The goal of this blog is to create a list of super facts. Important facts that are true with very high certainty and yet surprising, misunderstood, or disputed by many. This blog aims to be challenging, educational, and fun, without it being clickbait. I determine veracity using evidence, data from reputable sources and longstanding scientific consensus. Prepare to be challenged (I am). Intentionally seek the truth not confirmation of your belief.
Super fact 139 : 2.17million species have been described but it is possible that as many as 20% of those are duplicates. However, most species are likely undiscovered.
The number of identified and named species in each taxonomic group. Since many species have not yet been described, this is a large underestimate of the total number of species in the world. Note about Taxonomic group: Scientists sort living things into groups based on how closely related they are. Each of these groups is called a taxonomic group. The groups fit inside one another, from broad to narrow. Mammals, birds and fish are broad groups. Within mammals, primates are a narrower group. And within primates, humans are just one species. Data source: International Union for Conservation of Nature Red List of Threatened species (2025). OurWorldinData.org/biodiversity | CC BY
As mentioned, a couple of million species have been named and identified. For a species to be formally described, it’s description must be published in a scientific journal or book. Considering this it is quite impressive that we’ve described millions of species, mostly insects and plants. However, according to science magazine the most likely number of species is in the range of 5 to 10 million eukaryotes. Eukaryotes are organisms consisting of complex cells with a membrane wrapped in nucleus and other internal compartments, which exclude viruses and bacteria.
This graph includes a more complete set of taxonomic groups. Data source: International Union for Conservation of Nature Red List of Threatened species (2025). OurWorldinData.org/biodiversity | CC BY
The fact that we have succeeded in describing two million species is impressive and surprising. That is a lot of work. The fact that there are likely millions of more species we haven’t found is equally surprising. There are surprisingly many species and unless you already knew this, this is surprising and perhaps mind-blowing information, and therefore a super fact.
Challenges in Defining a Species
Species is a unit of biological classification and it is the lowest taxonomic rank below genus. Species is often defined using the Biological Species Concept, which is defined as populations whose members can interbreed and produce fertile offspring, and are reproductively isolated from other groups. However, it is complicated. Asexual organisms, hybrids and ring species, and extinct species complicate things. Therefore, other ways of defining species exist.
The major ranks: domain, kingdom, phylum, class, order, family, genus, and species, applied to the red fox, Vulpes vulpes. Many classifications based on genetic analysis require more than these eight ranks, not all of which have distinct names. Annina Breen, CC BY-SA 4.0 <https://creativecommons.org/licenses/by-sa/4.0>, via Wikimedia Commons.
To define a species, you can also use genetic similarity, unique ecological niches, unique common ancestors, distinct physical traits, size, shape, and structural features. In other words, species concept is not simple and defining a species requires expertise. This makes it even more impressive that we have identified and described two million species.
I should add that there are also subspecies. A subspecies is a distinct population within a species that lives in a specific geographic region and differs in physical traits from other populations of the same species, while still being able to interbreed with them. An example is the dog which is a subspecies of the gray wolf.
Ring Species
As mentioned, a common definition of species is that two animals belong to the same species if they can interbreed in nature and produce viable, fertile offspring. As I pointed out it is not always that simple. An animal A may be able to successfully interbreed with an animal B, and that animal B may be able to successfully interbreed with an animal C, but animal A and C cannot interbreed. Animal A could be said to be a different species relative to animal C, but animal B could be said to be the same species as both animal A & C using the definition above.
A great geography related example of this is ring species. In a ring species, gene flow occurs between neighboring populations of a species, but at the ends of the ring the populations don’t interbreed.
