VersoBooks on systems; if you like how I’ve taken a run at concrete, adult entertainment, Elon Musk, and heavy machines, you will (I hope) be on board with this ⚒— Georgina Voss (@gsvoss) February 20, 2019
The first population-level study on the link between gut bacteria and mental health identifies specific gut bacteria linked to depression and provides evidence that a wide range of gut bacteria can produce neuroactive compounds. Jeroen Raes (VIB-KU Leuven) and his team published these results today in the scientific journal Nature Microbiology. In their manuscript entitled ‘The neuroactive potential of the human gut microbiota in quality of life and depression’ Jeroen Raes and his team studied the relation between gut bacteria and quality of life and depression. The authors combined faecal microbiome data with general practitioner diagnoses of depression from 1,054 individuals enrolled in the Flemish Gut Flora Project. They identified specific groups of microorganisms that positively or negatively correlated with mental health. The authors found that two bacterial genera, Coprococcus and Dialister, were consistently depleted in individuals with depression, regardless of antidepressant treatment. The results were validated in an independent cohort of 1,063 individuals from the Dutch LifeLinesDEEP cohort and in a cohort of clinically depressed patients at the University Hospitals Leuven, Belgium.
privacytools.io is a socially motivated website that provides information for protecting your data security and privacy.
Datashader is a graphics pipeline system for creating meaningful representations of large datasets quickly and flexibly. Datashader breaks the creation of images into a series of explicit steps that allow computations to be done on intermediate representations. This approach allows accurate and effective visualizations to be produced automatically without trial-and-error parameter tuning, and also makes it simple for data scientists to focus on particular data and relationships of interest in a principled way.
The Home of Mathematical Knitting
Biodiversity of insects is threatened worldwide. Here, we present a comprehensive review of 73 historical reports of insect declines from across the globe, and systematically assess the underlying drivers. Our work reveals dramatic rates of decline that may lead to the extinction of 40% of the world’s insect species over the next few decades. […] The main drivers of species declines appear to be in order of importance: i) habitat loss and conversion to intensive agriculture and urbanisation; ii) pollution, mainly that by synthetic pesticides and fertilisers; iii) biological factors, including pathogens and introduced species; and iv) climate change