Illustration of ring species, an example of how speciation can be relative. All the circles next to each other can interbreed but at the end it no longer works. Andrew Z. Colvin, CC BY-SA 4.0 <https://creativecommons.org/licenses/by-sa/4.0>, via Wikimedia Commons
Other Super Facts Related to Wildlife
A couple of interesting super facts related to species and wildlife are :
(70) The Wild Mammal Biomass Has Substantially Declined – click to visit
(71) The Extinction Rate is Much Higher Than the Natural Baseline Rate – click to visit
The first one is concerning the fact that we humans and our domesticated animals, cattle etc., have largely replaced wild animals and wild mammals. As the total biomass has increased the wild mammal biomass has decreased. The second super fact is about the current extinction rate being perhaps thousands of times higher than what is typical. A mass extinction event is often defined as when 75% of all species, or more, goes extinct within 2 million years. 200 years is only 0.01% of 2 million years so modern society has existed for an extremely short time. It is just a tiny blip on geological scales. So, even with an extinction rate thousands of times above normal, we haven’t gotten very far yet. Luckily, it looks like we might be turning things around, so perhaps we won’t be like the asteroid that exterminated the non-Avian dinosaurs.
Extinction of the dinosaurs when a large asteroid hits earth 66 million years ago. It was the last mass extinction event. Asset id: 2196200279 by funstarts33
Superfact 135: Artificial Intelligence is already more capable than humans in many areas, including reading comprehension, image recognition, language understanding, handwriting recognition, speech recognition, predictive reasoning, and much more. In 1997, a computer defeated the reigning world champion in chess. Artificial Intelligence is rapidly becoming more capable. A future Artificial Intelligence that exceeds the cognitive performance of humans in virtually all domains is possible.
Artificial intelligence and research concept. Shutterstock Asset id: 2314449325 by Stock-Asso
In the 1990’s I was doing robotics research at a University and I utilized Artificial Intelligence. Robots and Artificial Intelligence go hand in hand. I also worked for a robotics company, ABB Robotics, creating software for spot welding, arc welding, painting and palletizing robots. The robots were faster and more precise than humans and generated higher quality work consistently 24/7 without requiring a salary or a vacation. Some people lost their jobs when they were replaced by robots. However, the higher productivity allowed them to get better jobs with the same company, or elsewhere.
I used mostly the seven joint Robotics Research Corporation Robot for my robotics research. The robot was able to detect and avoid colliding with the objects surrounding it. I used echolocation for object detection.
The Large Language Models, LLMs, that have become very successful lately are just one type of AI. There are many other applications of Artificial Intelligence, AI, including robot motion planning, advanced control systems using AI, self-driving cars, image processing, optical character recognition, classification, facial recognition systems, medical imaging diagnostics, game playing such as chess playing computers, financial fraud detection, cybersecurity, investment robots, route optimization, mathematical proof generation, recommendation algorithms, virtual assistants, programming code generation, smart home devices, drug discovery, and that is just for starters.
More recently Artificial Intelligence has surpassed human capabilities in several fields. As mentioned, in 1997, a computer defeated the reigning world champion in chess. Soon chess programs with AI installed on a regular laptop could do the same. Imagine what an AI powered chess engine could do on a supercomputer. The chess playing capabilities of modern AI are vastly beyond that of any human. Below is a graph that shows how the chess playing capabilities of AI have evolved since 1985. The Elo score as of 2023 is 3,591. You can read more about this and get more information from the graph by clicking here.
Highest chess rating ever achieved by computers. Chess ability is measured with the Elo rating system, which is calculated based on game results. A higher rating indicates that a player is more likely to win a game. Data source: Chess.com (2020); SSDF (2022, 2023) – Learn more about this data OurWorldinData.org/artificial-intelligence | CC BY
The graphs below from Our World in Data show the test scores of AI systems on various capabilities relative to human performance. Within each domain, the initial performance of the AI is set to –100. Human performance is used as a baseline, set to zero. When the AI’s performance crosses the zero line, it scored more points than humans.
Data source: Kiela et al. (2023). Note: For each capability, the first year always shows a baseline of –100, even if better performance was recorded later that year. OurWorldinData.org/artificial-intelligence | CC BYAI Brain Neural Network Supercomputer. Many super brains. Many super capabilities. Shutterstock asset id: 2087062936 by PeachShutterStock
The graph below includes twelve capabilities. For eight capabilities AI exceed human capabilities including in reading comprehension, image recognition, language understanding, handwriting recognition, speech recognition, and predictive reasoning, nuanced language interpretation, and reading comprehension with unanswerable questions. For the remaining four AI had not yet exceeded human capabilities by 2023, but as you can see AI is catching up very quickly and may already have exceeded human capability in those areas too. These capabilities are math problem solving, general knowledge tests, code generation, and complex reasoning. You can play around with the graphs and read more about this topic here.
Data source: Kiela et al. (2023). Note: For each capability, the first year always shows a baseline of –100, even if better performance was recorded later that year. OurWorldinData.org/artificial-intelligence | CC BY
AI is also quickly improving its intellectual capabilities in science and mathematics. The graph below shows the capabilities of AI in solving FrontierMath problems. FrontierMath problems are 338 original math problems written by experts that take specialists hours or days to solve them. It typically took AI 10 hours to solve them. One recent famous example of AI’s capabilities in math was the famous Navier-Stokes problem. The full general mathematical problem of Navier-Stokes had not been solved by humans, but AI made significant progress on this 90 year old problem in 88 hours on September 5th, 2026. You can read more about it here, here, and here.
Share of FrontierMath problems solved correctly by AI models. The FrontierMath benchmark tests AI models on research-level mathematics problems that take expert mathematicians hours or days to solve. Data source: Epoch AI (2026) – Learn more about this data. Note: This chart shows performance on Tiers 1-3 of the FrontierMath benchmark (295 problems). OurWorldinData.org/artificial-intelligence | CC BY
It is easy to get the impression from the recent popularity of large language models, LLMs, such as Gemini, ChatGPT and Claude, that this was a specific invention that happened a few years ago and that AI has a specific narrow band of applications. However, AI has been around a long time, and LLMs is just one type of AI. AI is continuously surpassing human capabilities in many fields. It will be very different a few years from now, and after that it will be very different again. I believe this is important information that is not well understood and therefore a super fact.
In September of 2014 there was a book published with the title “Superintelligence: Paths, Dangers, Strategies” published. <<Link-15>> The author was Oxford professor Nick Bostrom. He has expertise in neuroscience, artificial intelligence and philosophy. His book was a New York Times bestseller that sent shockwaves around the world. He defined Superintelligence as “any intellect that greatly exceeds the cognitive performance of humans in virtually all domains of interest”. Nick Bostrom was not the first one to use the term Superintelligence, but he popularized it. And no, our President did not come up with that expression, and he is also misusing it.
The front cover of Superintelligence, Paths, Dangers, Strategies by Nick Bostrom. Click on the image to go to the Amazon page for the paperback version of the book.
In the book the author described possible pathways to the creation of what he calls a full brain simulation. A full brain simulation is the creation of a computer system that replicates the complete physical architecture, neural pathways, and synaptic connections of a biological brain. A robot, or AI system, featuring a full brain simulation would be able to replicate, or exceed, any human capability, including what we call free will and consciousness.
He discussed the potential dangers of this and explained why AI exceeding human capabilities could be dangerous. Robots and AI systems taking every job in existence is just one potential problem. Like the fate of animals depends on us, the fate of humankind would depend on the actions of the machine superintelligence. I will write a review for this book in the future.
It should be noted that autonomous AI agents have broken out of their testing sandboxes and hacked external systems on their own during evaluations. So much for AI not taking their own initiatives. You can read more about rogue AI activity here. A great movie about AI breaking out of their testing environment is Ex-Machina. Have you seen it? Below is a survey of people’s opinions on robot versus human intelligence, just as an FYI.
Views of Americans about robot vs. human intelligence. Survey respondents were asked, “Which one, if any, of the following statements do you most agree with?” Data source: YouGov (2025) – Learn more about this data. Note: Number of respondents ranges between n = 1001 and n = 1085 US adults per survey wave. OurWorldinData.org/artificial-intelligence | CC BY
Are Americans Worried About their jobs getting Automated?
The previous sections may bring up a number of a number of anxieties such as; will AI exterminate us? Will AI or robots with AI take my job? The graph below tells us what Americans think about it. It seems like Americans are overall not too worried about it. The graph below is included in this article.
How worried are Americans about their work being automated? All working adults. Survey respondents were asked, “How worried, if at all, are you that your type of work could be automated within your lifetime?” Data source: YouGov (2026) – Learn more about this data. Note: Number of respondents ranges between n = 460 and n = 568 US working adults per survey wave. OurWorldinData.org/artificial-intelligence | CC BY
What about LLMs ?
LLMs are currently the most popular “viral” AI. We can all access LLMs in our browsers. This has created the common misconception that Artificial Intelligence is the same as Large Language Models. However, LLMs represent only one branch of narrow AI systems designed to perform specific tasks.
Two Robots powered by Artificial Intelligence. Shutterstock Asset id: 558350728 by Willrow Hood.
LLMs use large neural networks with many hidden layers, so called deep learning algorithms, and they employ the Rumelhart backpropagation learning algorithm invented by David Rumelhart, Geoffrey Hinton, and Ronald Williams. Clearly neural networks with multiple hidden layers and using the Rumelhart backpropagation algorithm are incredibly successful but it is just one of many kinds of Artificial Intelligence algorithms, and who knows what we will see in the future. ChatGPT is thought to have a trillion parameters (or neurons + connections) whilst the human brain has 100 trillion connections. However, Moore’s law is still in effect so it is only a matter of time before artificial neural networks surpass our brains. Below is an overview of a neural network powering an LLM.
The dots in the diagram are neurons. With permission from kwholley63.
Other Super Fact Posts Related to Artificial Intelligence
Super fact 134 : The idea that people have a dominant “left brain” or “right brain” that dictates their personality is a popular myth. Brain imaging studies show that people do not have a dominant hemisphere.
Shutterstock asset id: 2483871211 by Shutterstock AI
The left and right sides of the brain do tend to specialize in different tasks. For example, language tends to be on the left, and attention more on the right. Brain images studies show that we do not have a dominant hemisphere. Both halves of the brain work together and are used equally in most activities. You can read more about the topic here, and here, or here.
Four Minute Video on Left Brain versus Right Brain
The YouTube video below is 4 minutes long, but it presents a good overview of left brain versus right brain myth.
How did the right brain versus left brain myth get started ?
That the brain is divided into a left side and a right side has been known since ancient times. In the 1860’s it was discovered that speech was based predominantly in the left hemisphere of the brain. In the 1960’s Psychobiologist Roger Sperry studied “split-brain” patients who had their corpus callosum (the nerve bundle connecting the two halves) severed to treat epilepsy. Their neuroscience research seemed to show that one side of the brain tends to be more dominant in each person. Popular culture took these findings out of context and the right brain versus left brain myth took hold.
The human brain is divided into two hemispheres–left and right. Scientists continue to explore how some cognitive functions tend to be dominated by one side or the other; that is, how they are lateralized. Purple is the Right cerebral hemisphere. Blue is the Left cerebral hemisphere. Polygon data were generated by Database Center for Life Science (DBCLS), CC BY-SA 2.1 JP <https://creativecommons.org/licenses/by-sa/2.1/jp/deed.en>, via Wikimedia Commons. The gif is taken from this link.
Later research showed that the human brain does not favor one side over the other and that one side is not more dominant then the other, unless it is damaged. The two sides of the brain work in concert. You can read more about the topic here.
A related fascinating fact is that the human brain contains about 100 billion neurons and 100 trillion connections. That is 100 trillion parameters to use Artificial Intelligence speech. Which should be compared to the 175 billion (not trillion) parameters in ChatGPT 3.5, and one trillion in ChatGPT 4.0. Well AI neurons and connections/weights and those in the brain are not directly comparable. Another related interesting myth is that we only use 10% of our brain. We use our entire brain.
Superfact 133: Water vapor is responsible for roughly half of Earth’s total greenhouse effect, but unlike carbon dioxide or methane, water vapor condenses and falls as precipitation. Water molecules only stay in the atmosphere for about two weeks. We do not directly control global water vapor levels. When carbon dioxide warms the planet the atmosphere holds more water vapor, which amplifies the initial warming. However, water vapor does not drive global warming. Carbon dioxide emissions and to a lesser degree methane emissions drive global warming. Water vapor just amplifies the effect.
Water vapor is water in gaseous form, and it is invisible. This is a 3D illustration of a water molecule (H2O – two hydrogen atoms and one Oxygen atom). Shutterstock asset id: 1656757654 by Anusorn Nakdee
On social media you often see the claim that water vapor is a more powerful greenhouse gas than carbon dioxide, and the implicit implication is supposedly that our carbon emissions are not the problem. Alternatively, since water vapor has been around forever and is a more powerful greenhouse gas than carbon dioxide, global warming can’t be caused by greenhouse gases. What is getting lost in these posts is that we are not adding water vapor to the atmosphere like we are adding carbon dioxide (or methane) to the atmosphere. The amount of water vapor in the atmosphere will increase because a warmer atmosphere can hold more water vapor, but that is because of our carbon emissions in the first place. You can read more about that here, and here, and here.
Illustration of simple water cycle diagram. Water vapor, a greenhouse gas, is added to the atmosphere from evaporation (the sea) and transpiration (soil, plants, etc.) Then it condenses into clouds and comes down as precipitation. It collects in rivers, etc., and ends up in oceans and lakes. – Shutterstock asset id: Asset id: 2524245337 by zombiu26
A related fact is that the water cycle is a relatively fast cycle compared to the carbon cycle. A water molecule stays in the atmosphere on average for two weeks according to MIT and nine days according to Wikipedia. Our carbon emissions stay in the atmosphere for several hundred years. In short, water vapor is not the driver of the current rapid global warming. That is chiefly carbon dioxide, but also methane, and deforestation.
It does not matter that water vapor causes a larger percentage of the warming than carbon dioxide. It is not what is causing the increase in the average global temperature. Since so many people have been fooled by the water vapor misdirection, incorrectly thinking that carbon dioxide is unimportant because water vapor is a more important greenhouse gas, this is an important fact that will come as a surprise to many. Therefore, it is a super fact in my opinion.
More on the Water Cycle and the Greenhouse Effect
Below is a more detailed illustration of the water cycle for those who are interested. It should be noted that even though water vapor is not driving the rapid global warming we are witnessing, the very rapid global warming we are experiencing is affecting the water cycle, for example, the precipitation patterns around the world. You can read more about that here.
Water cycle showing human influences and major pools (storages) and fluxes. This is a more detailed picture than the one above. LangeLeslie and Anna Wright, CC BY-SA 4.0 https://creativecommons.org/licenses/by-sa/4.0, via Wikimedia Commons. This picture is taken from here.
Another less simplistic argument based on water vapor as a greenhouse gas that tries to claim that carbon dioxide is not behind the rapid global warming we are seeing is that water vapor is such an effective greenhouse gas across all frequences that there is not much room for carbon dioxide to make it worse.
However, if you look carefully, you see that carbon dioxide and water vapor complement each other in the spectra and in addition, as mentioned, we are not increasing water vapor directly, but we are increasing the amount of carbon dioxide directly. It should be noted that, in addition, satellite measurements directly confirm that our emissions are warming the planet. The topic of absorption at different frequencies by carbon dioxide and water vapor is explored in greater detail in the book “The Physics of Climate Change by Lawrence M. Krauss”, which I reviewed here.
The absorption bands of Earth’s atmosphere (grey color) delimit its atmospheric windows (middle panel) and the effect they have on both down going solar radiation and upgoing thermal radiation emitted near the surface is shown in the top panel. The individual absorption spectra of major greenhouse gases plus Rayleigh scattering are shown in the lower panel. This figure was prepared by Robert A. Rohde Д.Ильин: vectorization (File:Atmospheric Transmission-ru.svg); Cepheiden translation back to english, CC0, via Wikimedia Commons. This figure below is taken from this website. Physical drivers of global warming that have happened so far. Future global warming potential for long-lived drivers like carbon dioxide emissions is not represented. Whiskers on each bar show the possible error range. Eric Fisk, CC BY-SA 4.0 https://creativecommons.org/licenses/by-sa/4.0, via Wikimedia Commons. The illustration is taken from this site.
Conclusion
Water vapor is a powerful greenhouse gas but unlike carbon dioxide and methane it is not driving the rapid global warming that we are seeing. We are directly increasing water vapor via water vapor emissions, and if we did it would just come raining back down pretty quickly. However, when carbon dioxide warms the planet the atmosphere holds more water vapor, which amplifies the initial warming.
Super fact 132 : An estimated 100 trillion ghostly elementary particles, called neutrinos, pass through your body every second, which is 237 sextillion particles in 75 years. Despite that fact the chance that even a single neutrino will interact with an atom in your body during your entire life is about 1 in 4. These extremely abundant particles pass right through you as well as planets without interactions, like ghosts.
100 trillion neutrinos, almost entirely undetectable elementary particles, pass right through your body every second, without touching a single atom in your body, as if you don’t exist. I generated the picture with the help of ChatGPT.
Neutrinos are tiny subatomic particles, often called ‘ghost particles‘ because they barely interact with anything else. They are capable of passing right through our planet Earth as if it wasn’t there. As mentioned, an estimated 100 trillion neutrinos pass through your body every second.
Neutrinos do not interact with electromagnetic forces and not with the strong nuclear force. The electromagnetic forces are what is governing molecules, atoms, and matter and the strong nuclear force governs the nucleus of atoms. The only forces that neutrinos interact with are the weak nuclear force and gravity, which both are weak forces, and the weak nuclear force has a very short range. In addition, the mass of neutrinos is extremely tiny. That is why neutrinos pass through atoms as if they aren’t there, and it is why trillions of neutrinos can pass through your body without touching you even the slightest and it is also why they are completely harmless. This also makes them extremely hard to detect.
Alpha radiation is stopped by paper. Beta radiation (electrons) is stopped by aluminum foil. X-rays and gamma radiation (high energy photons) are stopped by a sheet of lead. Neutrons with certain energies can be stopped by a container of water. Neutrinos cannot even be stopped by a planet. Shutterstock asset id: 2313420693 by Anshuman Rath
An enormous amount of neutrinos flows right through your body as if you don’t exist. They are coming from the sky and from the ground below after passing through earth and none of them will touch any part of you. This is a mind blowing and surprising but not well known fact and therefore a super fact in my opinion.
The Mass of Elementary Particles
More than 200 subatomic particles have been discovered and there are probably many more that have not yet been discovered. Examples of subatomic particles are protons, neutrons and electrons. However, only some of them are elementary particles, or in other words fundamental particles. The electron is a fundamental particle, but the proton and the neutrons are not. Protons and neutrons are called composite particles and consist of quarks, gluons and mesons. The neutrino is an example of a fundamental particle like the electron. Quarks are other examples of fundamental particles.
Electrons are lightweight. They weigh 0.511 MeV/c², which is 1,836 times lighter than a proton, which weighs 938.272 MeV/c². The positron, which is the electrons anti-particle weighs exactly the same as the electron. The muon, which is very similar to an electron but is unstable and is 206.77 times heavier than an electron weighs 105.66 MeV/c². The tau is also similar to an electron and is about 3,477 times heavier than an electron and weighs 1,776.86 MeV/c². Quarks are also much heavier than electrons. Photons and gluons are massless.
The neutrino is a lepton and is in some ways similar to an electron, but it has no charge and does not interact with electromagnetic forces at all. The neutron also does not have any charge, but it does interact with electromagnetic forces, which makes it a lot easier to detect. As in the case for the electron there are lighter and heavier versions of neutrinos, the electron-neutrino, the muon-neutrino and the tau-neutrino. Here comes the shocker; the heaviest flavor of neutrino, the tau-neutrino weighs less than 0.12 eV/c² or 0.00000012 MeV/c² making it at least 4 million times lighter than an electron. However, the neutrinos may be a lot lighter than that. We don’t know. They have mass but it is very tiny.
Considering how tiny neutrinos are, and that they don’t interact with the electromagnetic force at all (unlike other neutral particles) and don’t interact with the strong nuclear force at all, it is understandable that neutrinos are like ghost particles, almost impossible to detect. Neutrinos are too light to be so called dark matter, but a hypothetical heavier form of neutrino called the sterile neutrino is a plausible candidate for dark matter.
